Multivariate poisson lognormal modeling of crashes by type and severity on rural two lane highways.
Wang, Kai; Ivan, John N; Ravishanker, Nalini; Jackson, Eric
2017-02-01
In an effort to improve traffic safety, there has been considerable interest in estimating crash prediction models and identifying factors contributing to crashes. To account for crash frequency variations among crash types and severities, crash prediction models have been estimated by type and severity. The univariate crash count models have been used by researchers to estimate crashes by crash type or severity, in which the crash counts by type or severity are assumed to be independent of one another and modelled separately. When considering crash types and severities simultaneously, this may neglect the potential correlations between crash counts due to the presence of shared unobserved factors across crash types or severities for a specific roadway intersection or segment, and might lead to biased parameter estimation and reduce model accuracy. The focus on this study is to estimate crashes by both crash type and crash severity using the Integrated Nested Laplace Approximation (INLA) Multivariate Poisson Lognormal (MVPLN) model, and identify the different effects of contributing factors on different crash type and severity counts on rural two-lane highways. The INLA MVPLN model can simultaneously model crash counts by crash type and crash severity by accounting for the potential correlations among them and significantly decreases the computational time compared with a fully Bayesian fitting of the MVPLN model using Markov Chain Monte Carlo (MCMC) method. This paper describes estimation of MVPLN models for three-way stop controlled (3ST) intersections, four-way stop controlled (4ST) intersections, four-way signalized (4SG) intersections, and roadway segments on rural two-lane highways. Annual Average Daily traffic (AADT) and variables describing roadway conditions (including presence of lighting, presence of left-turn/right-turn lane, lane width and shoulder width) were used as predictors. A Univariate Poisson Lognormal (UPLN) was estimated by crash type and severity for each highway facility, and their prediction results are compared with the MVPLN model based on the Average Predicted Mean Absolute Error (APMAE) statistic. A UPLN model for total crashes was also estimated to compare the coefficients of contributing factors with the models that estimate crashes by crash type and severity. The model coefficient estimates show that the signs of coefficients for presence of left-turn lane, presence of right-turn lane, land width and speed limit are different across crash type or severity counts, which suggest that estimating crashes by crash type or severity might be more helpful in identifying crash contributing factors. The standard errors of covariates in the MVPLN model are slightly lower than the UPLN model when the covariates are statistically significant, and the crash counts by crash type and severity are significantly correlated. The model prediction comparisons illustrate that the MVPLN model outperforms the UPLN model in prediction accuracy. Therefore, when predicting crash counts by crash type and crash severity for rural two-lane highways, the MVPLN model should be considered to avoid estimation error and to account for the potential correlations among crash type counts and crash severity counts. Copyright © 2016 Elsevier Ltd. All rights reserved.
A kinetic energy model of two-vehicle crash injury severity.
Sobhani, Amir; Young, William; Logan, David; Bahrololoom, Sareh
2011-05-01
An important part of any model of vehicle crashes is the development of a procedure to estimate crash injury severity. After reviewing existing models of crash severity, this paper outlines the development of a modelling approach aimed at measuring the injury severity of people in two-vehicle road crashes. This model can be incorporated into a discrete event traffic simulation model, using simulation model outputs as its input. The model can then serve as an integral part of a simulation model estimating the crash potential of components of the traffic system. The model is developed using Newtonian Mechanics and Generalised Linear Regression. The factors contributing to the speed change (ΔV(s)) of a subject vehicle are identified using the law of conservation of momentum. A Log-Gamma regression model is fitted to measure speed change (ΔV(s)) of the subject vehicle based on the identified crash characteristics. The kinetic energy applied to the subject vehicle is calculated by the model, which in turn uses a Log-Gamma Regression Model to estimate the Injury Severity Score of the crash from the calculated kinetic energy, crash impact type, presence of airbag and/or seat belt and occupant age. Copyright © 2010 Elsevier Ltd. All rights reserved.
Multivariate spatial models of excess crash frequency at area level: case of Costa Rica.
Aguero-Valverde, Jonathan
2013-10-01
Recently, areal models of crash frequency have being used in the analysis of various area-wide factors affecting road crashes. On the other hand, disease mapping methods are commonly used in epidemiology to assess the relative risk of the population at different spatial units. A natural next step is to combine these two approaches to estimate the excess crash frequency at area level as a measure of absolute crash risk. Furthermore, multivariate spatial models of crash severity are explored in order to account for both frequency and severity of crashes and control for the spatial correlation frequently found in crash data. This paper aims to extent the concept of safety performance functions to be used in areal models of crash frequency. A multivariate spatial model is used for that purpose and compared to its univariate counterpart. Full Bayes hierarchical approach is used to estimate the models of crash frequency at canton level for Costa Rica. An intrinsic multivariate conditional autoregressive model is used for modeling spatial random effects. The results show that the multivariate spatial model performs better than its univariate counterpart in terms of the penalized goodness-of-fit measure Deviance Information Criteria. Additionally, the effects of the spatial smoothing due to the multivariate spatial random effects are evident in the estimation of excess equivalent property damage only crashes. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.
2017-09-01
Many studies have utilized the spatial correlations among traffic crash data to develop crash prediction models with the aim to investigate the influential factors or predict crash counts at different sites. The spatial correlation have been observed to account for heterogeneity in different forms of weight matrices which improves the estimation performance of models. But very rarely have the weight matrices been compared for the prediction accuracy for estimation of crash counts. This study was targeted at the comparison of two different approaches for modelling the spatial correlations among crash data at macro-level (County). Multivariate Full Bayesian crash prediction models were developed using Decay-50 (distance-based) and Queen-1 (adjacency-based) weight matrices for simultaneous estimation crash counts of four different modes: vehicle, motorcycle, bike, and pedestrian. The goodness-of-fit and different criteria for accuracy at prediction of crash count reveled the superiority of Decay-50 over Queen-1. Decay-50 was essentially different from Queen-1 with the selection of neighbors and more robust spatial weight structure which rendered the flexibility to accommodate the spatially correlated crash data. The consistently better performance of Decay-50 at prediction accuracy further bolstered its superiority. Although the data collection efforts to gather centroid distance among counties for Decay-50 may appear to be a downside, but the model has a significant edge to fit the crash data without losing the simplicity of computation of estimated crash count.
Safety analytics for integrating crash frequency and real-time risk modeling for expressways.
Wang, Ling; Abdel-Aty, Mohamed; Lee, Jaeyoung
2017-07-01
To find crash contributing factors, there have been numerous crash frequency and real-time safety studies, but such studies have been conducted independently. Until this point, no researcher has simultaneously analyzed crash frequency and real-time crash risk to test whether integrating them could better explain crash occurrence. Therefore, this study aims at integrating crash frequency and real-time safety analyses using expressway data. A Bayesian integrated model and a non-integrated model were built: the integrated model linked the crash frequency and the real-time models by adding the logarithm of the estimated expected crash frequency in the real-time model; the non-integrated model independently estimated the crash frequency and the real-time crash risk. The results showed that the integrated model outperformed the non-integrated model, as it provided much better model results for both the crash frequency and the real-time models. This result indicated that the added component, the logarithm of the expected crash frequency, successfully linked and provided useful information to the two models. This study uncovered few variables that are not typically included in the crash frequency analysis. For example, the average daily standard deviation of speed, which was aggregated based on speed at 1-min intervals, had a positive effect on crash frequency. In conclusion, this study suggested a methodology to improve the crash frequency and real-time models by integrating them, and it might inspire future researchers to understand crash mechanisms better. Copyright © 2017 Elsevier Ltd. All rights reserved.
The use of generalized estimating equations in the analysis of motor vehicle crash data.
Hutchings, Caroline B; Knight, Stacey; Reading, James C
2003-01-01
The purpose of this study was to determine if it is necessary to use generalized estimating equations (GEEs) in the analysis of seat belt effectiveness in preventing injuries in motor vehicle crashes. The 1992 Utah crash dataset was used, excluding crash participants where seat belt use was not appropriate (n=93,633). The model used in the 1996 Report to Congress [Report to congress on benefits of safety belts and motorcycle helmets, based on data from the Crash Outcome Data Evaluation System (CODES). National Center for Statistics and Analysis, NHTSA, Washington, DC, February 1996] was analyzed for all occupants with logistic regression, one level of nesting (occupants within crashes), and two levels of nesting (occupants within vehicles within crashes) to compare the use of GEEs with logistic regression. When using one level of nesting compared to logistic regression, 13 of 16 variance estimates changed more than 10%, and eight of 16 parameter estimates changed more than 10%. In addition, three of the independent variables changed from significant to insignificant (alpha=0.05). With the use of two levels of nesting, two of 16 variance estimates and three of 16 parameter estimates changed more than 10% from the variance and parameter estimates in one level of nesting. One of the independent variables changed from insignificant to significant (alpha=0.05) in the two levels of nesting model; therefore, only two of the independent variables changed from significant to insignificant when the logistic regression model was compared to the two levels of nesting model. The odds ratio of seat belt effectiveness in preventing injuries was 12% lower when a one-level nested model was used. Based on these results, we stress the need to use a nested model and GEEs when analyzing motor vehicle crash data.
Crash protectiveness to occupant injury and vehicle damage: An investigation on major car brands.
Huang, Helai; Li, Chunyang; Zeng, Qiang
2016-01-01
This study sets out to investigate vehicles' crash protectiveness on occupant injury and vehicle damage, which can be deemed as an extension of the traditional crash worthiness. A Bayesian bivariate hierarchical ordered logistic (BVHOL) model is developed to estimate the occupant protectiveness (OP) and vehicle protectiveness (VP) of 23 major car brands in Florida, with considering vehicles' crash aggressivity and controlling external factors. The proposed model not only takes over the strength of the existing hierarchical ordered logistic (HOL) model, i.e. specifying the order characteristics of crash outcomes and cross-crash heterogeneities, but also accounts for the correlation between the two crash responses, driver injury and vehicle damage. A total of 7335 two-vehicle-crash records with 14,670 cars involved in Florida are used for the investigation. From the estimation results, it's found that most of the luxury cars such as Cadillac, Volvo and Lexus possess excellent OP and VP while some brands such as KIA and Saturn perform very badly in both aspects. The ranks of the estimated safety performance indices are even compared to the counterparts in Huang et al. study [Huang, H., Hu, S., Abdel-Aty, M., 2014. Indexing crash worthiness and crash aggressivity by major car brands. Safety Science 62, 339-347]. The results show that the rank of occupant protectiveness index (OPI) is relatively coherent with that of crash worthiness index, but the ranks of crash aggressivity index in both studies is more different from each other. Meanwhile, a great discrepancy between the OPI rank and that of vehicle protectiveness index is found. What's more, the results of control variables and hyper-parameters estimation as well as comparison to HOL models with separate or identical threshold errors, demonstrate the validity and advancement of the proposed model and the robustness of the estimated OP and VP. Copyright © 2015 Elsevier Ltd. All rights reserved.
Keall, Michael D; Newstead, Stuart
2016-01-01
Vehicle safety rating systems aim firstly to inform consumers about safe vehicle choices and, secondly, to encourage vehicle manufacturers to aspire to safer levels of vehicle performance. Primary rating systems (that measure the ability of a vehicle to assist the driver in avoiding crashes) have not been developed for a variety of reasons, mainly associated with the difficult task of disassociating driver behavior and vehicle exposure characteristics from the estimation of crash involvement risk specific to a given vehicle. The aim of the current study was to explore different approaches to primary safety estimation, identifying which approaches (if any) may be most valid and most practical, given typical data that may be available for producing ratings. Data analyzed consisted of crash data and motor vehicle registration data for the period 2003 to 2012: 21,643,864 observations (representing vehicle-years) and 135,578 crashed vehicles. Various logistic models were tested as a means to estimate primary safety: Conditional models (conditioning on the vehicle owner over all vehicles owned); full models not conditioned on the owner, with all available owner and vehicle data; reduced models with few variables; induced exposure models; and models that synthesised elements from the latter two models. It was found that excluding young drivers (aged 25 and under) from all primary safety estimates attenuated some high risks estimated for make/model combinations favored by young people. The conditional model had clear biases that made it unsuitable. Estimates from a reduced model based just on crash rates per year (but including an owner location variable) produced estimates that were generally similar to the full model, although there was more spread in the estimates. The best replication of the full model estimates was generated by a synthesis of the reduced model and an induced exposure model. This study compared approaches to estimating primary safety that could mimic an analysis based on a very rich data set, using variables that are commonly available when registered fleet data are linked to crash data. This exploratory study has highlighted promising avenues for developing primary safety rating systems for vehicle makes and models.
Lord, Dominique
2006-07-01
There has been considerable research conducted on the development of statistical models for predicting crashes on highway facilities. Despite numerous advancements made for improving the estimation tools of statistical models, the most common probabilistic structure used for modeling motor vehicle crashes remains the traditional Poisson and Poisson-gamma (or Negative Binomial) distribution; when crash data exhibit over-dispersion, the Poisson-gamma model is usually the model of choice most favored by transportation safety modelers. Crash data collected for safety studies often have the unusual attributes of being characterized by low sample mean values. Studies have shown that the goodness-of-fit of statistical models produced from such datasets can be significantly affected. This issue has been defined as the "low mean problem" (LMP). Despite recent developments on methods to circumvent the LMP and test the goodness-of-fit of models developed using such datasets, no work has so far examined how the LMP affects the fixed dispersion parameter of Poisson-gamma models used for modeling motor vehicle crashes. The dispersion parameter plays an important role in many types of safety studies and should, therefore, be reliably estimated. The primary objective of this research project was to verify whether the LMP affects the estimation of the dispersion parameter and, if it is, to determine the magnitude of the problem. The secondary objective consisted of determining the effects of an unreliably estimated dispersion parameter on common analyses performed in highway safety studies. To accomplish the objectives of the study, a series of Poisson-gamma distributions were simulated using different values describing the mean, the dispersion parameter, and the sample size. Three estimators commonly used by transportation safety modelers for estimating the dispersion parameter of Poisson-gamma models were evaluated: the method of moments, the weighted regression, and the maximum likelihood method. In an attempt to complement the outcome of the simulation study, Poisson-gamma models were fitted to crash data collected in Toronto, Ont. characterized by a low sample mean and small sample size. The study shows that a low sample mean combined with a small sample size can seriously affect the estimation of the dispersion parameter, no matter which estimator is used within the estimation process. The probability the dispersion parameter becomes unreliably estimated increases significantly as the sample mean and sample size decrease. Consequently, the results show that an unreliably estimated dispersion parameter can significantly undermine empirical Bayes (EB) estimates as well as the estimation of confidence intervals for the gamma mean and predicted response. The paper ends with recommendations about minimizing the likelihood of producing Poisson-gamma models with an unreliable dispersion parameter for modeling motor vehicle crashes.
Aguero-Valverde, Jonathan
2013-01-01
In recent years, complex statistical modeling approaches have being proposed to handle the unobserved heterogeneity and the excess of zeros frequently found in crash data, including random effects and zero inflated models. This research compares random effects, zero inflated, and zero inflated random effects models using a full Bayes hierarchical approach. The models are compared not just in terms of goodness-of-fit measures but also in terms of precision of posterior crash frequency estimates since the precision of these estimates is vital for ranking of sites for engineering improvement. Fixed-over-time random effects models are also compared to independent-over-time random effects models. For the crash dataset being analyzed, it was found that once the random effects are included in the zero inflated models, the probability of being in the zero state is drastically reduced, and the zero inflated models degenerate to their non zero inflated counterparts. Also by fixing the random effects over time the fit of the models and the precision of the crash frequency estimates are significantly increased. It was found that the rankings of the fixed-over-time random effects models are very consistent among them. In addition, the results show that by fixing the random effects over time, the standard errors of the crash frequency estimates are significantly reduced for the majority of the segments on the top of the ranking. Copyright © 2012 Elsevier Ltd. All rights reserved.
Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan
2014-09-01
Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.
Lord, Dominique; Park, Peter Young-Jin
2008-07-01
Traditionally, transportation safety analysts have used the empirical Bayes (EB) method to improve the estimate of the long-term mean of individual sites; to correct for the regression-to-the-mean (RTM) bias in before-after studies; and to identify hotspots or high risk locations. The EB method combines two different sources of information: (1) the expected number of crashes estimated via crash prediction models, and (2) the observed number of crashes at individual sites. Crash prediction models have traditionally been estimated using a negative binomial (NB) (or Poisson-gamma) modeling framework due to the over-dispersion commonly found in crash data. A weight factor is used to assign the relative influence of each source of information on the EB estimate. This factor is estimated using the mean and variance functions of the NB model. With recent trends that illustrated the dispersion parameter to be dependent upon the covariates of NB models, especially for traffic flow-only models, as well as varying as a function of different time-periods, there is a need to determine how these models may affect EB estimates. The objectives of this study are to examine how commonly used functional forms as well as fixed and time-varying dispersion parameters affect the EB estimates. To accomplish the study objectives, several traffic flow-only crash prediction models were estimated using a sample of rural three-legged intersections located in California. Two types of aggregated and time-specific models were produced: (1) the traditional NB model with a fixed dispersion parameter and (2) the generalized NB model (GNB) with a time-varying dispersion parameter, which is also dependent upon the covariates of the model. Several statistical methods were used to compare the fitting performance of the various functional forms. The results of the study show that the selection of the functional form of NB models has an important effect on EB estimates both in terms of estimated values, weight factors, and dispersion parameters. Time-specific models with a varying dispersion parameter provide better statistical performance in terms of goodness-of-fit (GOF) than aggregated multi-year models. Furthermore, the identification of hazardous sites, using the EB method, can be significantly affected when a GNB model with a time-varying dispersion parameter is used. Thus, erroneously selecting a functional form may lead to select the wrong sites for treatment. The study concludes that transportation safety analysts should not automatically use an existing functional form for modeling motor vehicle crashes without conducting rigorous analyses to estimate the most appropriate functional form linking crashes with traffic flow.
Crash probability estimation via quantifying driver hazard perception.
Li, Yang; Zheng, Yang; Wang, Jianqiang; Kodaka, Kenji; Li, Keqiang
2018-07-01
Crash probability estimation is an important method to predict the potential reduction of crash probability contributed by forward collision avoidance technologies (FCATs). In this study, we propose a practical approach to estimate crash probability, which combines a field operational test and numerical simulations of a typical rear-end crash model. To consider driver hazard perception characteristics, we define a novel hazard perception measure, called as driver risk response time, by considering both time-to-collision (TTC) and driver braking response to impending collision risk in a near-crash scenario. Also, we establish a driving database under mixed Chinese traffic conditions based on a CMBS (Collision Mitigation Braking Systems)-equipped vehicle. Applying the crash probability estimation in this database, we estimate the potential decrease in crash probability owing to use of CMBS. A comparison of the results with CMBS on and off shows a 13.7% reduction of crash probability in a typical rear-end near-crash scenario with a one-second delay of driver's braking response. These results indicate that CMBS is positive in collision prevention, especially in the case of inattentive drivers or ole drivers. The proposed crash probability estimation offers a practical way for evaluating the safety benefits in the design and testing of FCATs. Copyright © 2017 Elsevier Ltd. All rights reserved.
Median barrier crash severity: some new insights.
Hu, Wen; Donnell, Eric T
2010-11-01
Median barrier is used to prevent cross-median crashes on divided highways. Although it is well documented that crash frequencies increase after installing median barrier, little is known about median barrier crash severity outcomes. The present study estimated a nested logit model of median barrier crash severity using 5 years of data from rural divided highways in North Carolina. Vehicle, driver, roadway, and median cross-section design data were factors considered in the model. A unique aspect of the data used to estimate the model was the availability of median barrier placement and median cross-slope data, two elements not commonly included in roadway inventory data files. The estimation results indicate that collisions with a cable median barrier increase the probability of less-severe crash outcomes relative to collisions with a concrete or guardrail median barrier. Increasing the median barrier offset was associated with a lower probability of severe crash outcomes. The presence of a cable median barrier installed on foreslopes that were between 6H:1V and 10H:1V were associated with an increase in severe crash probabilities when compared to cable median barrier installations on foreslopes that were 10H:1V or flatter. 2010 Elsevier Ltd. All rights reserved.
van Petegem, J W H Jan Hendrik; Wegman, Fred
2014-06-01
About 50% of all road traffic fatalities and 30% of all traffic injuries in the Netherlands take place on rural roads with a speed limit of 80 km/h. About 50% of these crashes are run-off-road (ROR) crashes. To reduce the number of crashes on this road type, attention should be put on improving the safety of the infrastructure of this road type. With the development of a crash prediction model for ROR crashes on rural roads with a speed limit of 80 km/h, this study aims at making a start in providing the necessary new tools for a proactive road safety policy to road administrators in the Netherlands. The paper presents a basic framework of the model development, comprising a problem description, the data used, and the method for developing the model. The model is developed with the utilization of generalized linear modeling in SAS, using the Negative Binomial probability distribution. A stepwise approach is used by adding one variable at a time, which forms the basis for striving for a parsimonious model and the evaluation of the model. The likelihood ratio test and the Akaike information criterion are used to assess the model fit, and parameter estimations are compared with literature findings to check for consistency. The results comprise two important outcomes. One is a crash prediction model (CPM) to estimate the relative safety of rural roads with a speed limit of 80 km/h in a network. The other is a small set of estimated effects of traffic volume and road characteristics on ROR crash frequencies. The results may lead to adjustments of the road design guidelines in the Netherlands and to further research on the quantification of risk factors with crash prediction models. Copyright © 2014 Elsevier Ltd. All rights reserved.
Wu, Kun-Feng; Donnell, Eric T; Aguero-Valverde, Jonathan
2014-06-01
To approach the goal of "Toward Zero Deaths," there is a need to develop an analysis paradigm to better understand the effects of a countermeasure on reducing the number of severe crashes. One of the goals in traffic safety research is to search for an effective treatment to reduce fatal and major injury crashes, referred to as severe crashes. To achieve this goal, the selection of promising countermeasures is of utmost importance, and relies on the effectiveness of candidate countermeasures in reducing severe crashes. Although it is important to precisely evaluate the effectiveness of candidate countermeasures in reducing the number of severe crashes at a site, the current state-of-the-practice often leads to biased estimates. While there have been a few advanced statistical models developed to mitigate the problem in practice, these models are computationally difficult to estimate because severe crashes are dispersed spatially and temporally, and cannot be integrated into the Highway Safety Manual framework, which develops a series of safety performance functions and crash modification factors to predict the number of crashes. Crash severity outcomes are generally integrated into the Highway Safety Manual using deterministic distributions rather than statistical models. Accounting for the variability in crash severity as a function geometric design, traffic flow, and other roadway and roadside features is afforded by estimating statistical models. Therefore, there is a need to develop a new analysis paradigm to resolve the limitations in the current Highway Safety Manual methods. We propose an approach which decomposes the severe crash frequency into a function of the change in the total number of crashes and the probability of a crash becoming a severe crash before and after a countermeasure is implemented. We tested this approach by evaluating the effectiveness of shoulder rumble strips on reducing the number of severe crashes. A total of 310 segments that have had shoulder rumble strips installed during 2002-2009 are included in the analysis. It was found that shoulder rumble strips reduce the total number of crashes, but have no statistically significant effect on reducing the probability of a severe crash outcome. Copyright © 2014 Elsevier Ltd. All rights reserved.
Identifying crash-prone traffic conditions under different weather on freeways.
Xu, Chengcheng; Wang, Wei; Liu, Pan
2013-09-01
Understanding the relationships between traffic flow characteristics and crash risk under adverse weather conditions will help highway agencies develop proactive safety management strategies to improve traffic safety in adverse weather conditions. The primary objective is to develop separate crash risk prediction models for different weather conditions. The crash data, weather data, and traffic data used in this study were collected on the I-880N freeway in California in 2008 and 2010. This study considered three different weather conditions: clear weather, rainy weather, and reduced visibility weather. The preliminary analysis showed that there was some heterogeneity in the risk estimates for traffic flow characteristics by weather conditions, and that the crash risk prediction model for all weather conditions cannot capture the impacts of the traffic flow variables on crash risk under adverse weather conditions. The Bayesian random intercept logistic regression models were applied to link the likelihood of crash occurrence with various traffic flow characteristics under different weather conditions. The crash risk prediction models were compared to their corresponding logistic regression model. It was found that the random intercept model improved the goodness-of-fit of the crash risk prediction models. The model estimation results showed that the traffic flow characteristics contributing to crash risk were different across different weather conditions. The speed difference between upstream and downstream stations was found to be significant in each crash risk prediction model. Speed difference between upstream and downstream stations had the largest impact on crash risk in reduced visibility weather, followed by that in rainy weather. The ROC curves were further developed to evaluate the predictive performance of the crash risk prediction models under different weather conditions. The predictive performance of the crash risk model for clear weather was better than those of the crash risk models for adverse weather conditions. The research results could promote a better understanding of the impacts of traffic flow characteristics on crash risk under adverse weather conditions, which will help transportation professionals to develop better crash prevention strategies in adverse weather. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.
Effect of electronic stability control on automobile crash risk.
Farmer, Charles
2004-12-01
Per vehicle crash involvement rates were compared for otherwise identical vehicle models with and without electronic stability control (ESC) systems. ESC was found to affect single-vehicle crashes to a greater extent than multiple-vehicle crashes, and crashes with fatal injuries to a greater extent than less severe crashes. Based on all police-reported crashes in 7 states over 2 years, ESC reduced single-vehicle crash involvement risk by approximately 41 percent (95 percent confidence limits 3348) and single-vehicle injury crash involvement risk by 41 percent (2752). This translates to an estimated 7 percent reduction in overall crash involvement risk (310) and a 9 percent reduction in overall injury crash involvement risk (314). Based on all fatal crashes in the United States over 3 years, ESC was found to have reduced single-vehicle fatal crash involvement risk by 56 percent (3968). This translates to an estimated 34 percent reduction in overall fatal crash involvement risk (2145).
Chen, Cong; Zhang, Guohui; Huang, Helai; Wang, Jiangfeng; Tarefder, Rafiqul A
2016-11-01
Rural non-interstate crashes induce a significant amount of severe injuries and fatalities. Examination of such injury patterns and the associated contributing factors is of practical importance. Taking into account the ordinal nature of injury severity levels and the hierarchical feature of crash data, this study employs a hierarchical ordered logit model to examine the significant factors in predicting driver injury severities in rural non-interstate crashes based on two-year New Mexico crash records. Bayesian inference is utilized in model estimation procedure and 95% Bayesian Credible Interval (BCI) is applied to testing variable significance. An ordinary ordered logit model omitting the between-crash variance effect is evaluated as well for model performance comparison. Results indicate that the model employed in this study outperforms ordinary ordered logit model in model fit and parameter estimation. Variables regarding crash features, environment conditions, and driver and vehicle characteristics are found to have significant influence on the predictions of driver injury severities in rural non-interstate crashes. Factors such as road segments far from intersection, wet road surface condition, collision with animals, heavy vehicle drivers, male drivers and driver seatbelt used tend to induce less severe driver injury outcomes than the factors such as multiple-vehicle crashes, severe vehicle damage in a crash, motorcyclists, females, senior drivers, driver with alcohol or drug impairment, and other major collision types. Research limitations regarding crash data and model assumptions are also discussed. Overall, this research provides reasonable results and insight in developing effective road safety measures for crash injury severity reduction and prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.
Cai, Qing; Abdel-Aty, Mohamed; Lee, Jaeyoung
2017-10-01
This study aims at contributing to the literature on pedestrian and bicyclist safety by building on the conventional count regression models to explore exogenous factors affecting pedestrian and bicyclist crashes at the macroscopic level. In the traditional count models, effects of exogenous factors on non-motorist crashes were investigated directly. However, the vulnerable road users' crashes are collisions between vehicles and non-motorists. Thus, the exogenous factors can affect the non-motorist crashes through the non-motorists and vehicle drivers. To accommodate for the potentially different impact of exogenous factors we convert the non-motorist crash counts as the product of total crash counts and proportion of non-motorist crashes and formulate a joint model of the negative binomial (NB) model and the logit model to deal with the two parts, respectively. The formulated joint model is estimated using non-motorist crash data based on the Traffic Analysis Districts (TADs) in Florida. Meanwhile, the traditional NB model is also estimated and compared with the joint model. The result indicates that the joint model provides better data fit and can identify more significant variables. Subsequently, a novel joint screening method is suggested based on the proposed model to identify hot zones for non-motorist crashes. The hot zones of non-motorist crashes are identified and divided into three types: hot zones with more dangerous driving environment only, hot zones with more hazardous walking and cycling conditions only, and hot zones with both. It is expected that the joint model and screening method can help decision makers, transportation officials, and community planners to make more efficient treatments to proactively improve pedestrian and bicyclist safety. Published by Elsevier Ltd.
Hosseinpour, Mehdi; Sahebi, Sina; Zamzuri, Zamira Hasanah; Yahaya, Ahmad Shukri; Ismail, Noriszura
2018-06-01
According to crash configuration and pre-crash conditions, traffic crashes are classified into different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear-end, and angle crashes, are more frequent than single-vehicle crashes, and most often result in serious consequences. From a methodological point of view, the majority of prior studies focused on multivehicle collisions have employed univariate count models to estimate crash counts separately by collision type. However, univariate models fail to account for correlations which may exist between different collision types. Among others, multivariate Poisson lognormal (MVPLN) model with spatial correlation is a promising multivariate specification because it not only allows for unobserved heterogeneity (extra-Poisson variation) and dependencies between collision types, but also spatial correlation between adjacent sites. However, the MVPLN spatial model has rarely been applied in previous research for simultaneously modelling crash counts by collision type. Therefore, this study aims at utilizing a MVPLN spatial model to estimate crash counts for four different multi-vehicle collision types, including head-on, rear-end, angle, and sideswipe collisions. To investigate the performance of the MVPLN spatial model, a two-stage model and a univariate Poisson lognormal model (UNPLN) spatial model were also developed in this study. Detailed information on roadway characteristics, traffic volume, and crash history were collected on 407 homogeneous segments from Malaysian federal roads. The results indicate that the MVPLN spatial model outperforms the other comparing models in terms of goodness-of-fit measures. The results also show that the inclusion of spatial heterogeneity in the multivariate model significantly improves the model fit, as indicated by the Deviance Information Criterion (DIC). The correlation between crash types is high and positive, implying that the occurrence of a specific collision type is highly associated with the occurrence of other crash types on the same road segment. These results support the utilization of the MVPLN spatial model when predicting crash counts by collision manner. In terms of contributing factors, the results show that distinct crash types are attributed to different subsets of explanatory variables. Copyright © 2018 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhan, Xianyuan; Aziz, H. M. Abdul; Ukkusuri, Satish V.
Our study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly models crash frequency and severity accounting for correlations. The ordinary univariate count models analyze crashes of different severity level separately ignoring the correlations among severity levels. The MVPLN model is capable to incorporate the general correlation structure and takes account of the over dispersion in the data that leads to a superior data fitting. But, the traditional estimation approach for MVPLN model is computationally expensive, which often limits the use of MVPLN model in practice. In this work, a parallel sampling scheme is introduced to improve the original Markov Chainmore » Monte Carlo (MCMC) estimation approach of the MVPLN model, which significantly reduces the model estimation time. Two MVPLN models are developed using the pedestrian vehicle crash data collected in New York City from 2002 to 2006, and the highway-injury data from Washington State (5-year data from 1990 to 1994) The Deviance Information Criteria (DIC) is used to evaluate the model fitting. The estimation results show that the MVPLN models provide a superior fit over univariate Poisson-lognormal (PLN), univariate Poisson, and Negative Binomial models. Moreover, the correlations among the latent effects of different severity levels are found significant in both datasets that justifies the importance of jointly modeling crash frequency and severity accounting for correlations.« less
Zhan, Xianyuan; Aziz, H. M. Abdul; Ukkusuri, Satish V.
2015-11-19
Our study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly models crash frequency and severity accounting for correlations. The ordinary univariate count models analyze crashes of different severity level separately ignoring the correlations among severity levels. The MVPLN model is capable to incorporate the general correlation structure and takes account of the over dispersion in the data that leads to a superior data fitting. But, the traditional estimation approach for MVPLN model is computationally expensive, which often limits the use of MVPLN model in practice. In this work, a parallel sampling scheme is introduced to improve the original Markov Chainmore » Monte Carlo (MCMC) estimation approach of the MVPLN model, which significantly reduces the model estimation time. Two MVPLN models are developed using the pedestrian vehicle crash data collected in New York City from 2002 to 2006, and the highway-injury data from Washington State (5-year data from 1990 to 1994) The Deviance Information Criteria (DIC) is used to evaluate the model fitting. The estimation results show that the MVPLN models provide a superior fit over univariate Poisson-lognormal (PLN), univariate Poisson, and Negative Binomial models. Moreover, the correlations among the latent effects of different severity levels are found significant in both datasets that justifies the importance of jointly modeling crash frequency and severity accounting for correlations.« less
A TWO-STATE MIXED HIDDEN MARKOV MODEL FOR RISKY TEENAGE DRIVING BEHAVIOR
Jackson, John C.; Albert, Paul S.; Zhang, Zhiwei
2016-01-01
This paper proposes a joint model for longitudinal binary and count outcomes. We apply the model to a unique longitudinal study of teen driving where risky driving behavior and the occurrence of crashes or near crashes are measured prospectively over the first 18 months of licensure. Of scientific interest is relating the two processes and predicting crash and near crash outcomes. We propose a two-state mixed hidden Markov model whereby the hidden state characterizes the mean for the joint longitudinal crash/near crash outcomes and elevated g-force events which are a proxy for risky driving. Heterogeneity is introduced in both the conditional model for the count outcomes and the hidden process using a shared random effect. An estimation procedure is presented using the forward–backward algorithm along with adaptive Gaussian quadrature to perform numerical integration. The estimation procedure readily yields hidden state probabilities as well as providing for a broad class of predictors. PMID:27766124
DOT National Transportation Integrated Search
2011-08-01
The Backing crash Countermeasures project, part of the U.S. Department of Transportation's Advanced Crash Avoidance Technologies (ACAT) program, developed a basic methodological framework and computerbased simulation model to estimate the effectiv...
Comparison of four statistical and machine learning methods for crash severity prediction.
Iranitalab, Amirfarrokh; Khattak, Aemal
2017-11-01
Crash severity prediction models enable different agencies to predict the severity of a reported crash with unknown severity or the severity of crashes that may be expected to occur sometime in the future. This paper had three main objectives: comparison of the performance of four statistical and machine learning methods including Multinomial Logit (MNL), Nearest Neighbor Classification (NNC), Support Vector Machines (SVM) and Random Forests (RF), in predicting traffic crash severity; developing a crash costs-based approach for comparison of crash severity prediction methods; and investigating the effects of data clustering methods comprising K-means Clustering (KC) and Latent Class Clustering (LCC), on the performance of crash severity prediction models. The 2012-2015 reported crash data from Nebraska, United States was obtained and two-vehicle crashes were extracted as the analysis data. The dataset was split into training/estimation (2012-2014) and validation (2015) subsets. The four prediction methods were trained/estimated using the training/estimation dataset and the correct prediction rates for each crash severity level, overall correct prediction rate and a proposed crash costs-based accuracy measure were obtained for the validation dataset. The correct prediction rates and the proposed approach showed NNC had the best prediction performance in overall and in more severe crashes. RF and SVM had the next two sufficient performances and MNL was the weakest method. Data clustering did not affect the prediction results of SVM, but KC improved the prediction performance of MNL, NNC and RF, while LCC caused improvement in MNL and RF but weakened the performance of NNC. Overall correct prediction rate had almost the exact opposite results compared to the proposed approach, showing that neglecting the crash costs can lead to misjudgment in choosing the right prediction method. Copyright © 2017 Elsevier Ltd. All rights reserved.
Effect of horizontal curves on urban arterial crashes.
Banihashemi, Mohamadreza
2016-10-01
The crash prediction models of the Highway Safety Manual (HSM), 2010 estimate the expected number of crashes for different facility types. Models in Part C Chapter 12 of the first edition of the HSM include crash prediction models for divided and undivided urban arterials. Each of the HSM crash prediction models for highway segments is comprised of a "Safety Performance Function," a function of AADT and segment length, plus, a series of "Crash Modification Factors" (CMFs). The SPF estimates the expected number of crashes for the site if the site features are of base condition. The effects of the other features of the site, if their values are different from base condition, are carried out through use of CMFs. The existing models for urban arterials do not have any CMF for horizontal curvature. The goal of this research is to investigate if the horizontal alignment has any significant effect on crashes on any of these types of facilities and if so, to develop a CMF for this feature. Washington State cross sectional data from the Highway Safety Information System (HSIS), 2014 was used in this research. Data from 2007 to 2009 was used to conduct the investigation. The 2010 data was used to validate the results. As the results showed, the horizontal curvature has significant safety effect on two-lane undivided urban arterials with speed limits of 35 mph and higher and using a CMF for horizontal curvature in the crash prediction model of this type of facility improves the prediction of crashes significantly, for both tangent and curve segments. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modeling left-turn crash occurrence at signalized intersections by conflicting patterns.
Wang, Xuesong; Abdel-Aty, Mohamed
2008-01-01
In order to better understand the underlying crash mechanisms, left-turn crashes occurring at 197 four-legged signalized intersections over 6 years were classified into nine patterns based on vehicle maneuvers and then were assigned to intersection approaches. Crash frequency of each pattern was modeled at the approach level by mainly using Generalized Estimating Equations (GEE) with the Negative Binomial as the link function to account for the correlation among the crash data. GEE with a binomial logit link function was also applied for patterns with fewer crashes. The Cumulative Residuals test shows that, for correlated left-turn crashes, GEE models usually outperformed basic Negative Binomial models. The estimation results show that there are obvious differences in the factors that cause the occurrence of different left-turn collision patterns. For example, for each pattern, the traffic flows to which the colliding vehicles belong are identified to be significant. The width of the crossing distance (represented by the number of through lanes on the opposing approach of the left-turning traffic) is associated with more left-turn traffic colliding with opposing through traffic (Pattern 5), but with less left-turning traffic colliding with near-side crossing through traffic (Pattern 8). The safety effectiveness of the left-turning signal is not consistent for different crash patterns; "protected" phasing is correlated with fewer Pattern 5 crashes, but with more Pattern 8 crashes. The study indicates that in order to develop efficient countermeasures for left-turn crashes and improve safety at signalized intersections, left-turn crashes should be considered in different patterns.
DOT National Transportation Integrated Search
2016-10-01
The development of safety performance functions (SPFs) and crash modification factors (CMFs) requires data on traffic exposure. The analysis of motorcycle crashes can be especially challenging in this regard because few jurisdictions collect motorcyc...
Chen, Feng; Chen, Suren; Ma, Xiaoxiang
2018-06-01
Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.
Park, Byung-Jung; Lord, Dominique; Wu, Lingtao
2016-10-28
This study aimed to investigate the relative performance of two models (negative binomial (NB) model and two-component finite mixture of negative binomial models (FMNB-2)) in terms of developing crash modification factors (CMFs). Crash data on rural multilane divided highways in California and Texas were modeled with the two models, and crash modification functions (CMFunctions) were derived. The resultant CMFunction estimated from the FMNB-2 model showed several good properties over that from the NB model. First, the safety effect of a covariate was better reflected by the CMFunction developed using the FMNB-2 model, since the model takes into account the differential responsiveness of crash frequency to the covariate. Second, the CMFunction derived from the FMNB-2 model is able to capture nonlinear relationships between covariate and safety. Finally, following the same concept as those for NB models, the combined CMFs of multiple treatments were estimated using the FMNB-2 model. The results indicated that they are not the simple multiplicative of single ones (i.e., their safety effects are not independent under FMNB-2 models). Adjustment Factors (AFs) were then developed. It is revealed that current Highway Safety Manual's method could over- or under-estimate the combined CMFs under particular combination of covariates. Safety analysts are encouraged to consider using the FMNB-2 models for developing CMFs and AFs. Copyright © 2016 Elsevier Ltd. All rights reserved.
Intersection crash prediction modeling with macro-level data from various geographic units.
Lee, Jaeyoung; Abdel-Aty, Mohamed; Cai, Qing
2017-05-01
There have been great efforts to develop traffic crash prediction models for various types of facilities. The crash models have played a key role to identify crash hotspots and evaluate safety countermeasures. In recent, many macro-level crash prediction models have been developed to incorporate highway safety considerations in the long-term transportation planning process. Although the numerous macro-level studies have found that a variety of demographic and socioeconomic zonal characteristics have substantial effects on traffic safety, few studies have attempted to coalesce micro-level with macro-level data from existing geographic units for estimating crash models. In this study, the authors have developed a series of intersection crash models for total, severe, pedestrian, and bicycle crashes with macro-level data for seven spatial units. The study revealed that the total, severe, and bicycle crash models with ZIP-code tabulation area data performs the best, and the pedestrian crash models with census tract-based data outperforms the competing models. Furthermore, it was uncovered that intersection crash models can be drastically improved by only including random-effects for macro-level entities. Besides, the intersection crash models are even further enhanced by including other macro-level variables. Lastly, the pedestrian and bicycle crash modeling results imply that several macro-level variables (e.g., population density, proportions of specific age group, commuters who walk, or commuters using bicycle, etc.) can be a good surrogate exposure for those crashes. Copyright © 2017 Elsevier Ltd. All rights reserved.
Analysis of design attributes and crashes on the Oregon highway system : final report.
DOT National Transportation Integrated Search
2001-08-01
This report has investigated the statistical relationship between crash activity and roadway design attributes on the Oregon state : highway system. Crash models were estimated from highway segments distinguished by functional classification (freeway...
Wang, Ling; Abdel-Aty, Mohamed; Wang, Xuesong; Yu, Rongjie
2018-02-01
There have been plenty of traffic safety studies based on average daily traffic (ADT), average hourly traffic (AHT), or microscopic traffic at 5 min intervals. Nevertheless, not enough research has compared the performance of these three types of safety studies, and seldom of previous studies have intended to find whether the results of one type of study is transferable to the other two studies. First, this study built three models: a Bayesian Poisson-lognormal model to estimate the daily crash frequency using ADT, a Bayesian Poisson-lognormal model to estimate the hourly crash frequency using AHT, and a Bayesian logistic regression model for the real-time safety analysis using microscopic traffic. The model results showed that the crash contributing factors found by different models were comparable but not the same. Four variables, i.e., the logarithm of volume, the standard deviation of speed, the logarithm of segment length, and the existence of diverge segment, were positively significant in the three models. Additionally, weaving segments experienced higher daily and hourly crash frequencies than merge and basic segments. Then, each of the ADT-based, AHT-based, and real-time models was used to estimate safety conditions at different levels: daily and hourly, meanwhile, the real-time model was also used in 5 min intervals. The results uncovered that the ADT- and AHT-based safety models performed similar in predicting daily and hourly crash frequencies, and the real-time safety model was able to provide hourly crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.
Integrated traffic conflict model for estimating crash modification factors.
Shahdah, Usama; Saccomanno, Frank; Persaud, Bhagwant
2014-10-01
Crash modification factors (CMFs) for road safety treatments are usually obtained through observational models based on reported crashes. Observational Bayesian before-and-after methods have been applied to obtain more precise estimates of CMFs by accounting for the regression-to-the-mean bias inherent in naive methods. However, sufficient crash data reported over an extended period of time are needed to provide reliable estimates of treatment effects, a requirement that can be a challenge for certain types of treatment. In addition, these studies require that sites analyzed actually receive the treatment to which the CMF pertains. Another key issue with observational approaches is that they are not causal in nature, and as such, cannot provide a sound "behavioral" rationale for the treatment effect. Surrogate safety measures based on high risk vehicle interactions and traffic conflicts have been proposed to address this issue by providing a more "causal perspective" on lack of safety for different road and traffic conditions. The traffic conflict approach has been criticized, however, for lacking a formal link to observed and verified crashes, a difficulty that this paper attempts to resolve by presenting and investigating an alternative approach for estimating CMFs using simulated conflicts that are linked formally to observed crashes. The integrated CMF estimates are compared to estimates from an empirical Bayes (EB) crash-based before-and-after analysis for the same sample of treatment sites. The treatment considered involves changing left turn signal priority at Toronto signalized intersections from permissive to protected-permissive. The results are promising in that the proposed integrated method yields CMFs that closely match those obtained from the crash-based EB before-and-after analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.
Li, Lu; Persaud, Bhagwant; Shalaby, Amer
2017-03-01
This study investigates the use of crash prediction models and micro-simulation to develop an effective surrogate safety assessment measure at the intersection level. With the use of these tools, hypothetical scenarios can be developed and explored to evaluate the safety impacts of design alternatives in a controlled environment, in which factors not directly associated with the design alternatives can be fixed. Micro-simulation models are developed, calibrated, and validated. Traffic conflicts in the micro-simulation models are estimated and linked with observed crash frequency, which greatly alleviates the lengthy time needed to collect sufficient crash data for evaluating alternatives, due to the rare and infrequent nature of crash events. A set of generalized linear models with negative binomial error structure is developed to correlate the simulated conflicts with the observed crash frequency in Toronto, Ontario, Canada. Crash prediction models are also developed for crashes of different impact types and for transit-involved crashes. The resulting statistical significance and the goodness-of-fit of the models suggest adequate predictive ability. Based on the established correlation between simulated conflicts and observed crashes, scenarios are developed in the micro-simulation models to investigate the safety effects of individual transit line elements by making hypothetical modifications to such elements and estimating changes in crash frequency from the resulting changes in conflicts. The findings imply that the existing transit signal priority schemes can have a negative effect on safety performance, and that the existing near-side stop positioning and streetcar transit type can be safer at their current state than if they were to be replaced by their respective counterparts. Copyright © 2017 Elsevier Ltd. All rights reserved.
Contributing factors to vehicle to vehicle crash frequency and severity under rainfall.
Jung, Soyoung; Jang, Kitae; Yoon, Yoonjin; Kang, Sanghyeok
2014-09-01
This study combined vehicle to vehicle crash frequency and severity estimations to examine factor impacts on Wisconsin highway safety in rainy weather. Because of data deficiency, the real-time water film depth, the car-following distance, and the vertical curve grade were estimated with available data sources and a GIS analysis to capture rainy weather conditions at the crash location and time. Using a negative binomial regression for crash frequency estimation, the average annual daily traffic per lane, the interaction between the posted speed limit change and the existence of an off-ramp, and the interaction between the travel lane number change and the pavement surface material change were found to increase the likelihood of vehicle to vehicle crashes under rainfall. However, more average daily rainfall per month and a wider left shoulder were identified as factors that decrease the likelihood of vehicle to vehicle crashes. In the crash severity estimation using the multinomial logit model that outperformed the ordered logit model, the travel lane number, the interaction between the travel lane number and the slow grade, the deep water film, and the rear-end collision type were more likely to increase the likelihood of injury crashes under rainfall compared with crashes involving only property damage. As an exploratory data analysis, this study provides insight into potential strategies for rainy weather highway safety improvement, specifically, the following weather-sensitive strategies: road design and ITS implementation for drivers' safety awareness under rainfall. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.
Cost of Crashes Related to Road Conditions, United States, 2006
Zaloshnja, Eduard; Miller, Ted R.
2009-01-01
This is the first study to estimate the cost of crashes related to road conditions in the U.S. To model the probability that road conditions contributed to the involvement of a vehicle in the crash, we used 2000–03 Large Truck Crash Causation Study (LTCCS) data, the only dataset that provides detailed information whether road conditions contributed to crash occurrence. We applied the logistic regression results to a costed national crash dataset in order to calculate the probability that road conditions contributed to the involvement of a vehicle in each crash. In crashes where someone was moderately to seriously injured (AIS-2-6) in a vehicle that harmfully impacted a large tree or medium or large non-breakaway pole, or if the first harmful event was collision with a bridge, we changed the calculated probability of being road-related to 1. We used the state distribution of costs of fatal crashes where road conditions contributed to crash occurrence or severity to estimate the respective state distribution of non-fatal crash costs. The estimated comprehensive cost of traffic crashes where road conditions contributed to crash occurrence or severity was $217.5 billion in 2006. This represented 43.6% of the total comprehensive crash cost. The large share of crash costs related to road design and conditions underlines the importance of these factors in highway safety. Road conditions are largely controllable. Road maintenance and upgrading can prevent crashes and reduce injury severity. PMID:20184840
Transferability and robustness of real-time freeway crash risk assessment.
Shew, Cameron; Pande, Anurag; Nuworsoo, Cornelius
2013-09-01
This study examines the data from single loop detectors on northbound (NB) US-101 in San Jose, California to estimate real-time crash risk assessment models. The classification tree and neural network based crash risk assessment models developed with data from NB US-101 are applied to data from the same freeway, as well as to the data from nearby segments of the SB US-101, NB I-880, and SB I-880 corridors. The performance of crash risk assessment models on these nearby segments is the focus of this research. The model applications show that it is in fact possible to use the same model for multiple freeways, as the underlying relationships between traffic data and crash risk remain similar. The framework provided here may be helpful to authorities for freeway segments with newly installed traffic surveillance apparatuses, since the real-time crash risk assessment models from nearby freeways with existing infrastructure would be able to provide a reasonable estimate of crash risk. The robustness of the model output is also assessed by location, time of day, and day of week. The analysis shows that on some locations the models may require further learning due to higher than expected false positive (e.g., the I-680/I-280 interchange on US-101 NB) or false negative rates. The approach for post-processing the results from the model provides ideas to refine the model prior to or during the implementation. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.
Liu, Jun; Khattak, Asad J; Richards, Stephen H; Nambisan, Shashi
2015-12-01
Crashes at highway-rail grade crossings can result in severe injuries and fatalities to vehicle occupants. Using a crash database from the Federal Railroad Administration (N=15,639 for 2004-2013), this study explores differences in safety outcomes from crashes between passive controls (Crossbucks and STOP signs) and active controls (flashing lights, gates, audible warnings and highway signals). To address missing data, an imputation model is developed, creating a complete dataset for estimation. Path analysis is used to quantify the direct and indirect associations of passive and active controls with pre-crash behaviors and crash outcomes in terms of injury severity. The framework untangles direct and indirect associations of controls by estimating two models, one for pre-crash driving behaviors (e.g., driving around active controls), and another model for injury severity. The results show that while the presence of gates is not directly associated with injury severity, the indirect effect through stopping behavior is statistically significant (95% confidence level) and substantial. Drivers are more likely to stop at gates that also have flashing lights and audible warnings, and stopping at gates is associated with lower injury severity. This indirect association lowers the chances of injury by 16%, compared with crashes at crossings without gates. Similar relationships between other controls and injury severity are explored. Generally, crashes occurring at active controls are less severe than crashes at passive controls. The results of study can be used to modify Crash Modification Factors (CMFs) to account for crash injury severity. The study contributes to enhancing the understanding of safety by incorporating pre-crash behaviors in a broader framework that quantifies correlates of crash injury severity at active and passive crossings. Copyright © 2015 Elsevier Ltd. All rights reserved.
Zhao, Peibo; Lee, Chris
2018-04-01
This study analyzes rear-end collision risk of cars and heavy vehicles on freeways using a surrogate safety measure. The crash potential index (CPI) was modified to reflect driver's reaction time and estimated by types of lead and following vehicles (car or heavy vehicle). CPIs were estimated using the individual vehicle trajectory data from a segment of the US-101 freeway in Los Angeles, U.S.A. It was found that the CPI was generally higher for the following heavy vehicle than the following car due to heavy vehicle's lower braking capability. This study also validates the CPI using the simulated traffic data which replicate the observed traffic conditions a few minutes before the crash time upstream and downstream of the crash locations. The observed data were obtained from crash records and loop detectors on a section of the Gardiner Expressway in Toronto, Canada. The result shows that the values of CPI were consistently higher during the traffic conditions immediately before the crash time (crash case) than the normal traffic conditions (non-crash case). This demonstrates that the CPI can be used to capture rear-end collision risk during car-following maneuver on freeways. The result also shows that rear-end collision risk is lower for heavy vehicles than cars in the crash case due to their shorter reaction time and lower speed when spacing is shorter. Thus, it is important to reflect the differences in driver behavior and vehicle performance characteristics between cars and heavy vehicles in estimating surrogate safety measures. Lastly, it was found that the CPI-based crash prediction model can correctly identify the crash and non-crash cases at higher accuracy than the other crash prediction models based on detectors. Copyright © 2018 Elsevier Ltd. All rights reserved.
Haleem, Kirolos; Gan, Albert
2013-09-01
This study identifies geometric, traffic, environmental, vehicle-related, and driver-related predictors of crash injury severity on urban freeways. The study takes advantage of the mixed logit model's ability to account for unobserved effects that are difficult to quantify and may affect the model estimation, such as the driver's reaction at the time of crash. Crashes of 5 years occurring on 89 urban freeway segments throughout the state of Florida in the United States were used. Examples of severity predictors explored include traffic volume, distance of the crash to the nearest ramp, and detailed driver's age, vehicle types, and sides of impact. To show how the parameter estimates could vary, a binary logit model was compared with the mixed logit model. It was found that the at-fault driver's age, traffic volume, distance of the crash to the nearest ramp, vehicle type, side of impact, and percentage of trucks significantly influence severity on urban freeways. Additionally, young at-fault drivers were associated with a significant severity risk increase relative to other age groups. It was also observed that some variables in the binary logit model yielded illogic estimates due to ignoring the random variation of the estimation. Since the at-fault driver's age and side of impact were significant random parameters in the mixed logit model, an in-depth investigation was performed. It was noticed that back, left, and right impacts had the highest risk among middle-aged drivers, followed by young drivers, very young drivers, and finally, old and very old drivers. To reduce side impacts due to lane changing, two primary strategies can be recommended. The first strategy is to conduct campaigns to convey the hazardous effect of changing lanes at higher speeds. The second is to devise in-vehicle side crash avoidance systems to alert drivers of a potential crash risk. The study provided a promising approach to screening the predictors before fitting the mixed logit model using the random forest technique. Furthermore, potential countermeasures were proposed to reduce the severity of impacts. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.
Crash sequence based risk matrix for motorcycle crashes.
Wu, Kun-Feng; Sasidharan, Lekshmi; Thor, Craig P; Chen, Sheng-Yin
2018-04-05
Considerable research has been conducted related to motorcycle and other powered-two-wheeler (PTW) crashes; however, it always has been controversial among practitioners concerning with types of crashes should be first targeted and how to prioritize resources for the implementation of mitigating actions. Therefore, there is a need to identify types of motorcycle crashes that constitute the greatest safety risk to riders - most frequent and most severe crashes. This pilot study seeks exhibit the efficacy of a new approach for prioritizing PTW crash causation sequences as they relate to injury severity to better inform the application of mitigating countermeasures. To accomplish this, the present study constructed a crash sequence-based risk matrix to identify most frequent and most severe motorcycle crashes in an attempt to better connect causes and countermeasures of PTW crashes. Although the frequency of each crash sequence can be computed from crash data, a crash severity model is needed to compare the levels of crash severity among different crash sequences, while controlling for other factors that also have effects on crash severity such drivers' age, use of helmet, etc. The construction of risk matrix based on crash sequences involve two tasks: formulation of crash sequence and the estimation of a mixed-effects (ME) model to adjust the levels of severities for each crash sequence to account for other crash contributing factors that would have an effect on the maximum level of crash severity in a crash. Three data elements from the National Automotive Sampling System - General Estimating System (NASS-GES) data were utilized to form a crash sequence: critical event, crash types, and sequence of events. A mixed-effects model was constructed to model the severity levels for each crash sequence while accounting for the effects of those crash contributing factors on crash severity. A total of 8039 crashes involving 8208 motorcycles occurred during 2011 and 2013 were included in this study, weighted to represent 338,655 motorcyclists involved in traffic crashes in three years (2011-2013)(NHTSA, 2013). The top five most frequent and severe types of crash sequences were identified, accounting for 23 percent of all the motorcycle crashes included in the study, and they are (1) run-off-road crashes on the right, and hitting roadside objects, (2) cross-median crashes, and rollover, (3) left-turn oncoming crashes, and head-on, (4) crossing over (passing through) or turning into opposite direction at intersections, and (5) side-impacted. In addition to crash sequences, several other factors were also identified to have effects on crash severity: use of helmet, presence of horizontal curves, alcohol consumption, road surface condition, roadway functional class, and nighttime condition. Copyright © 2018 Elsevier Ltd. All rights reserved.
The mean time-limited crash rate of stock price
NASA Astrophysics Data System (ADS)
Li, Yun-Xian; Li, Jiang-Cheng; Yang, Ai-Jun; Tang, Nian-Sheng
2017-05-01
In this article we investigate the occurrence of stock market crash in an economy cycle. Bayesian approach, Heston model and statistical-physical method are considered. Specifically, Heston model and an effective potential are employed to address the dynamic changes of stock price. Bayesian approach has been utilized to estimate the Heston model's unknown parameters. Statistical physical method is used to investigate the occurrence of stock market crash by calculating the mean time-limited crash rate. The real financial data from the Shanghai Composite Index is analyzed with the proposed methods. The mean time-limited crash rate of stock price is used to describe the occurrence of stock market crash in an economy cycle. The monotonous and nonmonotonous behaviors are observed in the behavior of the mean time-limited crash rate versus volatility of stock for various cross correlation coefficient between volatility and price. Also a minimum occurrence of stock market crash matching an optimal volatility is discovered.
Crash data modeling with a generalized estimator.
Ye, Zhirui; Xu, Yueru; Lord, Dominique
2018-08-01
The investigation of relationships between traffic crashes and relevant factors is important in traffic safety management. Various methods have been developed for modeling crash data. In real world scenarios, crash data often display the characteristics of over-dispersion. However, on occasions, some crash datasets have exhibited under-dispersion, especially in cases where the data are conditioned upon the mean. The commonly used models (such as the Poisson and the NB regression models) have associated limitations to cope with various degrees of dispersion. In light of this, a generalized event count (GEC) model, which can be generally used to handle over-, equi-, and under-dispersed data, is proposed in this study. This model was first applied to case studies using data from Toronto, characterized by over-dispersion, and then to crash data from railway-highway crossings in Korea, characterized with under-dispersion. The results from the GEC model were compared with those from the Negative binomial and the hyper-Poisson models. The cases studies show that the proposed model provides good performance for crash data characterized with over- and under-dispersion. Moreover, the proposed model simplifies the modeling process and the prediction of crash data. Copyright © 2018 Elsevier Ltd. All rights reserved.
Fink, Joshua; Kwigizile, Valerian; Oh, Jun-Seok
2016-06-01
Despite seeing widespread usage worldwide, adaptive traffic control systems have experienced relatively little use in the United States. Of the systems used, the Sydney Coordinated Adaptive Traffic System (SCATS) is the most popular in America. Safety benefits of these systems are not as well understood nor as commonly documented. This study investigates the safety benefits of adaptive traffic control systems by using the large SCATS-based system in Oakland County, MI known as FAST-TRAC. This study uses data from FAST-TRAC-controlled intersections in Oakland County and compares a wide variety of geometric, traffic, and crash characteristics to similar intersections in metropolitan areas elsewhere in Michigan. Data from 498 signalized intersections are used to conduct a cross-sectional analysis. Negative binomial models are used to estimate models for three dependent crash variables. Multinomial logit models are used to estimate an injury severity model. A variable tracking the presence of FAST-TRAC controllers at intersections is used in all models to determine if a SCATS-based system has an impact on crash occurrences or crash severity. Estimates show that the presence of SCATS-based controllers at intersections is likely to reduce angle crashes by up to 19.3%. Severity results show a statistically significant increase in non-serious injuries, but not a significant reduction in incapacitating injuries or fatal accidents. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.
Meta-analysis of the effect of road work zones on crash occurrence.
Theofilatos, Athanasios; Ziakopoulos, Apostolos; Papadimitriou, Eleonora; Yannis, George; Diamandouros, Konstantinos
2017-11-01
There is strong evidence that work zones pose increased risk of crashes and injuries. The two most common risk factors associated with increased crash frequencies are work zone duration and length. However, relevant research on the topic is relatively limited. For that reason, this paper presents formal meta-analyses of studies that have estimated the relationship between the number of crashes and work zone duration and length, in order to provide overall estimates of those effects on crash frequencies. All studies presented in this paper are crash prediction models with similar specifications. According to the meta-analyses and after correcting for publication bias when it was considered appropriate, the summary estimates of regression coefficients were found to be 0.1703 for duration and 0.862 for length. These effects were significant for length but not for duration. However, the overall estimate of duration was significant before correcting for publication bias. Separate meta-analyses on the studies examining both duration and length was also carried out in order to have rough estimates of the combined effects. The estimate of duration was found to be 0.953, while for length was 0.847. Similar to previous meta-analyses the effect of duration after correcting for publication bias is not significant, while the effect of length was significant at a 95% level. Meta-regression findings indicate that the main factors influencing the overall estimates of the beta coefficients are study year and region for duration and study year and model specification for length. Copyright © 2017 Elsevier Ltd. All rights reserved.
Automobile driver fatalities in frontal impacts: air bags compared with manual belts.
Zador, P L; Ciccone, M A
1993-01-01
OBJECTIVES. The effectiveness of air bags was estimated in this study by comparing driver fatalities in frontal crashes with driver fatalities in nonfrontal crashes, for cars with air bags and manual belts and cars with manual belts only. METHODS. Fatal Accident Reporting System data for drivers fatally injured during 1985 to 1991 in 1985 to 1991 model year cars that were equipped with air bags in or before model year 1991 were analyzed. RESULTS. Driver fatalities in frontal crashes in air bag cars were 28% lower than those in comparable cars with manual belts only. This percentage was used for estimating the overall fatality reduction in air bag cars. The reduction was greater in large cars (50%) than in midsize cars (19%) or in small cars (14%). Air bags reduced driver fatalities in frontal crashes involving ejection by about 9%. Fatalities in frontal crashes among drivers who were reportedly using manual belts at the time of the crash were reduced by about 15%. The comparable reduction among drivers who were reportedly not using manual belts was 31%. CONCLUSION. It was estimated that air bags reduced the total number of all driver fatalities by about 19%. PMID:8484445
Chen, Feng; Chen, Suren; Ma, Xiaoxiang
2016-01-01
Traffic and environmental conditions (e.g., weather conditions), which frequently change with time, have a significant impact on crash occurrence. Traditional crash frequency models with large temporal scales and aggregated variables are not sufficient to capture the time-varying nature of driving environmental factors, causing significant loss of critical information on crash frequency modeling. This paper aims at developing crash frequency models with refined temporal scales for complex driving environments, with such an effort providing more detailed and accurate crash risk information which can allow for more effective and proactive traffic management and law enforcement intervention. Zero-inflated, negative binomial (ZINB) models with site-specific random effects are developed with unbalanced panel data to analyze hourly crash frequency on highway segments. The real-time driving environment information, including traffic, weather and road surface condition data, sourced primarily from the Road Weather Information System, is incorporated into the models along with site-specific road characteristics. The estimation results of unbalanced panel data ZINB models suggest there are a number of factors influencing crash frequency, including time-varying factors (e.g., visibility and hourly traffic volume) and site-varying factors (e.g., speed limit). The study confirms the unique significance of the real-time weather, road surface condition and traffic data to crash frequency modeling. PMID:27322306
Comparing motor-vehicle crash risk of EU and US vehicles.
Flannagan, Carol A C; Bálint, András; Klinich, Kathleen D; Sander, Ulrich; Manary, Miriam A; Cuny, Sophie; McCarthy, Michael; Phan, Vuthy; Wallbank, Caroline; Green, Paul E; Sui, Bo; Forsman, Åsa; Fagerlind, Helen
2018-08-01
This study examined the hypotheses that passenger vehicles meeting European Union (EU) safety standards have similar crashworthiness to United States (US) -regulated vehicles in the US driving environment, and vice versa. The first step involved identifying appropriate databases of US and EU crashes that include in-depth crash information, such as estimation of crash severity using Delta-V and injury outcome based on medical records. The next step was to harmonize variable definitions and sampling criteria so that the EU data could be combined and compared to the US data using the same or equivalent parameters. Logistic regression models of the risk of a Maximum injury according to the Abbreviated Injury Scale of 3 or greater, or fatality (MAIS3+F) in EU-regulated and US-regulated vehicles were constructed. The injury risk predictions of the EU model and the US model were each applied to both the US and EU standard crash populations. Frontal, near-side, and far-side crashes were analyzed together (termed "front/side crashes") and a separate model was developed for rollover crashes. For the front/side model applied to the US standard population, the mean estimated risk for the US-vehicle model is 0.035 (sd = 0.012), and the mean estimated risk for the EU-vehicle model is 0.023 (sd = 0.016). When applied to the EU front/side population, the US model predicted a 0.065 risk (sd = 0.027), and the EU model predicted a 0.052 risk (sd = 0.025). For the rollover model applied to the US standard population, the US model predicted a risk of 0.071 (sd = 0.024), and the EU model predicted 0.128 risk (sd = 0.057). When applied to the EU rollover standard population, the US model predicted a 0.067 risk (sd = 0.024), and the EU model predicted 0.103 risk (sd = 0.040). The results based on these methods indicate that EU vehicles most likely have a lower risk of MAIS3+F injury in front/side impacts, while US vehicles most likely have a lower risk of MAIS3+F injury in llroovers. These results should be interpreted with an understanding of the uncertainty of the estimates, the study limitations, and our recommendations for further study detailed in the report. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
Estimating safety effects of pavement management factors utilizing Bayesian random effect models.
Jiang, Ximiao; Huang, Baoshan; Zaretzki, Russell L; Richards, Stephen; Yan, Xuedong
2013-01-01
Previous studies of pavement management factors that relate to the occurrence of traffic-related crashes are rare. Traditional research has mostly employed summary statistics of bidirectional pavement quality measurements in extended longitudinal road segments over a long time period, which may cause a loss of important information and result in biased parameter estimates. The research presented in this article focuses on crash risk of roadways with overall fair to good pavement quality. Real-time and location-specific data were employed to estimate the effects of pavement management factors on the occurrence of crashes. This research is based on the crash data and corresponding pavement quality data for the Tennessee state route highways from 2004 to 2009. The potential temporal and spatial correlations among observations caused by unobserved factors were considered. Overall 6 models were built accounting for no correlation, temporal correlation only, and both the temporal and spatial correlations. These models included Poisson, negative binomial (NB), one random effect Poisson and negative binomial (OREP, ORENB), and two random effect Poisson and negative binomial (TREP, TRENB) models. The Bayesian method was employed to construct these models. The inference is based on the posterior distribution from the Markov chain Monte Carlo (MCMC) simulation. These models were compared using the deviance information criterion. Analysis of the posterior distribution of parameter coefficients indicates that the pavement management factors indexed by Present Serviceability Index (PSI) and Pavement Distress Index (PDI) had significant impacts on the occurrence of crashes, whereas the variable rutting depth was not significant. Among other factors, lane width, median width, type of terrain, and posted speed limit were significant in affecting crash frequency. The findings of this study indicate that a reduction in pavement roughness would reduce the likelihood of traffic-related crashes. Hence, maintaining a low level of pavement roughness is strongly suggested. In addition, the results suggested that the temporal correlation among observations was significant and that the ORENB model outperformed all other models.
Janstrup, Kira H; Kaplan, Sigal; Hels, Tove; Lauritsen, Jens; Prato, Carlo G
2016-08-17
This study aligns to the body of research dedicated to estimating the underreporting of road crash injuries and adds the perspective of understanding individual and crash factors contributing to the decision to report a crash to the police, the hospital, or both. This study focuses on road crash injuries that occurred in the province of Funen, Denmark, between 2003 and 2007 and were registered in the police, the hospital, or both authorities. Underreporting rates are computed with the capture-recapture method, and the probability for road crash injuries in police records to appear in hospital records (and vice versa) is estimated with joint binary logit models. The capture-recapture analysis shows high underreporting rates of road crash injuries in Denmark and the growth of underreporting not only with the decrease in injury severity but also with the involvement of cyclists (reporting rates of about 14% for serious injuries and 7% for slight injuries) and motorcyclists (reporting rates of about 35% for serious injuries and 10% for slight injuries). Model estimates show that the likelihood of appearing in both data sets is positively related to helmet and seat belt use, number of motor vehicles involved, alcohol involvement, higher speed limit, and females being injured. This study adds significantly to the literature about underreporting by recognizing that understanding the heterogeneity in the reporting rate of road crashes may lead to devising policy measures aimed at increasing the reporting rate by targeting specific road user groups (e.g., males, young road users) or specific situational factors (e.g., slight injuries, arm injuries, leg injuries, weekend).
Sasidharan, Lekshmi; Donnell, Eric T
2014-10-01
Accurate estimation of the expected number of crashes at different severity levels for entities with and without countermeasures plays a vital role in selecting countermeasures in the framework of the safety management process. The current practice is to use the American Association of State Highway and Transportation Officials' Highway Safety Manual crash prediction algorithms, which combine safety performance functions and crash modification factors, to estimate the effects of safety countermeasures on different highway and street facility types. Many of these crash prediction algorithms are based solely on crash frequency, or assume that severity outcomes are unchanged when planning for, or implementing, safety countermeasures. Failing to account for the uncertainty associated with crash severity outcomes, and assuming crash severity distributions remain unchanged in safety performance evaluations, limits the utility of the Highway Safety Manual crash prediction algorithms in assessing the effect of safety countermeasures on crash severity. This study demonstrates the application of a propensity scores-potential outcomes framework to estimate the probability distribution for the occurrence of different crash severity levels by accounting for the uncertainties associated with them. The probability of fatal and severe injury crash occurrence at lighted and unlighted intersections is estimated in this paper using data from Minnesota. The results show that the expected probability of occurrence of fatal and severe injury crashes at a lighted intersection was 1 in 35 crashes and the estimated risk ratio indicates that the respective probabilities at an unlighted intersection was 1.14 times higher compared to lighted intersections. The results from the potential outcomes-propensity scores framework are compared to results obtained from traditional binary logit models, without application of propensity scores matching. Traditional binary logit analysis suggests that the probability of occurrence of severe injury crashes is higher at lighted intersections compared to unlighted intersections, which contradicts the findings obtained from the propensity scores-potential outcomes framework. This finding underscores the importance of having comparable treated and untreated entities in traffic safety countermeasure evaluations. Copyright © 2014 Elsevier Ltd. All rights reserved.
A Heckman selection model for the safety analysis of signalized intersections
Wong, S. C.; Zhu, Feng; Pei, Xin; Huang, Helai; Liu, Youjun
2017-01-01
Purpose The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously. Methods This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI), respectively. The model uses 555 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during two years. Results The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels. Conclusions A comparison with the existing approaches suggests that the Heckman selection model offers an efficient and convenient alternative method for evaluating the safety performance at signalized intersections. PMID:28732050
A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data.
Ye, Xin; Wang, Ke; Zou, Yajie; Lord, Dominique
2018-01-01
This paper develops a semi-nonparametric Poisson regression model to analyze motor vehicle crash frequency data collected from rural multilane highway segments in California, US. Motor vehicle crash frequency on rural highway is a topic of interest in the area of transportation safety due to higher driving speeds and the resultant severity level. Unlike the traditional Negative Binomial (NB) model, the semi-nonparametric Poisson regression model can accommodate an unobserved heterogeneity following a highly flexible semi-nonparametric (SNP) distribution. Simulation experiments are conducted to demonstrate that the SNP distribution can well mimic a large family of distributions, including normal distributions, log-gamma distributions, bimodal and trimodal distributions. Empirical estimation results show that such flexibility offered by the SNP distribution can greatly improve model precision and the overall goodness-of-fit. The semi-nonparametric distribution can provide a better understanding of crash data structure through its ability to capture potential multimodality in the distribution of unobserved heterogeneity. When estimated coefficients in empirical models are compared, SNP and NB models are found to have a substantially different coefficient for the dummy variable indicating the lane width. The SNP model with better statistical performance suggests that the NB model overestimates the effect of lane width on crash frequency reduction by 83.1%.
Cheng, Wen; Gill, Gurdiljot Singh; Sakrani, Taha; Dasu, Mohan; Zhou, Jiao
2017-11-01
Motorcycle crashes constitute a very high proportion of the overall motor vehicle fatalities in the United States, and many studies have examined the influential factors under various conditions. However, research on the impact of weather conditions on the motorcycle crash severity is not well documented. In this study, we examined the impact of weather conditions on motorcycle crash injuries at four different severity levels using San Francisco motorcycle crash injury data. Five models were developed using Full Bayesian formulation accounting for different correlations commonly seen in crash data and then compared for fitness and performance. Results indicate that the models with serial and severity variations of parameters had superior fit, and the capability of accurate crash prediction. The inferences from the parameter estimates from the five models were: an increase in the air temperature reduced the possibility of a fatal crash but had a reverse impact on crashes of other severity levels; humidity in air was not observed to have a predictable or strong impact on crashes; the occurrence of rainfall decreased the possibility of crashes for all severity levels. Transportation agencies might benefit from the research results to improve road safety by providing motorcyclists with information regarding the risk of certain crash severity levels for special weather conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.
An empirical analysis of farm vehicle crash injury severities on Iowa's public road system.
Gkritza, Konstantina; Kinzenbaw, Caroline R; Hallmark, Shauna; Hawkins, Neal
2010-07-01
Farm vehicle crashes are a major safety concern for farmers as well as all other users of the public road system in agricultural states. Using data on farm vehicle crashes that occurred on Iowa's public roads between 2004 and 2006, we estimate a multinomial logit model to identify crash-, farm vehicle-, and driver-specific factors that determine farm vehicle crash injury severity outcomes. Estimation findings indicate that there are crash patterns (rear-end manner of collision; single-vehicle crash; farm vehicle crossed the centerline or median) and conditions (obstructed vision and crash in rural area; dry road, dark lighting, speed limit 55 mph or higher, and harvesting season), as well as farm vehicle and driver-contributing characteristics (old farm vehicle, young farm vehicle driver), where targeted intervention can help reduce the severity of crash outcomes. Determining these contributing factors and their effect is the first step to identifying countermeasures and safety strategies in a bid to improve transportation safety for all users on the public road system in Iowa as well as other agricultural states. Copyright 2010 Elsevier Ltd. All rights reserved.
Carter, Patrick M; Flannagan, Carol A C; Bingham, C Raymond; Cunningham, Rebecca M; Rupp, Jonathan D
2014-01-01
Seat belts are the most effective method of decreasing fatal and nonfatal motor vehicle crash injury. Advocacy groups have recently been successful in enacting repeals of mandatory motorcycle helmet laws in several states. In some states, this has prompted renewed efforts aimed at repealing mandatory seat belt laws. To evaluate and quantify the potential impact of rescinding seat belt laws on annual crash-related fatalities, nonfatal injuries, and associated economic costs, using Michigan as a model, to inform the national debate. Proportional injury rates were calculated utilizing police-reported statewide passenger vehicle crash data from 1999 and 2002, where belt use rates approximate estimates associated with repeal of primary and secondary seat belt laws. Proportional rates were applied to the most recent year of crash data (2011) to estimate changes in statewide fatalities and nonfatal injuries. National cost estimates were applied to injury data to calculate associated economic costs. Full repeal of the seat belt law is estimated to result in an additional 163 fatalities, 13,722 nonfatal injuries, and an associated societal cost of $1.6 billion annually. Repeal of the primary seat belt law only is estimated to result in an additional 95 fatalities, 9156 nonfatal injuries, and an associated societal cost of $1.0 billion annually. This analysis suggests that repealing the either the primary or full seat belt law would have a substantial and negative impact on public health, increasing motor vehicle crash related fatality, nonfatal injury, and associated economic costs.
Costs of Alcohol-Involved Crashes, United States, 2010
Zaloshnja, Eduard; Miller, Ted R.; Blincoe, Lawrence J.
2013-01-01
This paper estimates total and unit costs of alcohol-involved crashes in the U.S. in 2010. With methods from earlier studies, we estimated costs per crash survivor by MAIS, body part, and fracture/dislocation involvement. We multiplied them times 2010 crash incidence estimates from NHTSA data sets, with adjustments for underreporting of crashes and their alcohol involvement. The unit costs are lifetime costs discounted at 3%. To develop medical costs, we combined 2008 Health Care Utilization Program national data for hospitalizations and ED visits of crash survivors with prior estimates of post-discharge costs. Productivity losses drew on Current Population Survey and American Time Use Survey data. Quality of life losses came from a 2011 AAAM paper and property damage from insurance data. We built a hybrid incidence file comprised of 2008–2010 and 1984–86 NHTSA crash surveillance data, weighted with 2010 General Estimates System weights. Fatality data came from the 2010 FARS. An estimated 12% of 2010 crashes but only 0.9% of miles driven were alcohol-involved (BAC > .05). Alcohol-involved crashes cost an estimated $125 billion. That is 22.5% of the societal cost of all crashes. Alcohol-attributable crashes accounted for an estimated 22.5% of US auto liability insurance payments. Alcohol-involved crashes cost $0.86 per drink. Above the US BAC limit of .08, crash costs were $8.37 per mile driven; 1 in 788 trips resulted in a crash and 1 in 1,016 trips in an arrest. Unit costs for crash survivors by severity are higher for impaired driving than for other crashes. That suggests national aggregate impaired driving cost estimates in other countries are substantial underestimates if they are based on all-crash unit costs. PMID:24406941
Factor complexity of crash occurrence: An empirical demonstration using boosted regression trees.
Chung, Yi-Shih
2013-12-01
Factor complexity is a characteristic of traffic crashes. This paper proposes a novel method, namely boosted regression trees (BRT), to investigate the complex and nonlinear relationships in high-variance traffic crash data. The Taiwanese 2004-2005 single-vehicle motorcycle crash data are used to demonstrate the utility of BRT. Traditional logistic regression and classification and regression tree (CART) models are also used to compare their estimation results and external validities. Both the in-sample cross-validation and out-of-sample validation results show that an increase in tree complexity provides improved, although declining, classification performance, indicating a limited factor complexity of single-vehicle motorcycle crashes. The effects of crucial variables including geographical, time, and sociodemographic factors explain some fatal crashes. Relatively unique fatal crashes are better approximated by interactive terms, especially combinations of behavioral factors. BRT models generally provide improved transferability than conventional logistic regression and CART models. This study also discusses the implications of the results for devising safety policies. Copyright © 2012 Elsevier Ltd. All rights reserved.
Lee, Jaeyoung; Yasmin, Shamsunnahar; Eluru, Naveen; Abdel-Aty, Mohamed; Cai, Qing
2018-02-01
In traffic safety literature, crash frequency variables are analyzed using univariate count models or multivariate count models. In this study, we propose an alternative approach to modeling multiple crash frequency dependent variables. Instead of modeling the frequency of crashes we propose to analyze the proportion of crashes by vehicle type. A flexible mixed multinomial logit fractional split model is employed for analyzing the proportions of crashes by vehicle type at the macro-level. In this model, the proportion allocated to an alternative is probabilistically determined based on the alternative propensity as well as the propensity of all other alternatives. Thus, exogenous variables directly affect all alternatives. The approach is well suited to accommodate for large number of alternatives without a sizable increase in computational burden. The model was estimated using crash data at Traffic Analysis Zone (TAZ) level from Florida. The modeling results clearly illustrate the applicability of the proposed framework for crash proportion analysis. Further, the Excess Predicted Proportion (EPP)-a screening performance measure analogous to Highway Safety Manual (HSM), Excess Predicted Average Crash Frequency is proposed for hot zone identification. Using EPP, a statewide screening exercise by the various vehicle types considered in our analysis was undertaken. The screening results revealed that the spatial pattern of hot zones is substantially different across the various vehicle types considered. Copyright © 2017 Elsevier Ltd. All rights reserved.
Reductions in injury crashes associated with red light camera enforcement in oxnard, california.
Retting, Richard A; Kyrychenko, Sergey Y
2002-11-01
This study estimated the impact of red light camera enforcement on motor vehicle crashes in one of the first US communities to employ such cameras-Oxnard, California. Crash data were analyzed for Oxnard and for 3 comparison cities. Changes in crash frequencies were compared for Oxnard and control cities and for signalized and nonsignalized intersections by means of a generalized linear regression model. Overall, crashes at signalized intersections throughout Oxnard were reduced by 7% and injury crashes were reduced by 29%. Right-angle crashes, those most associated with red light violations, were reduced by 32%; right-angle crashes involving injuries were reduced by 68%. Because red light cameras can be a permanent component of the transportation infrastructure, crash reductions attributed to camera enforcement should be sustainable.
Spatial panel analyses of alcohol outlets and motor vehicle crashes in California: 1999–2008
Ponicki, William R.; Gruenewald, Paul J.; Remer, Lillian G.
2014-01-01
Although past research has linked alcohol outlet density to higher rates of drinking and many related social problems, there is conflicting evidence of density’s association with traffic crashes. An abundance of local alcohol outlets simultaneously encourages drinking and reduces driving distances required to obtain alcohol, leading to an indeterminate expected impact on alcohol-involved crash risk. This study separately investigates the effects of outlet density on (1) the risk of injury crashes relative to population and (2) the likelihood that any given crash is alcohol-involved, as indicated by police reports and single-vehicle nighttime status of crashes. Alcohol outlet density effects are estimated using Bayesian misalignment Poisson analyses of all California ZIP codes over the years 1999–2008. These misalignment models allow panel analysis of ZIP-code data despite frequent redefinition of postal-code boundaries, while also controlling for overdispersion and the effects of spatial autocorrelation. Because models control for overall retail density, estimated alcohol-outlet associations represent the extra effect of retail establishments selling alcohol. The results indicate a number of statistically well-supported associations between retail density and crash behavior, but the implied effects on crash risks are relatively small. Alcohol-serving restaurants have a greater impact on overall crash risks than on the likelihood that those crashes involve alcohol, whereas bars primarily affect the odds that crashes are alcohol-involved. Off-premise outlet density is negatively associated with risks of both crashes and alcohol involvement, while the presence of a tribal casino in a ZIP code is linked to higher odds of police-reported drinking involvement. Alcohol outlets in a given area are found to influence crash risks both locally and in adjacent ZIP codes, and significant spatial autocorrelation also suggests important relationships across geographical units. These results suggest that each type of alcohol outlet can have differing impacts on risks of crashing as well as the alcohol involvement of those crashes. PMID:23537623
Gender differences in injury severity risks in crashes at signalized intersections.
Obeng, K
2011-07-01
This paper analyzes gender differences in crash risk severities using data for signalized intersections. It estimates gender models for injury severity risks and finds that driver condition, type of crash, type of vehicle driven and vehicle safety features have different effects on females' and males' injury severity risks. Also, it finds some variables which are significantly related to females' injury severity risks but not males' and others which affect males' injury severity risks but not females'. It concludes that better and more in-depth information about gender differences in injury severity risks is gained by estimating separate models for females and males. Copyright © 2011 Elsevier Ltd. All rights reserved.
Sternlund, Simon; Strandroth, Johan; Rizzi, Matteo; Lie, Anders; Tingvall, Claes
2017-02-17
The objective of this study was to estimate the safety benefits of in vehicle lane departure warning (LDW) and lane keeping aid (LKA) systems in reducing relevant real-world passenger car injury crashes. The study used an induced exposure method, where LDW/LKA-sensitive and nonsensitive crashes were compared for Volvo passenger cars equipped with and without LDW/LKA systems. These crashes were matched by car make, model, model year, and technical equipment; that is, low-speed autonomous emergency braking (AEB) called City Safety (CS). The data were extracted from the Swedish Traffic Accident Data Acquisition database (STRADA) and consisted of 1,853 driver injury crashes that involved 146 LDW-equipped cars, 11 LKA-equipped cars, and 1,696 cars without LDW/LKA systems. The analysis showed a positive effect of the LDW/LKA systems in reducing lane departure crashes. The LDW/LKA systems were estimated to reduce head-on and single-vehicle injury crashes on Swedish roads with speed limits between 70 and 120 km/h and with dry or wet road surfaces (i.e., not covered by ice or snow) by 53% with a lower limit of 11% (95% confidence interval [CI]). This reduction corresponded to a reduction of 30% with a lower limit of 6% (95% CI) for all head-on and single-vehicle driver injury crashes (including all speed limits and all road surface conditions). LDW/LKA systems were estimated to lower the driver injury risk in crash types that the systems are designed to prevent; that is, head-on and single-vehicle crashes. Though these are important findings, they were based on a small data set. Therefore, further research is desirable to evaluate the effectiveness of LDW/LKA systems under real-world conditions and to differentiate the effectiveness between technical solutions (i.e., LDW and LKA) proposed by different manufacturers.
Dong, Chunjiao; Clarke, David B; Richards, Stephen H; Huang, Baoshan
2014-01-01
The influence of intersection features on safety has been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes. Although there are distinct differences between passenger cars and large trucks-size, operating characteristics, dimensions, and weight-modeling crash counts across vehicle types is rarely addressed. This paper develops and presents a multivariate regression model of crash frequencies by collision vehicle type using crash data for urban signalized intersections in Tennessee. In addition, the performance of univariate Poisson-lognormal (UVPLN), multivariate Poisson (MVP), and multivariate Poisson-lognormal (MVPLN) regression models in establishing the relationship between crashes, traffic factors, and geometric design of roadway intersections is investigated. Bayesian methods are used to estimate the unknown parameters of these models. The evaluation results suggest that the MVPLN model possesses most of the desirable statistical properties in developing the relationships. Compared to the UVPLN and MVP models, the MVPLN model better identifies significant factors and predicts crash frequencies. The findings suggest that traffic volume, truck percentage, lighting condition, and intersection angle significantly affect intersection safety. Important differences in car, car-truck, and truck crash frequencies with respect to various risk factors were found to exist between models. The paper provides some new or more comprehensive observations that have not been covered in previous studies. Copyright © 2013 Elsevier Ltd. All rights reserved.
Comparison of Test and Finite Element Analysis for Two Full-Scale Helicopter Crash Tests
NASA Technical Reports Server (NTRS)
Annett, Martin S.; Horta,Lucas G.
2011-01-01
Finite element analyses have been performed for two full-scale crash tests of an MD-500 helicopter. The first crash test was conducted to evaluate the performance of a composite deployable energy absorber under combined flight loads. In the second crash test, the energy absorber was removed to establish the baseline loads. The use of an energy absorbing device reduced the impact acceleration levels by a factor of three. Accelerations and kinematic data collected from the crash tests were compared to analytical results. Details of the full-scale crash tests and development of the system-integrated finite element model are briefly described along with direct comparisons of acceleration magnitudes and durations for the first full-scale crash test. Because load levels were significantly different between tests, models developed for the purposes of predicting the overall system response with external energy absorbers were not adequate under more severe conditions seen in the second crash test. Relative error comparisons were inadequate to guide model calibration. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used for the second full-scale crash test. The calibrated parameter set reduced 2-norm prediction error by 51% but did not improve impact shape orthogonality.
Assessing crash risk considering vehicle interactions with trucks using point detector data.
Hyun, Kyung Kate; Jeong, Kyungsoo; Tok, Andre; Ritchie, Stephen G
2018-03-12
Trucks have distinct driving characteristics in general traffic streams such as lower speeds and limitations in acceleration and deceleration. As a consequence, vehicles keep longer headways or frequently change lane when they follow a truck, which is expected to increase crash risk. This study introduces several traffic measures at the individual vehicle level to capture vehicle interactions between trucks and non-trucks and analyzed how the measures affect crash risk under different traffic conditions. The traffic measures were developed using headways obtained from Inductive Loop Detectors (ILDs). In addition, a truck detection algorithm using a Gaussian Mixture (GM) model was developed to identify trucks and to estimate truck exposure from ILD data. Using the identified vehicle types from the GM model, vehicle interaction metrics were categorized into three groups based on the combination of leading and following vehicle types. The effects of the proposed traffic measures on crash risk were modeled in two different cases of prior- and non-crash using a case-control approach utilizing a conditional logistic regression. Results showed that the vehicle interactions between the leading and following vehicle types were highly associated with crash risk, and further showed different impacts on crash risk by traffic conditions. Specifically, crashes were more likely to occur when a truck following a non-truck had shorter average headway but greater headway variance in heavy traffic while a non-truck following a truck had greater headway variance in light traffic. This study obtained meaningful conclusions that vehicle interactions involved with trucks were significantly related to the crash likelihood rather than the measures that estimate average traffic condition such as total volume or average headway of the traffic stream. Copyright © 2018 Elsevier Ltd. All rights reserved.
Dimitriou, Loukas; Stylianou, Katerina; Abdel-Aty, Mohamed A
2018-03-01
Rear-end crashes are one of the most frequently occurring crash types, especially in urban networks. An understanding of the contributing factors and their significant association with rear-end crashes is of practical importance and will help in the development of effective countermeasures. The objective of this study is to assess rear-end crash potential at a microscopic level in an urban environment, by investigating vehicle-by-vehicle interactions. To do so, several traffic parameters at the individual vehicle level have been taken into consideration, for capturing car-following characteristics and vehicle interactions, and to investigate their effect on potential rear-end crashes. In this study rear-end crash potential was estimated based on stopping distance between two consecutive vehicles, and four rear-end crash potential cases were developed. The results indicated that 66.4% of the observations were estimated as rear-end crash potentials. It was also shown that rear-end crash potential was presented when traffic flow and speed standard deviation were higher. Also, locational characteristics such as lane of travel and location in the network were found to affect drivers' car following decisions and additionally, it was shown that speeds were lower and headways higher when Heavy Goods Vehicles lead. Finally, a model-based behavioral analysis based on Multinomial Logit regression was conducted to systematically identify the statistically significant variables in explaining rear-end risk potential. The modeling results highlighted the significance of the explanatory variables associated with rear-end crash potential, however it was shown that their effect varied among different model configurations. The outcome of the results can be of significant value for several purposes, such as real-time monitoring of risk potential, allocating enforcement units in urban networks and designing targeted proactive safety policies. Copyright © 2018 Elsevier Ltd. All rights reserved.
An insight into the performance of road barriers - redistribution of barrier-relevant crashes.
Zou, Yaotian; Tarko, Andrew P
2016-11-01
Unlike most of traffic safety treatments that prevent crashes, road barriers reduce the severity of crash outcomes by replacing crashes with a high risk of severe injury and fatality (such as median crossover head-on collisions or collisions with high-hazard objects) with less risky events (such as collisions with barriers). This "crash conversion" is actually more complex than one-to-one replacement and it has not been studied yet. The published work estimated the reduction of selected types of crashes (typically, median crossover collisions) or the overall effect of barriers on crash severity. The objective of this study was to study the probabilities of various types of crash events possible under various road and barrier scenarios. The estimated probabilities are conditional given that at least one vehicle left the travelled way and the resulted crash had been recorded. The results are meant to deliver a useful insight onto the conversion of crashes by barriers from more to less risky to help better understand the mechanism of crash severity reduction. Such knowledge should allow engineers more accurate estimation of barriers' benefits and help researchers evaluate barriers' performance to improve the barrier's design. Seven barrier-relevant crash events possible after a vehicle departs the road could be identified based on the existing crash data and their probabilities estimated given the presence and location of three types of barriers: median concrete barriers, median and roadside W-beam steel guardrails, and high-tension median cable barriers. A multinomial logit model with variable outcomes was estimated based on 2049 barrier-relevant crashes occurred between 2003 and 2012 on 1258 unidirectional travelled ways in Indiana. The developed model allows calculating the changes in the probabilities of the barrier-relevant crash events. The results of this study indicated that road departures lead to less frequent crossings of unprotected (no barriers) medians 50-80ft. wide than for narrower medians 30-50ft wide. This benefit decreased with an increase in rollovers inside the median. Although our data indicated no median crossover events when a median barrier was present, the risk of crossovers, although low, is still present and could manifest itself if the sample were larger. The presence of barriers near a travelled way was associated with a higher risk of redirecting errant vehicles back to the roadway where they could collide with other vehicles continuing on the road. As expected, cable barriers installed on the far-side edge of a median were associated with a lower probability of being hit by errant vehicles and of redirecting vehicles into traffic than the nearside cable barriers. On the other hand, the probability of off-road non-barrier crashes was higher because vehicles penetrating the median from the unprotected side were exposed to median ditches and similar obstacles. The roadside guardrails were confirmed to reduce the percentage of hazardous off-road crashes. The results of this study facilitate a more transparent evaluation of the safety effect of road barriers. Copyright © 2016 Elsevier Ltd. All rights reserved.
Investigation of pedestrian crashes on two-way two-lane rural roads in Ethiopia.
Tulu, Getu Segni; Washington, Simon; Haque, Md Mazharul; King, Mark J
2015-05-01
Understanding pedestrian crash causes and contributing factors in developing countries is critically important as they account for about 55% of all traffic crashes. Not surprisingly, considerable attention in the literature has been paid to road traffic crash prediction models and methodologies in developing countries of late. Despite this interest, there are significant challenges confronting safety managers in developing countries. For example, in spite of the prominence of pedestrian crashes occurring on two-way two-lane rural roads, it has proven difficult to develop pedestrian crash prediction models due to a lack of both traffic and pedestrian exposure data. This general lack of available data has further hampered identification of pedestrian crash causes and subsequent estimation of pedestrian safety performance functions. The challenges are similar across developing nations, where little is known about the relationship between pedestrian crashes, traffic flow, and road environment variables on rural two-way roads, and where unique predictor variables may be needed to capture the unique crash risk circumstances. This paper describes pedestrian crash safety performance functions for two-way two-lane rural roads in Ethiopia as a function of traffic flow, pedestrian flows, and road geometry characteristics. In particular, random parameter negative binomial model was used to investigate pedestrian crashes. The models and their interpretations make important contributions to road crash analysis and prevention in developing countries. They also assist in the identification of the contributing factors to pedestrian crashes, with the intent to identify potential design and operational improvements. Copyright © 2015. Published by Elsevier Ltd.
Effects of blind spot monitoring systems on police-reported lane-change crashes.
Cicchino, Jessica B
2018-06-21
To examine the effectiveness of blind spot monitoring systems in preventing police-reported lane-change crashes. Poisson regression was used to compare crash involvement rates per insured vehicle year in police-reported lane-change crashes in 26 U.S. states during 2009-2015 between vehicles with blind spot monitoring and the same vehicle models without the optional system, controlling for other factors that can affect crash risk. Crash involvement rates in lane-change crashes were 14% lower (95% confidence limits -24% to -2%) among vehicles with blind spot monitoring than those without. Blind spot monitoring systems are effective in preventing police-reported lane-change crashes when considering crashes of all severities. If every U.S. vehicle in 2015 were equipped with blind spot monitoring that performed like the study systems, it is estimated that about 50,000 crashes could have been prevented.
Chen, Cong; Zhang, Guohui; Liu, Xiaoyue Cathy; Ci, Yusheng; Huang, Helai; Ma, Jianming; Chen, Yanyan; Guan, Hongzhi
2016-12-01
There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.
Cameron, M H; Elvik, R
2010-11-01
Nilsson (1981) proposed power relationships connecting changes in traffic speeds with changes in road crashes at various levels of injury severity. Increases in fatal crashes are related to the 4(th) power of the increase in mean speed, increases in serious casualty crashes (those involving death or serious injury) according to the 3(rd) power, and increases in casualty crashes (those involving death or any injury) according to the 2(nd) power. Increases in numbers of crash victims at cumulative levels of injury severity are related to the crash increases plus higher powers predicting the number of victims per crash. These relationships are frequently applied in OECD countries to estimate road trauma reductions resulting from expected speed reductions. The relationships were empirically derived based on speed changes resulting from a large number of rural speed limit changes in Sweden during 1967-1972. Nilsson (2004) noted that there had been very few urban speed limit changes studied to test his power model. This paper aims to test the assumption that the model is equally applicable in all road environments. It was found that the road environment is an important moderator of Nilsson's power model. While Nilsson's model appears satisfactory for rural highways and freeways, the model does not appear to be directly applicable to traffic speed changes on urban arterial roads. The evidence of monotonically increasing powers applicable to changes in road trauma at increasing injury severity levels with changes in mean speed is weak. The estimated power applicable to serious casualties on urban arterial roads was significantly less than that on rural highways, which was also significantly less than that on freeways. Alternative models linking the parameters of speed distributions with road trauma are reviewed and some conclusions reached for their use on urban roads instead of Nilsson's model. Further research is needed on the relationships between serious road trauma and urban speeds. 2010 Elsevier Ltd. All rights reserved.
Front air bag nondeployments in frontal crashes fatal to drivers or right-front passengers.
Braver, Elisa R; McCartt, Anne T; Sherwood, Christopher P; Zuby, David S; Blanar, Laura; Scerbo, Marge
2010-04-01
Public concern has arisen about the reliability of front air bags because Fatality Analysis Reporting System (FARS) data indicate many nondeployed air bags in fatal frontal crashes. However, the accuracy of air bag deployment, the variable in question, is uncertain. This study aimed to provide more certain estimates of nondeployment incidence in fatal frontal crashes. Fatally injured passenger vehicle drivers and right-front passengers in frontal crashes were identified in two U.S. databases for calendar years 1998-2006 and model years 1994-2006: FARS, a census of police-reported fatal crashes on public roads, and National Automotive Sampling System/Crashworthiness Data System (NASS/CDS), a probability sample of tow-away crashes. NASS/CDS contains subsets of fatal crashes in FARS and collects detailed data using crash investigators. Front air bag deployment coding for front-seat occupant fatalities was compared in FARS and NASS/CDS, and case reviews were conducted. Among FARS frontal deaths with available deployment status (N = 43,169), front air bags were coded as not deployed for 18 percent of front occupants. In comparison, NASS/CDS (N = 628) reported 9 percent (weighted estimate) nondeployment among front occupants killed. Among crashes common to both databases, NASS/CDS reported deployments for 45 percent of front occupant deaths for which FARS had coded nondeployments. Detailed case reviews of NASS/CDS crashes indicated highly accurate coding for deployment status. Based on this case review, 8 percent (weighted estimate) of front occupant deaths in frontal crashes appeared to involve air bag nondeployments; 1-2 percent of front occupant deaths represented potential system failures where deployments would have been expected. Air bag deployments appeared unwarranted in most nondeployments based on crash characteristics. FARS data overstate the magnitude of the problem of air bag deployment failures; steps should be taken to improve coding. There are inherent uncertainties in judgments about whether or not air bags would be expected to deploy in some crashes. Continued monitoring of air bag performance is warranted.
Calibration of Airframe and Occupant Models for Two Full-Scale Rotorcraft Crash Tests
NASA Technical Reports Server (NTRS)
Annett, Martin S.; Horta, Lucas G.; Polanco, Michael A.
2012-01-01
Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. Accelerations and kinematic data collected from the crash tests were compared to a system integrated finite element model of the test article. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the second full-scale crash test. This combination of heuristic and quantitative methods was used to identify modeling deficiencies, evaluate parameter importance, and propose required model changes. It is shown that the multi-dimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and co-pilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. This approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and test planning guidance. Complete crash simulations with validated finite element models can be used to satisfy crash certification requirements, thereby reducing overall development costs.
Modeling work zone crash frequency by quantifying measurement errors in work zone length.
Yang, Hong; Ozbay, Kaan; Ozturk, Ozgur; Yildirimoglu, Mehmet
2013-06-01
Work zones are temporary traffic control zones that can potentially cause safety problems. Maintaining safety, while implementing necessary changes on roadways, is an important challenge traffic engineers and researchers have to confront. In this study, the risk factors in work zone safety evaluation were identified through the estimation of a crash frequency (CF) model. Measurement errors in explanatory variables of a CF model can lead to unreliable estimates of certain parameters. Among these, work zone length raises a major concern in this analysis because it may change as the construction schedule progresses generally without being properly documented. This paper proposes an improved modeling and estimation approach that involves the use of a measurement error (ME) model integrated with the traditional negative binomial (NB) model. The proposed approach was compared with the traditional NB approach. Both models were estimated using a large dataset that consists of 60 work zones in New Jersey. Results showed that the proposed improved approach outperformed the traditional approach in terms of goodness-of-fit statistics. Moreover it is shown that the use of the traditional NB approach in this context can lead to the overestimation of the effect of work zone length on the crash occurrence. Copyright © 2013 Elsevier Ltd. All rights reserved.
Improved guidelines for estimating the Highway safety manual calibration factors.
DOT National Transportation Integrated Search
2016-01-01
Crash prediction models can be used to predict the number of crashes and evaluate roadway safety. Part C of the first edition of the Highway Safety Manual (HSM) provides safety performance functions (SPFs). The HSM addendum that includes freeway and ...
Xu, Chengcheng; Wang, Wei; Liu, Pan; Zhang, Fangwei
2015-01-01
This study aimed to identify the traffic flow variables contributing to crash risks under different traffic states and to develop a real-time crash risk model incorporating the varying crash mechanisms across different traffic states. The crash, traffic, and geometric data were collected on the I-880N freeway in California in 2008 and 2009. This study considered 4 different traffic states in Wu's 4-phase traffic theory. They are free fluid traffic, bunched fluid traffic, bunched congested traffic, and standing congested traffic. Several different statistical methods were used to accomplish the research objective. The preliminary analysis showed that traffic states significantly affected crash likelihood, collision type, and injury severity. Nonlinear canonical correlation analysis (NLCCA) was conducted to identify the underlying phenomena that made certain traffic states more hazardous than others. The results suggested that different traffic states were associated with various collision types and injury severities. The matching of traffic flow characteristics and crash characteristics in NLCCA revealed how traffic states affected traffic safety. The logistic regression analyses showed that the factors contributing to crash risks were quite different across various traffic states. To incorporate the varying crash mechanisms across different traffic states, random parameters logistic regression was used to develop a real-time crash risk model. Bayesian inference based on Markov chain Monte Carlo simulations was used for model estimation. The parameters of traffic flow variables in the model were allowed to vary across different traffic states. Compared with the standard logistic regression model, the proposed model significantly improved the goodness-of-fit and predictive performance. These results can promote a better understanding of the relationship between traffic flow characteristics and crash risks, which is valuable knowledge in the pursuit of improving traffic safety on freeways through the use of dynamic safety management systems.
Selection of comparison crash types for quasi-induced exposure risk estimation.
Keall, Michael; Newstead, Stuart
2009-03-01
The objective of this study was to find a comparison crash type that best represented exposure on the road and to identify situations where the induced exposure risk estimates were likely to be biased. Counts of crash involvements were compared with distance driven estimates derived from a register of licensed motor vehicles to identify the most appropriate comparison crash type for induced exposure estimation, which is the crash type whose counts are best correlated with vehicle distance driven. The best sets of comparison crashes for disaggregations by driver age and gender and vehicle type were found to be multi-vehicle crashes in which the vehicle was damaged in the rear or multi-vehicle crashes in which the driver was adjudged to be not at fault. Likely bias of induced exposure risk estimates was identified, even for these best sets of comparison crashes, according to vehicle size (with large vehicles underrepresented) and owner age and gender (with young owners and female owners overrepresented). This research identified some important features of crash occurrence useful for making choices of comparison crash types when controlling for exposure. None of the crash types considered as comparison crashes performed perfectly. Even the crash types that seemed to best reflect exposure on the road still appeared to over- or underestimate distance driven according to owner age group, gender, and vehicle size.
Modelling the effect on injuries and fatalities when changing mode of transport from car to bicycle.
Nilsson, Philip; Stigson, Helena; Ohlin, Maria; Strandroth, Johan
2017-03-01
Several studies have estimated the health effects of active commuting, where a transport mode shift from car to bicycle reduces risk of mortality and morbidity. Previous studies mainly assess the negative aspects of bicycling by referring to fatalities or police reported injuries. However, most bicycle crashes are not reported by the police and therefore hospital reported data would cover a much higher rate of injuries from bicycle crashes. The aim of the present study was to estimate the effect on injuries and fatalities from traffic crashes when shifting mode of transport from car to bicycle by using hospital reported data. This present study models the change in number of injuries and fatalities due to a transport mode change using a given flow change from car to bicycle and current injury and fatality risk per distance for bicyclists and car occupants. show that bicyclists have a much higher injury risk (29 times) and fatality risk (10 times) than car occupants. In a scenario where car occupants in Stockholm living close to their work place shifts transport mode to bicycling, injuries, fatalities and health loss expressed in Disability-Adjusted Life Years (DALY) were estimated to increase. The vast majority of the estimated DALY increase was caused by severe injuries and fatalities and it tends to fluctuate so that the number of severe crashes may exceed the estimation with a large margin. Although the estimated increase of traffic crashes and DALY, a transport mode shift is seen as a way towards a more sustainable society. Thus, this present study highlights the need of strategic preventive measures in order to minimize the negative impacts from increased bicycling. Copyright © 2016 Elsevier Ltd. All rights reserved.
Islam, Samantha; Brown, Joshua
2017-11-01
The research described in this paper explored the factors contributing to the injury severity resulting from the motorcycle at-fault accidents in rural and urban areas in Alabama. Given the occurrence of a motorcycle at-fault crash, random parameter logit models of injury severity (with possible outcomes of fatal, major, minor, and possible or no injury) were estimated. The estimated models identified a variety of statistically significant factors influencing the injury severities resulting from motorcycle at-fault crashes. According to these models, some variables were found to be significant only in one model (rural or urban) but not in the other one. For example, variables such as clear weather, young motorcyclists, and roadway without light were found significant only in the rural model. On the other hand, variables such as older female motorcyclists, horizontal curve and at intersection were found significant only in the urban model. In addition, some variables (such as, motorcyclists under influence of alcohol, non-usage of helmet, high speed roadways, etc.) were found significant in both models. Also, estimation findings showed that two parameters (clear weather and roadway without light) in the rural model and one parameter (on weekend) in the urban model could be modeled as random parameters indicating their varying influences on the injury severity due to unobserved effects. Based on the results obtained, this paper discusses the effects of different variables on injury severities resulting from rural and urban motorcycle at-fault crashes and their possible explanations. Copyright © 2017 Elsevier Ltd. All rights reserved.
Venkataraman, Narayan; Ulfarsson, Gudmundur F; Shankar, Venky N
2013-10-01
A nine-year (1999-2007) continuous panel of crash histories on interstates in Washington State, USA, was used to estimate random parameter negative binomial (RPNB) models for various aggregations of crashes. A total of 21 different models were assessed in terms of four ways to aggregate crashes, by: (a) severity, (b) number of vehicles involved, (c) crash type, and by (d) location characteristics. The models within these aggregations include specifications for all severities (property damage only, possible injury, evident injury, disabling injury, and fatality), number of vehicles involved (one-vehicle to five-or-more-vehicle), crash type (sideswipe, same direction, overturn, head-on, fixed object, rear-end, and other), and location types (urban interchange, rural interchange, urban non-interchange, rural non-interchange). A total of 1153 directional road segments comprising of the seven Washington State interstates were analyzed, yielding statistical models of crash frequency based on 10,377 observations. These results suggest that in general there was a significant improvement in log-likelihood when using RPNB compared to a fixed parameter negative binomial baseline model. Heterogeneity effects are most noticeable for lighting type, road curvature, and traffic volume (ADT). Median lighting or right-side lighting are linked to increased crash frequencies in many models for more than half of the road segments compared to both-sides lighting. Both-sides lighting thereby appears to generally lead to a safety improvement. Traffic volume has a random parameter but the effect is always toward increasing crash frequencies as expected. However that the effect is random shows that the effect of traffic volume on crash frequency is complex and varies by road segment. The number of lanes has a random parameter effect only in the interchange type models. The results show that road segment-specific insights into crash frequency occurrence can lead to improved design policy and project prioritization. Copyright © 2013 Elsevier Ltd. All rights reserved.
Bärgman, Jonas; Boda, Christian-Nils; Dozza, Marco
2017-05-01
As the development and deployment of in-vehicle intelligent safety systems (ISS) for crash avoidance and mitigation have rapidly increased in the last decades, the need to evaluate their prospective safety benefits before introduction has never been higher. Counterfactual simulations using relevant mathematical models (for vehicle dynamics, sensors, the environment, ISS algorithms, and models of driver behavior) have been identified as having high potential. However, although most of these models are relatively mature, models of driver behavior in the critical seconds before a crash are still relatively immature. There are also large conceptual differences between different driver models. The objective of this paper is, firstly, to demonstrate the importance of the choice of driver model when counterfactual simulations are used to evaluate two ISS: Forward collision warning (FCW), and autonomous emergency braking (AEB). Secondly, the paper demonstrates how counterfactual simulations can be used to perform sensitivity analyses on parameter settings, both for driver behavior and ISS algorithms. Finally, the paper evaluates the effect of the choice of glance distribution in the driver behavior model on the safety benefit estimation. The paper uses pre-crash kinematics and driver behavior from 34 rear-end crashes from the SHRP2 naturalistic driving study for the demonstrations. The results for FCW show a large difference in the percent of avoided crashes between conceptually different models of driver behavior, while differences were small for conceptually similar models. As expected, the choice of model of driver behavior did not affect AEB benefit much. Based on our results, researchers and others who aim to evaluate ISS with the driver in the loop through counterfactual simulations should be sure to make deliberate and well-grounded choices of driver models: the choice of model matters. Copyright © 2017 Elsevier Ltd. All rights reserved.
Predicting reduced visibility related crashes on freeways using real-time traffic flow data.
Hassan, Hany M; Abdel-Aty, Mohamed A
2013-06-01
The main objective of this paper is to investigate whether real-time traffic flow data, collected from loop detectors and radar sensors on freeways, can be used to predict crashes occurring at reduced visibility conditions. In addition, it examines the difference between significant factors associated with reduced visibility related crashes to those factors correlated with crashes occurring at clear visibility conditions. Random Forests and matched case-control logistic regression models were estimated. The findings indicated that real-time traffic variables can be used to predict visibility related crashes on freeways. The results showed that about 69% of reduced visibility related crashes were correctly identified. The results also indicated that traffic flow variables leading to visibility related crashes are slightly different from those variables leading to clear visibility crashes. Using time slices 5-15 minutes before crashes might provide an opportunity for the appropriate traffic management centers for a proactive intervention to reduce crash risk in real-time. Copyright © 2013 Elsevier Ltd. All rights reserved.
Safety performance of traffic phases and phase transitions in three phase traffic theory.
Xu, Chengcheng; Liu, Pan; Wang, Wei; Li, Zhibin
2015-12-01
Crash risk prediction models were developed to link safety to various phases and phase transitions defined by the three phase traffic theory. Results of the Bayesian conditional logit analysis showed that different traffic states differed distinctly with respect to safety performance. The random-parameter logit approach was utilized to account for the heterogeneity caused by unobserved factors. The Bayesian inference approach based on the Markov Chain Monte Carlo (MCMC) method was used for the estimation of the random-parameter logit model. The proposed approach increased the prediction performance of the crash risk models as compared with the conventional logit model. The three phase traffic theory can help us better understand the mechanism of crash occurrences in various traffic states. The contributing factors to crash likelihood can be well explained by the mechanism of phase transitions. We further discovered that the free flow state can be divided into two sub-phases on the basis of safety performance, including a true free flow state in which the interactions between vehicles are minor, and a platooned traffic state in which bunched vehicles travel in successions. The results of this study suggest that a safety perspective can be added to the three phase traffic theory. The results also suggest that the heterogeneity between different traffic states should be considered when estimating the risks of crash occurrences on freeways. Copyright © 2015 Elsevier Ltd. All rights reserved.
Selecting exposure measures in crash rate prediction for two-lane highway segments.
Qin, Xiao; Ivan, John N; Ravishanker, Nalini
2004-03-01
A critical part of any risk assessment is identifying how to represent exposure to the risk involved. Recent research shows that the relationship between crash count and traffic volume is non-linear; consequently, a simple crash rate computed as the ratio of crash count to volume is not proper for comparing the safety of sites with different traffic volumes. To solve this problem, we describe a new approach for relating traffic volume and crash incidence. Specifically, we disaggregate crashes into four types: (1) single-vehicle, (2) multi-vehicle same direction, (3) multi-vehicle opposite direction, and (4) multi-vehicle intersecting, and define candidate exposure measures for each that we hypothesize will be linear with respect to each crash type. This paper describes initial investigation using crash and physical characteristics data for highway segments in Michigan from the Highway Safety Information System (HSIS). We use zero-inflated-Poisson (ZIP) modeling to estimate models for predicting counts for each of the above crash types as a function of the daily volume, segment length, speed limit and roadway width. We found that the relationship between crashes and the daily volume (AADT) is non-linear and varies by crash type, and is significantly different from the relationship between crashes and segment length for all crash types. Our research will provide information to improve accuracy of crash predictions and, thus, facilitate more meaningful comparison of the safety record of seemingly similar highway locations.
Ramirez, Marizen; Bedford, Ronald; Wu, Hongqian; Harland, Karisa; Cavanaugh, Joseph E; Peek-Asa, Corinne
2016-01-01
Objective To evaluate the effectiveness of roadway policies for lighting and marking of farm equipment in reducing crashes in Illinois, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota and Wisconsin. Methods In this ecological study, state policies on lighting and marking of farm equipment were scored for compliance with standards of the American Society of Agricultural and Biological Engineers (ASABE). Using generalized estimating equations negative binomial models, we estimated the relationships between lighting and marking scores, and farm equipment crash rates, per 100 000 farm operations. Results A total of 7083 crashes involving farm equipment was reported from 2005 to 2010 in the Upper Midwest and Great Plains. As the state lighting and marking score increased by 5 units, crash rates reduced by 17% (rate ratio=0.83; 95% CI 0.78 to 0.88). Lighting-only (rate ratio=0.48; 95% CI 0.45 to 0.51) and marking-only policies (rate ratio=0.89; 95% CI 0.83 to 0.96) were each associated with reduced crash rates. Conclusions Aligning lighting and marking policies with ASABE standards may effectively reduce crash rates involving farm equipment. PMID:27405602
Green, Paul E; Woodrooffe, John
2006-01-01
Using data from the NASS General Estimates System (GES), the method of induced exposure was used to assess the effects of electronic stability control (ESC) on loss-of-control type crashes for sport utility vehicles. Sport utility vehicles were classified into crash types generally associated with loss of control and crash types most likely not associated with loss of control. Vehicles were then compared as to whether ESC technology was present or absent in the vehicles. A generalized additive model was fit to assess the effects of ESC, driver age, and driver gender on the odds of loss of control. In addition, the effects of ESC on roads that were not dry were compared to effects on roads that were dry. Overall, the estimated percentage reduction in the odds of a loss-of-control crash for sport utility vehicles equipped with ESC was 70.3%. Both genders and all age groups showed reduced odds of loss-of-control crashes, but there was no significant difference between males and females. With respect to driver age, the maximum percentage reduction of 73.6% occurred at age 27. The positive effects of ESC on roads that were not dry were significantly greater than on roads that were dry.
Costs of Crashes to Government, United States, 2008
Miller, Ted R; Bhattacharya, Soma; Zaloshnja, Eduard; Taylor, Dexter; Bahar, Geni; David, Iuliana
2011-01-01
We estimated how much the Federal government and state/local government pay for different kinds of crashes in the United States. Government costs include reductions in an array of public services (emergency, incident management, vocational rehabilitation, coroner court processing of liability litigation), medical payments, social safety net assistance to the injured and their families, and taxes foregone because victims miss work. Government also pays when its employees crash while working and covers fringe benefits for crash-involved employees and their benefit-eligible dependents in non-work hours. We estimated government shares of crash costs by component. We applied those estimates to existing US Department of Transportation estimates of crash costs to society and employers. Government pays an estimated $35 billion annually because of crashes, an estimated 12.6% of the economic cost of crashes (Federal 7.1%, State/local 5.5%). Government bears a higher percentage of the monetary costs of injury crashes than fatal crashes or crashes involving property damage only. Government is increasingly recovering the medical cost of crashes from auto insurers. Nevertheless, medical costs and income and sales tax losses account for 75% of government's crash costs. For State/local government to break even on a 100%-State funded investment in road safety, the intervention would need to have an unrealistically high benefit-cost ratio of 34. Government invests in medical treatment of illness to save lives and improve quality of life. Curing a child's leukemia, for example, is not less costly than leaving that leukemia untreated. Safety should not be held to a different standard. PMID:22105409
A spatial generalized ordered response model to examine highway crash injury severity.
Castro, Marisol; Paleti, Rajesh; Bhat, Chandra R
2013-03-01
This paper proposes a flexible econometric structure for injury severity analysis at the level of individual crashes that recognizes the ordinal nature of injury severity categories, allows unobserved heterogeneity in the effects of contributing factors, as well as accommodates spatial dependencies in the injury severity levels experienced in crashes that occur close to one another in space. The modeling framework is applied to analyze the injury severity sustained in crashes occurring on highway road segments in Austin, Texas. The sample is drawn from the Texas Department of Transportation (TxDOT) crash incident files from 2009 and includes a variety of crash characteristics, highway design attributes, driver and vehicle characteristics, and environmental factors. The results from our analysis underscore the value of our proposed model for data fit purposes as well as to accurately estimate variable effects. The most important determinants of injury severity on highways, according to our results, are (1) whether any vehicle occupant is ejected, (2) whether collision type is head-on, (3) whether any vehicle involved in the crash overturned, (4) whether any vehicle occupant is unrestrained by a seat-belt, and (5) whether a commercial truck is involved. Copyright © 2012 Elsevier Ltd. All rights reserved.
Iraeus, Johan; Lindquist, Mats
2016-10-01
Frontal crashes still account for approximately half of all fatalities in passenger cars, despite several decades of crash-related research. For serious injuries in this crash mode, several authors have listed the thorax as the most important. Computer simulation provides an effective tool to study crashes and evaluate injury mechanisms, and using stochastic input data, whole populations of crashes can be studied. The aim of this study was to develop a generic buck model and to validate this model on a population of real-life frontal crashes in terms of the risk of rib fracture. The study was conducted in four phases. In the first phase, real-life validation data were derived by analyzing NASS/CDS data to find the relationship between injury risk and crash parameters. In addition, available statistical distributions for the parameters were collected. In the second phase, a generic parameterized finite element (FE) model of a vehicle interior was developed based on laser scans from the A2MAC1 database. In the third phase, model parameters that could not be found in the literature were estimated using reverse engineering based on NCAP tests. Finally, in the fourth phase, the stochastic FE model was used to simulate a population of real-life crashes, and the result was compared to the validation data from phase one. The stochastic FE simulation model overestimates the risk of rib fracture, more for young occupants and less for senior occupants. However, if the effect of underestimation of rib fractures in the NASS/CDS material is accounted for using statistical simulations, the risk of rib fracture based on the stochastic FE model matches the risk based on the NASS/CDS data for senior occupants. The current version of the stochastic model can be used to evaluate new safety measures using a population of frontal crashes for senior occupants. Copyright © 2016 Elsevier Ltd. All rights reserved.
Carter, Patrick M; Flannagan, Carol A C; Bingham, C Raymond; Cunningham, Rebecca M; Rupp, Jonathan D
2015-05-01
We estimated the injury prevention impact and cost savings associated with alcohol interlock installation in all new US vehicles. We identified fatal and nonfatal injuries associated with drinking driver vehicle crashes from the Fatality Analysis Reporting System and National Automotive Sampling System's General Estimates System data sets (2006-2010). We derived the estimated impact of universal interlock installation using an estimate of the proportion of alcohol-related crashes that were preventable in vehicles < 1 year-old. We repeated this analysis for each subsequent year, assuming a 15-year implementation. We applied existing crash-induced injury cost metrics to approximate economic savings, and we used a sensitivity analysis to examine results with varying device effectiveness. Over 15 years, 85% of crash fatalities (> 59 000) and 84% to 88% of nonfatal injuries (> 1.25 million) attributed to drinking drivers would be prevented, saving an estimated $342 billion in injury-related costs, with the greatest injury and cost benefit realized among recently legal drinking drivers. Cost savings outweighed installation costs after 3 years, with the policy remaining cost effective provided device effectiveness remained above approximately 25%. Alcohol interlock installation in all new vehicles is likely a cost-effective primary prevention policy that will substantially reduce alcohol-involved crash fatalities and injuries, especially among young vulnerable drivers.
Flannagan, Carol A. C.; Bingham, C. Raymond; Cunningham, Rebecca M.; Rupp, Jonathan D.
2015-01-01
Objectives. We estimated the injury prevention impact and cost savings associated with alcohol interlock installation in all new US vehicles. Methods. We identified fatal and nonfatal injuries associated with drinking driver vehicle crashes from the Fatality Analysis Reporting System and National Automotive Sampling System’s General Estimates System data sets (2006–2010). We derived the estimated impact of universal interlock installation using an estimate of the proportion of alcohol-related crashes that were preventable in vehicles < 1 year-old. We repeated this analysis for each subsequent year, assuming a 15-year implementation. We applied existing crash-induced injury cost metrics to approximate economic savings, and we used a sensitivity analysis to examine results with varying device effectiveness. Results. Over 15 years, 85% of crash fatalities (> 59 000) and 84% to 88% of nonfatal injuries (> 1.25 million) attributed to drinking drivers would be prevented, saving an estimated $342 billion in injury-related costs, with the greatest injury and cost benefit realized among recently legal drinking drivers. Cost savings outweighed installation costs after 3 years, with the policy remaining cost effective provided device effectiveness remained above approximately 25%. Conclusions. Alcohol interlock installation in all new vehicles is likely a cost-effective primary prevention policy that will substantially reduce alcohol-involved crash fatalities and injuries, especially among young vulnerable drivers. PMID:25790385
Effects of red light camera enforcement on fatal crashes in large U.S. cities.
Hu, Wen; McCartt, Anne T; Teoh, Eric R
2011-08-01
To estimate the effects of red light camera enforcement on per capita fatal crash rates at intersections with signal lights. From the 99 large U.S. cities with more than 200,000 residents in 2008, 14 cities were identified with red light camera enforcement programs for all of 2004-2008 but not at any time during 1992-1996, and 48 cities were identified without camera programs during either period. Analyses compared the citywide per capita rate of fatal red light running crashes and the citywide per capita rate of all fatal crashes at signalized intersections during the two study periods, and rate changes then were compared for cities with and without cameras programs. Poisson regression was used to model crash rates as a function of red light camera enforcement, land area, and population density. The average annual rate of fatal red light running crashes declined for both study groups, but the decline was larger for cities with red light camera enforcement programs than for cities without camera programs (35% vs. 14%). The average annual rate of all fatal crashes at signalized intersections decreased by 14% for cities with camera programs and increased slightly (2%) for cities without cameras. After controlling for population density and land area, the rate of fatal red light running crashes during 2004-2008 for cities with camera programs was an estimated 24% lower than what would have been expected without cameras. The rate of all fatal crashes at signalized intersections during 2004-2008 for cities with camera programs was an estimated 17% lower than what would have been expected without cameras. Red light camera enforcement programs were associated with a statistically significant reduction in the citywide rate of fatal red light running crashes and a smaller but still significant reduction in the rate of all fatal crashes at signalized intersections. The study adds to the large body of evidence that red light camera enforcement can prevent the most serious crashes. Communities seeking to reduce crashes at intersections should consider this evidence. Copyright © 2011 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wenzel, Tom
In this report we compare two measures of driver risks: fatality risk per vehicle registration-year, and casualty (fatality plus serious injury) risk per police-reported crash. Our analysis is based on three sets of data from five states (Florida, Illinois, Maryland, Missouri, and Pennsylvania): data on all police-reported crashes involving model year 2000 to 2004 vehicles; 2005 county-level vehicle registration data by vehicle model year and make/model; and odometer readings from vehicle emission inspection and maintenance (I/M) programs conducted in urban areas of four of the five states (Florida does not have an I/M program). The two measures of risk couldmore » differ for three reasons: casualty risks are different from fatality risk; risks per vehicle registration-year are different from risks per crash; and risks estimated from national data are different from risks from the five states analyzed here. We also examined the effect of driver behavior, crash location, and general vehicle design on risk, as well as sources of potential bias in using the crash data from five states.« less
Another look at the safety effects of horizontal curvature on rural two-lane highways.
Saleem, Taha; Persaud, Bhagwant
2017-09-01
Crash Modification Factors (CMFs) are used to represent the effects on crashes of changes to highway design elements and are usually obtained from observational studies based on reported crashes. The design element of interest for this paper is horizontal curvature on rural 2-lane highways. The data for this study came from the Washington State database in the Highway Safety Information System (HSIS). Crash prediction models are developed for curve sections on rural 2-lane highway and the tangent sections up- and down-stream of the curve sections. Different negative binomial models were developed for segments on level grades (<3%), moderate grades (3-6%), and steep grades (>6%) to account for the confounding effects of gradient. The relationships between crashes at different traffic volumes and deflection angles are explored to illustrate how to get estimates of CMFs for increases in the minimum radius, considering the effect of increased tangent length for sharper curves, an effect that is overlooked in the Highway Safety Manual CMF, in addition to the effect of gradient. The results of that exploration indicated that even at different design speeds and deflection angles, the CMF estimates for incremental increases in radius lie within the same range, and that the crash reduction rate (CRR) is higher at segments on higher grades compared to the ones on lower grades. Copyright © 2017 Elsevier Ltd. All rights reserved.
Braver, E R; Ferguson, S A; Greene, M A; Lund, A K
1997-11-05
Virtually all new cars now are equipped with passenger air bags. Determining whether passenger air bags are saving lives is important, particularly because passenger air bags have caused some deaths among children and adults. To assess the effectiveness of passenger air bags in reducing the risk of death in frontal crashes for right front passengers. Air bags are designed to protect occupants in frontal crashes. Using Fatality Analysis Reporting System data for calendar years 1992 through 1995, the relative frequency of right front passenger deaths in frontal vs nonfrontal fatal crashes was compared for cars with dual air bags and for cars with driver-only air bags. Odds of right front passengers dying in frontal compared with nonfrontal fatal crashes were computed for 1992 through 1995 model year cars with dual air bags and for cars with driver-only air bags. Percentage reductions in right front passenger deaths in dual air bag vehicles were estimated. Right front passenger fatalities were 18% lower than expected in frontal crashes of cars with dual air bags and 11% lower in all crashes. An estimated 73 fewer than expected right front passengers died in 1992 through 1995 model cars with dual air bags during 1992 through 1995. The risk of frontal crash death for right front passengers in cars with dual air bags was reduced 14% among those reported to be using belts and 23% among belt nonusers. Children younger than 10 years in cars with dual air bags had a 34% increased risk of dying in frontal crashes. Passenger air bags were associated with substantial reductions in fatalities among right front passengers in frontal crashes. However, more children are being killed than are being saved by air bags. Immediate countermeasures to reduce the dangers of air bags to children and adults are suggested.
The effect of the learner license Graduated Driver Licensing components on teen drivers' crashes.
Ehsani, Johnathon Pouya; Bingham, C Raymond; Shope, Jean T
2013-10-01
Most studies evaluating the effectiveness of Graduated Driver Licensing (GDL) have focused on the overall system. Studies examining individual components have rarely accounted for the confounding of multiple, simultaneously implemented components. The purpose of this paper is to quantify the effects of a required learner license duration and required hours of supervised driving on teen driver fatal crashes. States that introduced a single GDL component independent of any other during the period 1990-2009 were identified. Monthly and quarterly fatal crash rates per 100,000 population of 16- and 17-year-old drivers were analyzed using single-state time series analysis, adjusting for adult crash rates and gasoline prices. Using the parameter estimates from each state's time series model, the pooled effect of each GDL component on 16- and 17-year-old drivers' fatal crashes was estimated using a random effects meta-analytic model to combine findings across states. In three states, a six-month minimum learner license duration was associated with a significant decline in combined 16- and 17-year-old drivers' fatal crash rates. The pooled effect of the minimum learner license duration across all states in the sample was associated with a significant change in combined 16- and 17-year-old driver fatal crash rates of -.07 (95% Confidence Interval [CI] -.11, -.03). Following the introduction of 30 h of required supervised driving in one state, novice drivers' fatal crash rates increased 35%. The pooled effect across all states in the study sample of having a supervised driving hour requirement was not significantly different from zero (.04, 95% CI -.15, .22). These findings suggest that a learner license duration of at least six-months may be necessary to achieve a significant decline in teen drivers' fatal crash rates. Evidence of the effect of required hours of supervised driving on teen drivers' fatal crash rates was mixed. Copyright © 2013 Elsevier Ltd. All rights reserved.
Safety modeling of urban arterials in Shanghai, China.
Wang, Xuesong; Fan, Tianxiang; Chen, Ming; Deng, Bing; Wu, Bing; Tremont, Paul
2015-10-01
Traffic safety on urban arterials is influenced by several key variables including geometric design features, land use, traffic volume, and travel speeds. This paper is an exploratory study of the relationship of these variables to safety. It uses a comparatively new method of measuring speeds by extracting GPS data from taxis operating on Shanghai's urban network. This GPS derived speed data, hereafter called Floating Car Data (FCD) was used to calculate average speeds during peak and off-peak hours, and was acquired from samples of 15,000+ taxis traveling on 176 segments over 18 major arterials in central Shanghai. Geometric design features of these arterials and surrounding land use characteristics were obtained by field investigation, and crash data was obtained from police reports. Bayesian inference using four different models, Poisson-lognormal (PLN), PLN with Maximum Likelihood priors (PLN-ML), hierarchical PLN (HPLN), and HPLN with Maximum Likelihood priors (HPLN-ML), was used to estimate crash frequencies. Results showed the HPLN-ML models had the best goodness-of-fit and efficiency, and models with ML priors yielded estimates with the lowest standard errors. Crash frequencies increased with increases in traffic volume. Higher average speeds were associated with higher crash frequencies during peak periods, but not during off-peak periods. Several geometric design features including average segment length of arterial, number of lanes, presence of non-motorized lanes, number of access points, and commercial land use, were positively related to crash frequencies. Copyright © 2015 Elsevier Ltd. All rights reserved.
Latent class analysis of factors that influence weekday and weekend single-vehicle crash severities.
Adanu, Emmanuel Kofi; Hainen, Alexander; Jones, Steven
2018-04-01
This paper investigates factors that influence the severity of single-vehicle crashes that happen on weekdays and weekends. Crash data from 2012 to 2016 for the State of Alabama was used for this study. Latent class logit models were developed as alternative to the frequently used random parameters models to account for unobserved heterogeneity across crash-severity observations. Exploration of the data revealed that a high proportion of severe injury injury crashes happened on weekends. The study examined whether single-vehicle crash contributing factors differ between weekdays and weekends. The model estimation results indicate a significant association of severe injury crashes to risk factors such as driver unemployment, driving with invalid license, no seatbelt use, fatigue, driving under influence, old age, and driving on county roads for both weekdays and weekends. Research findings show a strong link between human factors and the occurrence of severe injury single-vehicle crashes, as it has been observed that many of the factors associated with severe-injury outcome are driver behavior related. To illustrate the significance of the findings of this study, a third model using the combined data was developed to explore the merit of using sub-populations of the data for improved and detailed segmentation of the crash-severity factors. It has also been shown that generally, the factors that influence single-vehicle crash injury outcomes were not very different between weekdays and weekends. The findings of this study show the importance of investigating sub-populations of data to reveal complex relationships that should be understood as a necessary step in targeted countermeasure application. Copyright © 2018 Elsevier Ltd. All rights reserved.
Crash data and rates for age-sex groups of drivers, 1996
DOT National Transportation Integrated Search
1998-01-01
The results of this research note are based on 1996data for fatal crashes, driver licenses, and estimates of total crashes based upon data obtained from the nationally representative sample of crashes gathered in the General Estimates System (GES). T...
Crash cost estimates by maximum police-reported injury severity within selected crash geometrics
DOT National Transportation Integrated Search
2005-10-01
This paper presents estimates for the economic (human capital) and comprehensive costs per crash for six KABCO groupings within 22 selected crash types and within two speed limit categories (=80 km/h (>= 50 mi/h)). The comp...
Predicting regional variations in mortality from motor vehicle crashes.
Clark, D E; Cushing, B M
1999-02-01
To show that the previously-observed inverse relationship between population density and per-capita mortality from motor vehicle crashes can be derived from a simple mathematical model that can be used for prediction. The authors proposed models in which the number of fatal crashes in an area was directly proportional to the population and also to some power of the mean distance between hospitals. Alternatively, these can be parameterized as Weibull survival models. Using county and state data from the U.S. Census, the authors fitted linear regression equations on a logarithmic scale to test the validity of these models. The southern states conformed to a different model from the other states. If an indicator variable was used to distinguish these groups, the resulting model accounted for 74% of the variation from state to state (Alaska excepted). After controlling for mean inter-hospital distance, the southern states had a per-capita mortality 1.37 times that of the other states. Simply knowing the mean distance between hospitals in a region allows a fiarly accurate estimate of its per-capita mortality from vehicle crashes. After controlling for this factor, vehicle crash mortality per capita is higher in the southern states, for reasons yet to be explained.
Hu, Jingwen; Flannagan, Carol A; Bao, Shan; McCoy, Robert W; Siasoco, Kevin M; Barbat, Saeed
2015-11-01
The objective of this study is to develop a method that uses a combination of field data analysis, naturalistic driving data analysis, and computational simulations to explore the potential injury reduction capabilities of integrating passive and active safety systems in frontal impact conditions. For the purposes of this study, the active safety system is actually a driver assist (DA) feature that has the potential to reduce delta-V prior to a crash, in frontal or other crash scenarios. A field data analysis was first conducted to estimate the delta-V distribution change based on an assumption of 20% crash avoidance resulting from a pre-crash braking DA feature. Analysis of changes in driver head location during 470 hard braking events in a naturalistic driving study found that drivers' head positions were mostly in the center position before the braking onset, while the percentage of time drivers leaning forward or backward increased significantly after the braking onset. Parametric studies with a total of 4800 MADYMO simulations showed that both delta-V and occupant pre-crash posture had pronounced effects on occupant injury risks and on the optimal restraint designs. By combining the results for the delta-V and head position distribution changes, a weighted average of injury risk reduction of 17% and 48% was predicted by the 50th percentile Anthropomorphic Test Device (ATD) model and human body model, respectively, with the assumption that the restraint system can adapt to the specific delta-V and pre-crash posture. This study demonstrated the potential for further reducing occupant injury risk in frontal crashes by the integration of a passive safety system with a DA feature. Future analyses considering more vehicle models, various crash conditions, and variations of occupant characteristics, such as age, gender, weight, and height, are necessary to further investigate the potential capability of integrating passive and DA or active safety systems.
Loo, B P Y; Tsui, K L
2007-06-01
This paper aims to determine the percentage of road crashes resulting in injuries requiring hospital care that are reported to the police and to identify factors associated with reporting such crashes to the police. The data of one of two hospitals in the Road Casualty Information System were matched with the police's Traffic Accident Database System. Factors affecting the police-reporting rate were examined at two levels: the different reporting rates among subgroups examined and tested with chi2 tests; and multiple explanatory factors were scrutinised with a logistic regression model to arrive at the odds ratios to reflect the probability of police-reporting among subgroups. The police-reporting rate was estimated to be 57.5-59.9%. In particular, under-reporting among children (reporting rate = 33.6%) and cyclists (reporting rate = 33.0%) was notable. Accurate and reliable road crash data are essential for unveiling the full-scale and nature of the road safety problem. The police crash database needs to be supplemented by other data. In particular, any estimation about the social costs of road crashes must recognise the under-reporting problem. The large number of injuries not reflected in the police crash database represents a major public health issue that should be carefully examined.
Primary Enforcement of Mandatory Seat Belt Laws and Motor Vehicle Crash Deaths.
Harper, Sam; Strumpf, Erin C
2017-08-01
Policies that allow directly citing motorists for seat belt non-use (primary enforcement) have been shown to reduce motor vehicle crash deaths relative to secondary enforcement, but the evidence base is dated and does not account for recent improvements in vehicle designs and road safety. The purpose of this study was to test whether recent upgrades to primary enforcement still reduce motor vehicle crash deaths. In 2016, researchers used motor vehicle crash death data from the Fatal Analysis Reporting System for 2000-2014 and calculated rates using both person- and exposure-based denominators. Researchers used a difference-in-differences design to estimate the effect of primary enforcement on death rates, and estimated negative binomial regression models, controlling for age, substance use involvement, fixed state characteristics, secular trends, state median household income, and other state-level traffic safety policies. Models adjusted only for crash characteristics and state-level covariates models showed a protective effect of primary enforcement (rate ratio, 0.88, 95% CI=0.77, 0.98; rate difference, -1.47 deaths per 100,000 population, 95% CI= -2.75, -0.19). After adjustment for fixed state characteristics and secular trends, there was no evidence of an effect of upgrading from secondary to primary enforcement in the whole population (rate ratio, 0.98, 95% CI=0.92, 1.04; rate difference, -0.22, 95% CI= -0.90, 0.46) or for any age group. Upgrading to primary enforcement no longer appears protective for motor vehicle crash death rates. Copyright © 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Xie, Kun; Ozbay, Kaan; Kurkcu, Abdullah; Yang, Hong
2017-08-01
This study aims to explore the potential of using big data in advancing the pedestrian risk analysis including the investigation of contributing factors and the hotspot identification. Massive amounts of data of Manhattan from a variety of sources were collected, integrated, and processed, including taxi trips, subway turnstile counts, traffic volumes, road network, land use, sociodemographic, and social media data. The whole study area was uniformly split into grid cells as the basic geographical units of analysis. The cell-structured framework makes it easy to incorporate rich and diversified data into risk analysis. The cost of each crash, weighted by injury severity, was assigned to the cells based on the relative distance to the crash site using a kernel density function. A tobit model was developed to relate grid-cell-specific contributing factors to crash costs that are left-censored at zero. The potential for safety improvement (PSI) that could be obtained by using the actual crash cost minus the cost of "similar" sites estimated by the tobit model was used as a measure to identify and rank pedestrian crash hotspots. The proposed hotspot identification method takes into account two important factors that are generally ignored, i.e., injury severity and effects of exposure indicators. Big data, on the one hand, enable more precise estimation of the effects of risk factors by providing richer data for modeling, and on the other hand, enable large-scale hotspot identification with higher resolution than conventional methods based on census tracts or traffic analysis zones. © 2017 Society for Risk Analysis.
Escalera-Antezana, Juan Pablo; Dadvand, Payam; Llatje, Òscar; Barrera-Gómez, Jose; Cunillera, Jordi; Medina-Ramón, Mercedes; Pérez, Katherine
2015-01-01
Background Experimental studies have shown a decrease in driving performance at high temperatures. The epidemiological evidence for the relationship between heat and motor vehicle crashes is not consistent. Objectives We estimated the impact of high ambient temperatures on the daily number of motor vehicle crashes and, in particular, on crashes involving driver performance factors (namely distractions, driver error, fatigue, or sleepiness). Methods We performed a time-series analysis linking daily counts of motor vehicle crashes and daily temperature or occurrence of heat waves while controlling for temporal trends. All motor vehicle crashes with victims that occurred during the warm period of the years 2000–2011 in Catalonia (Spain) were included. Temperature data were obtained from 66 weather stations covering the region. Poisson regression models adjusted for precipitation, day of the week, month, year, and holiday periods were fitted to quantify the associations. Results The study included 118,489 motor vehicle crashes (an average of 64.1 per day). The estimated risk of crashes significantly increased by 2.9% [95% confidence interval (CI): 0.7%, 5.1%] during heat wave days, and this association was stronger (7.7%, 95% CI: 1.2%, 14.6%) when restricted to crashes with driver performance–associated factors. The estimated risk of crashes with driver performance factors significantly increased by 1.1% (95% CI: 0.1%, 2.1%) for each 1°C increase in maximum temperature. Conclusions Motor vehicle crashes involving driver performance–associated factors were increased in association with heat waves and increasing temperature. These findings are relevant for designing preventive plans in a context of global warming. Citation Basagaña X, Escalera-Antezana JP, Dadvand P, Llatje Ò, Barrera-Gómez J, Cunillera J, Medina-Ramón M, Pérez K. 2015. High ambient temperatures and risk of motor vehicle crashes in Catalonia, Spain (2000–2011): a time-series analysis. Environ Health Perspect 123:1309–1316; http://dx.doi.org/10.1289/ehp.1409223 PMID:26046727
Crash avoidance potential of four passenger vehicle technologies.
Jermakian, Jessica S
2011-05-01
The objective was to update estimates of maximum potential crash reductions in the United States associated with each of four crash avoidance technologies: side view assist, forward collision warning/mitigation, lane departure warning/prevention, and adaptive headlights. Compared with previous estimates (Farmer, 2008), estimates in this study attempted to account for known limitations of current systems. Crash records were extracted from the 2004-08 files of the National Automotive Sampling System General Estimates System (NASS GES) and the Fatality Analysis Reporting System (FARS). Crash descriptors such as vehicle damage location, road characteristics, time of day, and precrash maneuvers were reviewed to determine whether the information or action provided by each technology potentially could have prevented or mitigated the crash. Of the four crash avoidance technologies, forward collision warning/mitigation had the greatest potential for preventing crashes of any severity; the technology is potentially applicable to 1.2 million crashes in the United States each year, including 66,000 serious and moderate injury crashes and 879 fatal crashes. Lane departure warning/prevention systems appeared relevant to 179,000 crashes per year. Side view assist and adaptive headlights could prevent 395,000 and 142,000 crashes per year, respectively. Lane departure warning/prevention was relevant to the most fatal crashes, up to 7500 fatal crashes per year. A combination of all four current technologies potentially could prevent or mitigate (without double counting) up to 1,866,000 crashes each year, including 149,000 serious and moderate injury crashes and 10,238 fatal crashes. If forward collision warning were extended to detect objects, pedestrians, and bicyclists, it would be relevant to an additional 3868 unique fatal crashes. There is great potential effectiveness for vehicle-based crash avoidance systems. However, it is yet to be determined how drivers will interact with the systems. The actual effectiveness of these systems will not be known until sufficient real-world experience has been gained. Copyright © 2010 Elsevier Ltd. All rights reserved.
Figler, Bradley D; Mack, Christopher D; Kaufman, Robert; Wessells, Hunter; Bulger, Eileen; Smith, Thomas G; Voelzke, Bryan
2014-03-01
The National Highway Traffic Safety Administration's New Car Assessment Program (NCAP) implemented side-impact crash testing on all new vehicles since 1998 to assess the likelihood of major thoracoabdominal injuries during a side-impact crash. Higher crash test rating is intended to indicate a safer car, but the real-world applicability of these ratings is unknown. Our objective was to determine the relationship between a vehicle's NCAP side-impact crash test rating and the risk of major thoracoabdominal injury among the vehicle's occupants in real-world side-impact motor vehicle crashes. The National Automotive Sampling System Crashworthiness Data System contains detailed crash and injury data in a sample of major crashes in the United States. For model years 1998 to 2010 and crash years 1999 to 2010, 68,124 occupants were identified in the Crashworthiness Data System database. Because 47% of cases were missing crash severity (ΔV), multiple imputation was used to estimate the missing values. The primary predictor of interest was the occupant vehicle's NCAP side-impact crash test rating, and the outcome of interest was the presence of major (Abbreviated Injury Scale [AIS] score ≥ 3) thoracoabdominal injury. In multivariate analysis, increasing NCAP crash test rating was associated with lower likelihood of major thoracoabdominal injury at high (odds ratio [OR], 0.8; 95% confidence interval [CI], 0.7-0.9; p < 0.01) and medium (OR, 0.9; 95% CI, 0.8-1.0; p < 0.05) crash severity (ΔV), but not at low ΔV (OR, 0.95; 95% CI, 0.8-1.2; p = 0.55). In our model, older age and absence of seat belt use were associated with greater likelihood of major thoracoabdominal injury at low and medium ΔV (p < 0.001), but not at high ΔV (p ≥ 0.09). Among adults in model year 1998 to 2010 vehicles involved in medium and high severity motor vehicle crashes, a higher NCAP side-impact crash test rating is associated with a lower likelihood of major thoracoabdominal trauma. Epidemiologic study, level III.
Dong, Ni; Huang, Helai; Zheng, Liang
2015-09-01
In zone-level crash prediction, accounting for spatial dependence has become an extensively studied topic. This study proposes Support Vector Machine (SVM) model to address complex, large and multi-dimensional spatial data in crash prediction. Correlation-based Feature Selector (CFS) was applied to evaluate candidate factors possibly related to zonal crash frequency in handling high-dimension spatial data. To demonstrate the proposed approaches and to compare them with the Bayesian spatial model with conditional autoregressive prior (i.e., CAR), a dataset in Hillsborough county of Florida was employed. The results showed that SVM models accounting for spatial proximity outperform the non-spatial model in terms of model fitting and predictive performance, which indicates the reasonableness of considering cross-zonal spatial correlations. The best model predictive capability, relatively, is associated with the model considering proximity of the centroid distance by choosing the RBF kernel and setting the 10% of the whole dataset as the testing data, which further exhibits SVM models' capacity for addressing comparatively complex spatial data in regional crash prediction modeling. Moreover, SVM models exhibit the better goodness-of-fit compared with CAR models when utilizing the whole dataset as the samples. A sensitivity analysis of the centroid-distance-based spatial SVM models was conducted to capture the impacts of explanatory variables on the mean predicted probabilities for crash occurrence. While the results conform to the coefficient estimation in the CAR models, which supports the employment of the SVM model as an alternative in regional safety modeling. Copyright © 2015 Elsevier Ltd. All rights reserved.
Dong, Chunjiao; Xie, Kun; Zeng, Jin; Li, Xia
2018-04-01
Highway safety laws aim to influence driver behaviors so as to reduce the frequency and severity of crashes, and their outcomes. For one specific highway safety law, it would have different effects on the crashes across severities. Understanding such effects can help policy makers upgrade current laws and hence improve traffic safety. To investigate the effects of highway safety laws on crashes across severities, multivariate models are needed to account for the interdependency issues in crash counts across severities. Based on the characteristics of the dependent variables, multivariate dynamic Tobit (MVDT) models are proposed to analyze crash counts that are aggregated at the state level. Lagged observed dependent variables are incorporated into the MVDT models to account for potential temporal correlation issues in crash data. The state highway safety law related factors are used as the explanatory variables and socio-demographic and traffic factors are used as the control variables. Three models, a MVDT model with lagged observed dependent variables, a MVDT model with unobserved random variables, and a multivariate static Tobit (MVST) model are developed and compared. The results show that among the investigated models, the MVDT models with lagged observed dependent variables have the best goodness-of-fit. The findings indicate that, compared to the MVST, the MVDT models have better explanatory power and prediction accuracy. The MVDT model with lagged observed variables can better handle the stochasticity and dependency in the temporal evolution of the crash counts and the estimated values from the model are closer to the observed values. The results show that more lives could be saved if law enforcement agencies can make a sustained effort to educate the public about the importance of motorcyclists wearing helmets. Motor vehicle crash-related deaths, injuries, and property damages could be reduced if states enact laws for stricter text messaging rules, higher speeding fines, older licensing age, and stronger graduated licensing provisions. Injury and PDO crashes would be significantly reduced with stricter laws prohibiting the use of hand-held communication devices and higher fines for drunk driving. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Annett, Martin S.; Horta, Lucas G.; Jackson, Karen E.; Polanco, Michael A.; Littell, Justin D.
2012-01-01
Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber (DEA) under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. The presence of this energy absorbing device reduced the peak impact acceleration levels by a factor of three. Accelerations and kinematic data collected from the crash tests were compared to a system-integrated finite element model of the test article developed in parallel with the test program. In preparation for the full-scale crash test, a series of sub-scale and MD-500 mass simulator tests were conducted to evaluate the impact performances of various components and subsystems, including new crush tubes and the DEA blocks. Parameters defined for the system-integrated finite element model were determined from these tests. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the full-scale crash test without the DEA. This combination of heuristic and quantitative methods identified modeling deficiencies, evaluated parameter importance, and proposed required model changes. The multidimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and copilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. One lesson learned was that this approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and pretest predictions. Complete crash simulations with validated finite element models can be used to satisfy crash certification requirements, potentially reducing overall development costs.
Estimate of air carrier and air taxi crash frequencies from high altitude en route flight operations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sanzo, D.; Kimura, C.Y.; Prassinos, P.G.
1996-06-03
In estimating the frequency of an aircraft crashing into a facility, it has been found convenient to break the problem down into two broad categories. One category estimates the aircraft crash frequency due to air traffic from nearby airports, the so-called near-airport environment. The other category estimates the aircraft crash frequency onto facilities due to air traffic from airways, jet routes, and other traffic flying outside the near-airport environment The total aircraft crash frequency is the summation of the crash frequencies from each airport near the facility under evaluation and from all airways, jet routes, and other traffic near themore » facility of interest. This paper will examine the problems associated with the determining the aircraft crash frequencies onto facilities outside the near-airport environment. This paper will further concentrate on the estimating the risk of aircraft crashes to ground facilities due to high altitude air carrier and air taxi traffic. High altitude air carrier and air taxi traffic will be defined as all air carrier and air taxi flights above 18,000 feet Mean Sea Level (MSL).« less
Kaplan, Sigal; Prato, Carlo Giacomo
2012-01-01
The current study focuses on the propensity of drivers to engage in crash avoidance maneuvers in relation to driver attributes, critical events, crash characteristics, vehicles involved, road characteristics, and environmental conditions. The importance of avoidance maneuvers derives from the key role of proactive and state-aware road users within the concept of sustainable safety systems, as well as from the key role of effective corrective maneuvers in the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that represents the selection among 5 emergency lateral and speed control maneuvers (i.e., "no avoidance maneuvers," "braking," "steering," "braking and steering," and "other maneuvers) while accommodating correlations across maneuvers and heteroscedasticity. Data for the analysis were retrieved from the General Estimates System (GES) crash database for the year 2009 by considering drivers for which crash avoidance maneuvers are known. The results show that (1) the nature of the critical event that made the crash imminent greatly influences the choice of crash avoidance maneuvers, (2) women and elderly have a relatively lower propensity to conduct crash avoidance maneuvers, (3) drowsiness and fatigue have a greater negative marginal effect on the tendency to engage in crash avoidance maneuvers than alcohol and drug consumption, (4) difficult road conditions increase the propensity to perform crash avoidance maneuvers, and (5) visual obstruction and artificial illumination decrease the probability to carry out crash avoidance maneuvers. The results emphasize the need for public awareness campaigns to promote safe driving style for senior drivers and warning about the risks of driving under fatigue and distraction being comparable to the risks of driving under the influence of alcohol and drugs. Moreover, the results suggest the need to educate drivers about hazard perception, designing a forgiving infrastructure within a sustainable safety systems, and rethinking in-vehicle collision warning systems. Future research should address the effectiveness of crash avoidance maneuvers and joint modeling of maneuver selection and crash severity.
Hospital charges associated with motorcycle crash factors: a quantile regression analysis.
Olsen, Cody S; Thomas, Andrea M; Cook, Lawrence J
2014-08-01
Previous studies of motorcycle crash (MC) related hospital charges use trauma registries and hospital records, and do not adjust for the number of motorcyclists not requiring medical attention. This may lead to conservative estimates of helmet use effectiveness. MC records were probabilistically linked with emergency department and hospital records to obtain total hospital charges. Missing data were imputed. Multivariable quantile regression estimated reductions in hospital charges associated with helmet use and other crash factors. Motorcycle helmets were associated with reduced median hospital charges of $256 (42% reduction) and reduced 98th percentile of $32,390 (33% reduction). After adjusting for other factors, helmets were associated with reductions in charges in all upper percentiles studied. Quantile regression models described homogenous and heterogeneous associations between other crash factors and charges. Quantile regression comprehensively describes associations between crash factors and hospital charges. Helmet use among motorcyclists is associated with decreased hospital charges. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.
Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C
2017-01-01
This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.
Drinking, driving, and crashing: a traffic-flow model of alcohol-related motor vehicle accidents.
Gruenewald, Paul J; Johnson, Fred W
2010-03-01
This study examined the influence of on-premise alcohol-outlet densities and of drinking-driver densities on rates of alcohol-related motor vehicle crashes. A traffic-flow model is developed to represent geographic relationships between residential locations of drinking drivers, alcohol outlets, and alcohol-related motor vehicle crashes. Cross-sectional and time-series cross-sectional spatial analyses were performed using data collected from 144 geographic units over 4 years. Data were obtained from archival and survey sources in six communities. Archival data were obtained within community areas and measured activities of either the resident population or persons visiting these communities. These data included local and highway traffic flow, locations of alcohol outlets, population density, network density of the local roadway system, and single-vehicle nighttime (SVN) crashes. Telephone-survey data obtained from residents of the communities were used to estimate the size of the resident drinking and driving population. Cross-sectional analyses showed that effects relating on-premise densities to alcohol-related crashes were moderated by highway trafficflow. Depending on levels of highway traffic flow, 10% greater densities were related to 0% to 150% greater rates of SVN crashes. Time-series cross-sectional analyses showed that changes in the population pool of drinking drivers and on-premise densities interacted to increase SVN crash rates. A simple traffic-flow model can assess the effects of on-premise alcohol-outlet densities and of drinking-driver densities as they vary across communities to produce alcohol-related crashes. Analyses based on these models can usefully guide policy decisions on the sitting of on-premise alcohol outlets.
Pre-crash scenario typology for crash avoidance research
DOT National Transportation Integrated Search
2007-04-01
This report defines a new pre-crash scenario typology for crash avoidance research based on the 2004 General Estimates System (GES) crash database, which consists of pre-crash scenarios depicting vehicle movements and dynamics as well as the critical...
Antona-Makoshi, Jacobo; Mikami, Koji; Lindkvist, Mats; Davidsson, Johan; Schick, Sylvia
2018-08-01
This study estimated the frequency and risk of Moderate-to-Maximal traumatic brain injuries sustained by occupants in motor vehicle crashes in the US. National Automotive Sampling System - Crashworthiness Data System crashes that occurred in years 2001-2015 with light vehicles produced 2001 or later were incorporated in the study. Crash type, crash severity, car model year, belt usage and occupant age and sex were controlled for in the analysis. The results showed that Moderate concussions account for 79% of all MAIS brain 2+ injuries. Belted occupants were at lower risks than unbelted occupants for most brain injury categories, including concussions. After controlling for the effects of age and crash severity, belted female occupants involved in frontal crashes were estimated to be 1.5 times more likely to sustain a concussion than male occupants in similar conditions. Belted elderly occupants were found to be at 10.5 and 8 times higher risks for sub-dural haemorrhages than non-elderly belted occupants in frontal and side crashes, respectively. Adopted occupant protection strategies appear to be insufficient to achieve significant decreases in risk of both life-threatening brain injuries and concussions for all car occupants. Further effort to develop occupant and injury specific strategies for the prevention of brain injuries are needed. This study suggests that these strategies may consider prioritization of life-threatening brain vasculature injuries, particularly in elderly occupants, and concussion injuries, particularly in female occupants. Copyright © 2018 Elsevier Ltd. All rights reserved.
Ramirez, Marizen; Bedford, Ronald; Wu, Hongqian; Harland, Karisa; Cavanaugh, Joseph E; Peek-Asa, Corinne
2016-09-01
To evaluate the effectiveness of roadway policies for lighting and marking of farm equipment in reducing crashes in Illinois, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota and Wisconsin. In this ecological study, state policies on lighting and marking of farm equipment were scored for compliance with standards of the American Society of Agricultural and Biological Engineers (ASABE). Using generalized estimating equations negative binomial models, we estimated the relationships between lighting and marking scores, and farm equipment crash rates, per 100 000 farm operations. A total of 7083 crashes involving farm equipment was reported from 2005 to 2010 in the Upper Midwest and Great Plains. As the state lighting and marking score increased by 5 units, crash rates reduced by 17% (rate ratio=0.83; 95% CI 0.78 to 0.88). Lighting-only (rate ratio=0.48; 95% CI 0.45 to 0.51) and marking-only policies (rate ratio=0.89; 95% CI 0.83 to 0.96) were each associated with reduced crash rates. Aligning lighting and marking policies with ASABE standards may effectively reduce crash rates involving farm equipment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Multilevel analysis of the role of human factors in regional disparities in crash outcomes.
Adanu, Emmanuel Kofi; Smith, Randy; Powell, Lars; Jones, Steven
2017-12-01
A growing body of research has examined the disparities in road traffic safety among population groups and geographic regions. These studies reveal disparities in crash outcomes between people and regions with different socioeconomic characteristics. A critical aspect of the road traffic crash epidemic that has received limited attention is the influence of local characteristics on human elements that increase the risk of getting into a crash. This paper applies multilevel logistic regression modeling techniques to investigate the influence of driver residential factors on driver behaviors in an attempt to explain the area-based differences in the severity of road crashes across the State of Alabama. Specifically, the paper reports the effects of characteristics attributable to drivers and the geographic regions they reside on the likelihood of a crash resulting in serious injuries. Model estimation revealed that driver residence (postal code or region) accounted for about 7.3% of the variability in the probability of a driver getting into a serious injury crash, regardless of driver characteristics. The results also reveal disparities in serious injury crash rate as well as significant proportions of serious injury crashes involving no seatbelt usage, driving under influence (DUI), unemployed drivers, young drivers, distracted driving, and African American drivers among some regions. The average credit scores, average commute times, and populations of driver postal codes are shown to be significant predictors for risk of severe injury crashes. This approach to traffic crash analysis presented can serve as the foundation for evidence-based policies and also guide the implementation of targeted countermeasures. Copyright © 2017 Elsevier Ltd. All rights reserved.
Effects of osteoporosis on AIS 3+ injury risk in motor-vehicle crashes.
Rupp, Jonathan D; Flannagan, Carol A C; Hoff, Carrie N; Cunningham, Rebecca M
2010-11-01
Older occupants in motor-vehicle crashes are more likely to experience injury than younger occupants. One possible reason for this is that increasing age is associated with increased prevalence of osteoporosis, which decreases bone strength. Crash-injury data were used with Bayes' Theorem to estimate the conditional probability of AIS 3+ skeletal injury given that an occupant is osteoporotic for the injury to the head, spine, thorax, lower extremities, and upper extremities. This requires the conditional probabilities of osteoporosis given AIS 3+ injury for each of the body regions, which were determined from analysis of the Crash Injury Research and Engineering Network database. It also requires information on probability of osteoporosis in the crash-involved population and the probabilities of AIS 3+ skeletal injury to different body regions in crashes. The latter probabilities were obtained from the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) database. The former was obtained by modeling the probability of osteoporosis in the US populations using data from the 2006 National Health Examination Nutrition Survey and applying this model to the estimate of the crash-involved population in NASS-CDS. To attempt to account for the effects of age on injury outcome that are independent of osteoporosis, only data from occupants who were 60 years of age or older were used in all analyses. Results indicate that the only body region that experiences a statistically significant change in fracture injury risk with osteoporosis is the spine, for which osteoporosis increases the risk of AIS 3+ fracture by 3.28 times, or from 0.41% to 1.34% (p<0.0001). This finding suggests that the increase in AIS 3+ injury risk with age for non-spine injuries is likely influenced by factors other than osteoporosis. 2010 Elsevier Ltd. All rights reserved.
Wang, Bo; Hallmark, Shauna; Savolainen, Peter; Dong, Jing
2017-12-01
Prior research has shown the probability of a crash occurring on horizontal curves to be significantly higher than on similar tangent segments, and a disproportionally higher number of curve-related crashes occurred in rural areas. Challenges arise when analyzing the safety of horizontal curves due to imprecision in integrating information as to the temporal and spatial characteristics of each crash with specific curves. The second Strategic Highway Research Program(SHRP 2) conducted a large-scale naturalistic driving study (NDS),which provides a unique opportunity to better understand the contributing factors leading to crash or near-crash events. This study utilizes high-resolution behavioral data from the NDS to identify factors associated with 108 safety critical events (i.e., crashes or near-crashes) on rural two-lane curves. A case-control approach is utilized wherein these events are compared to 216 normal, baseline-driving events. The variables examined in this study include driver demographic characteristics, details of the traffic environment and roadway geometry, as well as driver behaviors such as in-vehicle distractions. Logistic regression models are estimated to discern those factors affecting the likelihood of a driver being crash-involved. These factors include high-risk behaviors, such as speeding and visual distractions, as well as curve design elements and other roadway characteristics such as pavement surface conditions. This paper successfully integrated driver behavior, vehicle characteristics, and roadway environments into the same model. Logistic regression model was found to be an effective way to investigate crash risks using naturalistic driving data. This paper revealed a number of contributing factors to crashes on rural two-lane curves, which has important implications in traffic safety policy and curve geometry design. This paper also discussed limitations and lessons learned from working with the SHRP 2 NDS data. It will benefit future researchers who work with similar type of data. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.
Side Impact Regulatory Trends, Crash Environment and Injury Risk in the USA.
Prasad, Priya; Dalmotas, Dainius; Chouinard, Aline
2015-11-01
Light duty vehicles in the US are designed to meet and exceed regulatory standards, self-imposed industry agreements and safety rating tests conducted by NHTSA and IIHS. The evolution of side impact regulation in the US from 1973 to 2015 is discussed in the paper along with two key industry agreements in 2003 affecting design of restraint systems and structures for side impact protection. A combination of all the above influences shows that vehicles in the US are being designed to more demanding and comprehensive requirements than in any other region of the world. The crash environment in the US related to side impacts was defined based on data in the nationally representative crash database NASS. Crash environment factors, including the distribution of cars, light trucks and vans (LTV's), and medium-to-heavy vehicles (MHV's) in the fleet, and the frequency of their interactions with one another in side impacts, were considered. Other factors like, crash severity in terms of closing velocity between two vehicles involved in crash, gender and age of involved drivers in two-vehicle and single vehicle crashes, were also examined. Injury risks in side impacts to drivers and passengers were determined in various circumstances such as near-side, far-side, and single vehicle crashes as a function of crash severity, in terms of estimated closing speed or lateral delta-V. Also injury risks in different pairs of striking and struck cars and LTV's, were estimated. A logistic regression model for studying injury risks in two vehicle crashes was developed. The risk factors included in the model include case and striking vehicles, consisting of cars, SUV's, vans, and pickup trucks, delta-V, damage extent, occupant proximity to the impact side, age and gender of the occupant, and belt use. Results show that car occupants make up the vast majority of serious-to-fatally injured occupants. Injury rates of car occupants in two-vehicle collision are highest when the car is struck by a pickup and lowest when struck by a car. This was the case across all lateral delta-V ranges. Additionally, near-side injury rates are substantially higher than those in far-side impacts.
Costs of large truck- and bus-involved crashes.
DOT National Transportation Integrated Search
2000-12-01
This study provides comprehensive, economically sophisticated estimates of the costs of highway crashes involving large trucks and buses by severity. Based on the latest data available, the estimated cost of police-reported crashes involving trucks w...
Iraeus, Johan; Lindquist, Mats
2014-01-01
In the widely used National Automotive Sampling System (NASS)-Crashworthiness Data System (CDS) database, summary metrics that describe crashes are available. Crash angle or principal direction of force (PDOF) is estimated by the crash examiner and velocity changes (ΔV) in the x- and y-directions are calculated by the WinSMASH computer program using PDOF and results from rigid barrier crash testing combined with deformations of the crashed car. In recent years, results from event data recorders (EDRs) have been added to the database. The aim of this study is to compare both PDOF and ΔV between EDR measurements and WinSMASH calculations. NASS-CDS inclusion criteria were model-year 2000 through 2010 automobiles, frontal crashes with ΔV higher than 16 km/h, and the pulse entirely recorded in the EDR module. This resulted in 649 cases. The subject vehicles were further examined and characterized with regard to frontal structure engagement (large or small overlap) as well as collision properties of the partner (impact location; front, side, or back) or object. The EDR crash angle was calculated as the angle between the lateral and longitudinal ΔV at the time of peak longitudinal ΔV. This angle was compared to the NASS-CDS investigator's estimated PDOF with regard to structural engagement and the collision partner or object. Multiple linear regression was used to establish adjustment factors on ΔV and crash angle between the results calculated based on EDR recorded data and that estimated in NASS-CDS. According to this study, simulation in the newest WinSMASH version (2008) underestimates EDR ΔV by 11 percent for large overlap crashes and 17 percent for small overlap impacts. The older WinSMASH version, used prior to 2008, underestimated each one of these two groups by an additional 7 percentage points. Another significant variable to enhance the prediction was whether the crash examiner had reported the WinSMASH estimated ΔV as low or high. In this study, none of the collision partner groups was significantly different compared to front-to-front impacts. However, with a larger data set a couple of configurations may very well be significantly different. In this study, the crash angle denoted by PDOF in the NASS database underestimates the crash angle calculated from recent EDR modules by 35 percent. On average the ΔV and crash angle are underestimated in NASS-CDS when analyzing the data based on collision partner/object and structural engagement. The largest difference is found in small overlap crashes and the least difference in collision scenarios similar to barrier tests. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.
Scanlon, John M; Sherony, Rini; Gabler, Hampton C
2017-05-29
Accounting for one fifth of all crashes and one sixth of all fatal crashes in the United States, intersection crashes are among the most frequent and fatal crash modes. Intersection advanced driver assistance systems (I-ADAS) are emerging vehicle-based active safety systems that aim to help drivers safely navigate intersections. The objective of this study was to estimate the number of crashes and number of vehicles with a seriously injured driver (Maximum Abbreviated Injury Scale [MAIS] 3+) that could be prevented or reduced if, for every straight crossing path (SCP) intersection crash, one of the vehicles had been equipped with an I-ADAS. This study retrospectively simulated 448 U.S. SCP crashes as if one of the vehicles had been equipped with I-ADAS. Crashes were reconstructed to determine the path and speeds traveled by the vehicles. Cases were then simulated with I-ADAS. A total of 30 variations of I-ADAS were considered in this study. These variations consisted of 5 separate activation timing thresholds, 3 separate computational latency times, and 2 different I-ADAS response modalities (i.e., a warning or autonomous braking). The likelihood of a serious driver injury was computed for every vehicle in every crash using impact delta-V. The results were then compiled across all crashes in order to estimate system effectiveness. The model predicted that an I-ADAS that delivers an alert to the driver has the potential to prevent 0-23% of SCP crashes and 0-25% of vehicles with a seriously injured driver. Conversely, an I-ADAS that autonomously brakes was found to have the potential to prevent 25-59% of crashes and 38-79% of vehicles with a seriously injured driver. I-ADAS effectiveness is a strong function of design. Increasing computational latency time from 0 to 0.5 s was found to reduce crash and injury prevention estimates by approximately one third. For an I-ADAS that delivers an alert, crash/injury prevention effectiveness was found to be very sensitive to changes in activation timing (warning delivered 1.0 to 3.0 s prior to impact). If autonomous braking was used, system effectiveness was found to largely plateau for activation timings greater than 1.5 s prior to impact. In general, the results of this study suggest that I-ADAS will be 2-3 times more effective if an autonomous braking system is utilized over a warning-based system. This study highlights the potential effectiveness of I-ADAS in the U.S. vehicle fleet, while also indicating the sensitivity of system effectiveness to design specifications. The results of this study should be considered by designers of I-ADAS and evaluators of this technology considering a future I-ADAS safety test.
Ignition Interlock Laws: Effects on Fatal Motor Vehicle Crashes, 1982-2013.
McGinty, Emma E; Tung, Gregory; Shulman-Laniel, Juliana; Hardy, Rose; Rutkow, Lainie; Frattaroli, Shannon; Vernick, Jon S
2017-04-01
Alcohol-involved motor vehicle crashes are a major cause of preventable mortality in the U.S., leading to more than 10,000 fatalities in 2013. Ignition interlocks, or alcohol-sensing devices connected to a vehicle's ignition to prevent it from starting if a driver has a predetermined blood alcohol content (BAC) level, are a promising avenue for preventing alcohol-involved driving. This study sought to assess the effects of laws requiring ignition interlocks for some or all drunk driving offenders on alcohol-involved fatal crashes. A multilevel modeling approach assessed the effects of state interlock laws on alcohol-involved fatal crashes in the U.S. from 1982 to 2013. Monthly data on alcohol-involved crashes in each of the 50 states was collected in 2014 from the National Highway Traffic Safety Administration Fatality Analysis Reporting System. Random-intercept models accounted for between-state variation in alcohol-involved fatal crash rates and autocorrelation of within-state crash rates over time. Analysis was conducted in 2015. State laws requiring interlocks for all drunk driving offenders were associated with a 7% decrease in the rate of BAC >0.08 fatal crashes and an 8% decrease in the rate of BAC ≥0.15 fatal crashes, translating into an estimated 1,250 prevented BAC >0.08 fatal crashes. Laws requiring interlocks for segments of high-risk drunk driving offenders, such as repeat offenders, may reduce alcohol-involved fatal crashes after 2 years of implementation. Ignition interlock laws reduce alcohol-involved fatal crashes. Increasing the spread of interlock laws that are mandatory for all offenders would have significant public health benefit. Copyright © 2016 American Journal of Preventive Medicine. All rights reserved.
A crash-prediction model for multilane roads.
Caliendo, Ciro; Guida, Maurizio; Parisi, Alessandra
2007-07-01
Considerable research has been carried out in recent years to establish relationships between crashes and traffic flow, geometric infrastructure characteristics and environmental factors for two-lane rural roads. Crash-prediction models focused on multilane rural roads, however, have rarely been investigated. In addition, most research has paid but little attention to the safety effects of variables such as stopping sight distance and pavement surface characteristics. Moreover, the statistical approaches have generally included Poisson and Negative Binomial regression models, whilst Negative Multinomial regression model has been used to a lesser extent. Finally, as far as the authors are aware, prediction models involving all the above-mentioned factors have still not been developed in Italy for multilane roads, such as motorways. Thus, in this paper crash-prediction models for a four-lane median-divided Italian motorway were set up on the basis of accident data observed during a 5-year monitoring period extending between 1999 and 2003. The Poisson, Negative Binomial and Negative Multinomial regression models, applied separately to tangents and curves, were used to model the frequency of accident occurrence. Model parameters were estimated by the Maximum Likelihood Method, and the Generalized Likelihood Ratio Test was applied to detect the significant variables to be included in the model equation. Goodness-of-fit was measured by means of both the explained fraction of total variation and the explained fraction of systematic variation. The Cumulative Residuals Method was also used to test the adequacy of a regression model throughout the range of each variable. The candidate set of explanatory variables was: length (L), curvature (1/R), annual average daily traffic (AADT), sight distance (SD), side friction coefficient (SFC), longitudinal slope (LS) and the presence of a junction (J). Separate prediction models for total crashes and for fatal and injury crashes only were considered. For curves it is shown that significant variables are L, 1/R and AADT, whereas for tangents they are L, AADT and junctions. The effect of rain precipitation was analysed on the basis of hourly rainfall data and assumptions about drying time. It is shown that a wet pavement significantly increases the number of crashes. The models developed in this paper for Italian motorways appear to be useful for many applications such as the detection of critical factors, the estimation of accident reduction due to infrastructure and pavement improvement, and the predictions of accidents counts when comparing different design options. Thus this research may represent a point of reference for engineers in adjusting or designing multilane roads.
Yue, Lishengsa; Abdel-Aty, Mohamed; Wu, Yina; Wang, Ling
2018-08-01
The Connected Vehicle (CV) technologies together with other Driving Assistance (DA) technologies are believed to have great effects on traffic operation and safety, and they are expected to impact the future of our cities. However, few research has estimated the exact safety benefits when all vehicles are equipped with these technologies. This paper seeks to fill the gap by using a general crash avoidance effectiveness framework for major CV&DA technologies to make a comprehensive crash reduction estimation. Twenty technologies that were tested in recent studies are summarized and sensitivity analysis is used for estimating their total crash avoidance effectiveness. The results show that crash avoidance effectiveness of CV&DA technology is significantly affected by the vehicle type and the safety estimation methodology. A 70% crash avoidance rate seems to be the highest effectiveness for the CV&DA technologies operating in the real-world environment. Based on the 2005-2008 U.S. GES Crash Records, this research found that the CV&DA technologies could lead to the reduction of light vehicles' crashes and heavy trucks' crashes by at least 32.99% and 40.88%, respectively. The rear-end crashes for both light vehicles and heavy trucks have the most expected crash benefits from the technologies. The paper also studies the effectiveness of Forward Collision Warning technology (FCW) under fog conditions, and the results show that FCW could reduce 35% of the near-crash events under fog conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.
Kraemer, John D
2018-05-18
This study aims to examine potential road crash disparities across relative wealth and location of residence in Kenya by analyzing population-representative Demographic and Health Survey data. Relative wealth was measured by household assets, converted into an index by polychoric principal components analysis. Location and sex-stratified associations between wealth quantiles and crashes were flexibly estimated using fractional polynomial models. Structural equation models were fit to examine whether observed differences may operate through previously identified determinants. In rural areas, crashes were least common for both the poorest men (-5.2 percentage points, 95% CI: -7.3 to -3.2) and women (-1.6 percentage points, 95% CI: -2.9 to -0.4). In urban areas, male crashes were lowest (-3.0 percentage points, 95% CI: -5.2 to -0.8) among the wealthiest, while they peaked in the middle of the female wealth distribution (2.0 percentage points, 95% CI: 0.3-3.8). Male differences operate partially though occupational driving and vehicle ownership. Urban female differences operate partially through household vehicle ownership, but differences for rural women were not explained by modeled determinants. Relative wealth and road crash have opposite associations in rural and urban areas. Especially in rural areas, it is important to mitigate potential unintended effects of economic development.
Older driver crash rates in relation to type and quantity of travel.
Keall, Michael D; Frith, William J
2004-03-01
It is a well-established phenomenon that, notwithstanding their overall good crash record, older drivers have a higher than average rate of involvement in injury crashes when the rate is calculated by dividing crash numbers by distance driven. It has been hypothesised that at least some of this higher crash rate is an artefact of the different nature of driving undertaken by many older drivers. For example, driving in congested urban environments provides more opportunities for collisions than driving the same distance on a motorway. However, there have been few opportunities to investigate this theory, as relevant data are difficult to acquire. High-quality data from the New Zealand Travel Survey (1997/1998) were combined with crash data to enable a statistical model to estimate the risk of driver groups under various driving conditions characterised by the type of road used, time of day, day of week, and season of year. Despite elevated crash risks per distance driven compared with middle-aged drivers for most road types, older drivers were as safe as any other age group when driving on motorways. Accounting for the fragility of older drivers and their passengers in the risk estimates for other road types, older drivers appeared to have daytime risks comparable to 25-year-olds and night-time risks as low as any other age group. The driving patterns of older drivers (in terms of when and where they drive) were estimated to minimize their risks in comparison with the driving patterns of other age groups. These results are of interest to both policy makers and transportation planners working against the background of inevitable increases in the number of older drivers as the population ages.
Modeling crash injury severity by road feature to improve safety.
Penmetsa, Praveena; Pulugurtha, Srinivas S
2018-01-02
The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature. Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity. Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway. The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.
The log-periodic-AR(1)-GARCH(1,1) model for financial crashes
NASA Astrophysics Data System (ADS)
Gazola, L.; Fernandes, C.; Pizzinga, A.; Riera, R.
2008-02-01
This paper intends to meet recent claims for the attainment of more rigorous statistical methodology within the econophysics literature. To this end, we consider an econometric approach to investigate the outcomes of the log-periodic model of price movements, which has been largely used to forecast financial crashes. In order to accomplish reliable statistical inference for unknown parameters, we incorporate an autoregressive dynamic and a conditional heteroskedasticity structure in the error term of the original model, yielding the log-periodic-AR(1)-GARCH(1,1) model. Both the original and the extended models are fitted to financial indices of U. S. market, namely S&P500 and NASDAQ. Our analysis reveal two main points: (i) the log-periodic-AR(1)-GARCH(1,1) model has residuals with better statistical properties and (ii) the estimation of the parameter concerning the time of the financial crash has been improved.
Delay and environmental costs of truck crashes
DOT National Transportation Integrated Search
2013-03-01
This report presents estimates of certain categories of costs of truck- and bus-involved crashes. Crash related costs estimated as part of this study include vehicle delay costs, emission costs, and fuel consumption costs. In addition, this report al...
Crash avoidance potential of four large truck technologies.
Jermakian, Jessica S
2012-11-01
The objective of this paper was to estimate the maximum potential large truck crash reductions in the United States associated with each of four crash avoidance technologies: side view assist, forward collision warning/mitigation, lane departure warning/prevention, and vehicle stability control. Estimates accounted for limitations of current systems. Crash records were extracted from the 2004-08 files of the National Automotive Sampling System General Estimates System (NASS GES) and the Fatality Analysis Reporting System (FARS). Crash descriptors such as location of damage on the vehicle, road characteristics, time of day, and precrash maneuvers were reviewed to determine whether the information or action provided by each technology potentially could have prevented the crash. Of the four technologies, side view assist had the greatest potential for preventing large truck crashes of any severity; the technology is potentially applicable to 39,000 crashes in the United States each year, including 2000 serious and moderate injury crashes and 79 fatal crashes. Vehicle stability control is another promising technology, with the potential to prevent or mitigate up to 31,000 crashes per year including more serious crashes--up to 7000 moderate-to-serious injury crashes and 439 fatal crashes per year. Vehicle stability control could prevent or mitigate up to 20 and 11 percent of moderate-to-serious injury and fatal large truck crashes, respectively. Forward collision warning has the potential to prevent as many as 31,000 crashes per year, including 3000 serious and moderate injury crashes and 115 fatal crashes. Finally, 10,000 large truck crashes annually were relevant to lane departure warning/prevention systems. Of these, 1000 involved serious and moderate injuries and 247 involved fatal injuries. There is great potential effectiveness for truck-based crash avoidance systems. However, it is yet to be determined how drivers will interact with the systems. Actual effectiveness of crash avoidance systems will not be known until sufficient real-world experience has been gained. Copyright © 2012 Elsevier Ltd. All rights reserved.
Spatial regression analysis of traffic crashes in Seoul.
Rhee, Kyoung-Ah; Kim, Joon-Ki; Lee, Young-ihn; Ulfarsson, Gudmundur F
2016-06-01
Traffic crashes can be spatially correlated events and the analysis of the distribution of traffic crash frequency requires evaluation of parameters that reflect spatial properties and correlation. Typically this spatial aspect of crash data is not used in everyday practice by planning agencies and this contributes to a gap between research and practice. A database of traffic crashes in Seoul, Korea, in 2010 was developed at the traffic analysis zone (TAZ) level with a number of GIS developed spatial variables. Practical spatial models using available software were estimated. The spatial error model was determined to be better than the spatial lag model and an ordinary least squares baseline regression. A geographically weighted regression model provided useful insights about localization of effects. The results found that an increased length of roads with speed limit below 30 km/h and a higher ratio of residents below age of 15 were correlated with lower traffic crash frequency, while a higher ratio of residents who moved to the TAZ, more vehicle-kilometers traveled, and a greater number of access points with speed limit difference between side roads and mainline above 30 km/h all increased the number of traffic crashes. This suggests, for example, that better control or design for merging lower speed roads with higher speed roads is important. A key result is that the length of bus-only center lanes had the largest effect on increasing traffic crashes. This is important as bus-only center lanes with bus stop islands have been increasingly used to improve transit times. Hence the potential negative safety impacts of such systems need to be studied further and mitigated through improved design of pedestrian access to center bus stop islands. Copyright © 2016 Elsevier Ltd. All rights reserved.
Abdel-Aty, Mohamed; Chundi, Sai Srinivas; Lee, Chris
2007-01-01
There is a growing concern with the safety of school-aged children. This study identifies the locations of pedestrian/bicyclist crashes involving school-aged children and examines the conditions when these crashes are more likely to occur. The 5-year records of crashes in Orange County, Florida where school-aged children were involved were used. The spatial distribution of these crashes was investigated using the Geographic Information Systems (GIS) and the likelihoods of crash occurrence under different conditions were estimated using log-linear models. A majority of school-aged children crashes occurred in the areas near schools. Although elementary school children were generally very involved, middle and high school children were more involved in crashes, particularly on high-speed multi-lane roadways. Driver's age, gender, and alcohol use, pedestrian's/bicyclist's age, number of lanes, median type, speed limits, and speed ratio were also found to be correlated with the frequency of crashes. The result confirms that school-aged children are exposed to high crash risk near schools. High crash involvement of middle and high school children reflects that middle and high schools tend to be located near multi-lane high-speed roads. The pedestrian's/bicyclist's demographic factors and geometric characteristics of the roads adjacent to schools associated with school children's crash involvement are of interest to school districts.
Identifying work-related motor vehicle crashes in multiple databases.
Thomas, Andrea M; Thygerson, Steven M; Merrill, Ray M; Cook, Lawrence J
2012-01-01
To compare and estimate the magnitude of work-related motor vehicle crashes in Utah using 2 probabilistically linked statewide databases. Data from 2006 and 2007 motor vehicle crash and hospital databases were joined through probabilistic linkage. Summary statistics and capture-recapture were used to describe occupants injured in work-related motor vehicle crashes and estimate the size of this population. There were 1597 occupants in the motor vehicle crash database and 1673 patients in the hospital database identified as being in a work-related motor vehicle crash. We identified 1443 occupants with at least one record from either the motor vehicle crash or hospital database indicating work-relatedness that linked to any record in the opposing database. We found that 38.7 percent of occupants injured in work-related motor vehicle crashes identified in the motor vehicle crash database did not have a primary payer code of workers' compensation in the hospital database and 40.0 percent of patients injured in work-related motor vehicle crashes identified in the hospital database did not meet our definition of a work-related motor vehicle crash in the motor vehicle crash database. Depending on how occupants injured in work-related motor crashes are identified, we estimate the population to be between 1852 and 8492 in Utah for the years 2006 and 2007. Research on single databases may lead to biased interpretations of work-related motor vehicle crashes. Combining 2 population based databases may still result in an underestimate of the magnitude of work-related motor vehicle crashes. Improved coding of work-related incidents is needed in current databases.
Societal costs of traffic crashes and crime in Michigan : 2011 update.
DOT National Transportation Integrated Search
2011-06-01
"Cost estimates, including both monetary and nonmonetary quality-of-life costs specific to Michigan, were : estimated for overall traffic crashes and index crimes by experts in the field of economics of traffic crashes : and crimes. These cost estima...
Unit costs of medium and heavy truck crashes.
DOT National Transportation Integrated Search
2008-03-01
This study provides the latest estimates of unit costs for highway crashes involving medium/heavy trucks by severity. Based on the latest data available, the estimated cost of police-reported crashes involving trucks with a gross weight rating of mor...
Cummings, P
2002-01-01
Objective: Estimates of any protective effect of seat belts could be exaggerated if some crash survivors falsely claimed to police that they were belted in order to avoid a fine. The aim of this study was to determine whether estimates of seat belt effectiveness differed when based on belt use as recorded by the police and belt use determined by trained crash investigators. Design: Matched cohort study. Setting: United States. Subjects: Adult driver-passenger pairs in the same vehicle with at least one death (n=1689) sampled from crashes during 1988–2000; data from the National Accident Sampling System Crashworthiness Data System. Main outcome measure: Risk ratio for death among belted occupants compared with those not belted. Results: Trained investigators determined post-crash seat belt use by vehicle inspections for 92% of the occupants, confidential interviews with survivors for 5%, and medical or autopsy reports for 3%. Using this information, the adjusted risk ratio for belted persons was 0.36 (95% confidence interval 0.29 to 0.46). The risk ratio was also 0.36 using police reported belt use for the same crashes. Conclusions: Estimates of seat belt effects based upon police data were not substantially different from estimates which used data obtained by trained crash investigators who were not police officers. These results were from vehicles in which at least one front seat occupant died; these findings may not apply to estimates which use data from crashes without a death. PMID:12460976
Pruchnicki, Shawn A; Wu, Lora J; Belenky, Gregory
2011-05-01
On 27 August 2006 at 0606 eastern daylight time (EDT) at Bluegrass Airport in Lexington, KY (LEX), the flight crew of Comair Flight 5191 inadvertently attempted to take off from a general aviation runway too short for their aircraft. The aircraft crashed killing 49 of the 50 people on board. To better understand this accident and to aid in preventing similar accidents, we applied mathematical modeling predicting fatigue-related degradation in performance for the Air Traffic Controller on-duty at the time of the crash. To provide the necessary input to the model, we attempted to estimate circadian phase and sleep/wake histories for the Captain, First Officer, and Air Traffic Controller. We were able to estimate with confidence the circadian phase for each. We were able to estimate with confidence the sleep/wake history for the Air Traffic Controller, but unable to do this for the Captain and First Officer. Using the sleep/wake history estimates for the Air Traffic Controller as input, the mathematical modeling predicted moderate fatigue-related performance degradation at the time of the crash. This prediction was supported by the presence of what appeared to be fatigue-related behaviors in the Air Traffic Controller during the 30 min prior to and in the minutes after the crash. Our modeling results do not definitively establish fatigue in the Air Traffic Controller as a cause of the accident, rather they suggest that had he been less fatigued he might have detected Comair Flight 5191's lining up on the wrong runway. We were not able to perform a similar analysis for the Captain and First Officer because we were not able to estimate with confidence their sleep/wake histories. Our estimates of sleep/wake history and circadian rhythm phase for the Air Traffic Controller might generalize to other air traffic controllers and to flight crew operating in the early morning hours at LEX. Relative to other times of day, the modeling results suggest an elevated risk of fatigue-related error, incident, or accident in the early morning due to truncated sleep from the early start and adverse circadian phase from the time of day. This in turn suggests that fatigue mitigation targeted to early morning starts might reduce fatigue risk. In summary, this study suggests that mathematical models predicting performance from sleep/wake history and circadian phase are (1) useful in retrospective accident analysis provided reliable sleep/wake histories are available for the accident personnel and, (2) useful in prospective fatigue-risk identification, mitigation, and accident prevention. Copyright © 2010 Elsevier Ltd. All rights reserved.
DOT National Transportation Integrated Search
2014-04-01
Through the analysis of national crash databases from the National Highway Traffic Safety Administration, pre-crash scenarios are identified, prioritized, and described for the development of objective tests for pedestrian crash avoidance/mitigation ...
NASA Astrophysics Data System (ADS)
Seyrich, Maximilian; Sornette, Didier
2016-04-01
We present a plausible micro-founded model for the previously postulated power law finite time singular form of the crash hazard rate in the Johansen-Ledoit-Sornette (JLS) model of rational expectation bubbles. The model is based on a percolation picture of the network of traders and the concept that clusters of connected traders share the same opinion. The key ingredient is the notion that a shift of position from buyer to seller of a sufficiently large group of traders can trigger a crash. This provides a formula to estimate the crash hazard rate by summation over percolation clusters above a minimum size of a power sa (with a>1) of the cluster sizes s, similarly to a generalized percolation susceptibility. The power sa of cluster sizes emerges from the super-linear dependence of group activity as a function of group size, previously documented in the literature. The crash hazard rate exhibits explosive finite time singular behaviors when the control parameter (fraction of occupied sites, or density of traders in the network) approaches the percolation threshold pc. Realistic dynamics are generated by modeling the density of traders on the percolation network by an Ornstein-Uhlenbeck process, whose memory controls the spontaneous excursion of the control parameter close to the critical region of bubble formation. Our numerical simulations recover the main stylized properties of the JLS model with intermittent explosive super-exponential bubbles interrupted by crashes.
Harland, Karisa K; Greenan, Mitchell; Ramirez, Marizen
2014-09-01
Although approximately one-third of agricultural equipment-related crashes occur near town, these crashes are thought to be a rural problem. This analysis examines differences between agricultural equipment-related crashes by their urban-rural distribution and distance from a town. Agricultural equipment crashes were collected from nine Midwest Departments of Transportation (2005-2008). Crash zip code was assigned as urban or rural (large, small and isolated) using Rural-Urban Commuting Areas. Crash proximity to a town was estimated with ArcGIS. Multivariable logistic regression was used to estimate the odds of crashing in an urban versus rural zip codes and across rural gradients. ANOVA analysis estimated mean distance (miles) from a crash site to a town. Over four years, 4444 crashes involved agricultural equipment. About 30% of crashes occurred in urban zip codes. Urban crashes were more likely to be non-collisions (aOR=1.69[1.24-2.30]), involve ≥2 vehicles (2 vehicles: aOR=1.58[1.14-2.20], 3+ vehicles: aOR=1.68[0.98-2.88]), occur in a town (aOR=2.06[1.73-2.45]) and within one mile of a town (aOR=1.65[1.40-1.95]) than rural crashes. The proportion of crashes within a town differed significantly across rural gradients (P<0.0001). Small rural crashes, compared to isolated rural crashes, were 1.98 (95%CI[1.28-3.06]) times more likely to be non-collisions. The distance from the crash to town differed significantly by the urban-rural distribution (P<0.0001). Crashes with agricultural equipment are unexpectedly common in urban areas and near towns and cities. Education among all roadway users, increased visibility of agricultural equipment and the development of complete rural roads are needed to increase road safety and prevent agricultural equipment-related crashes. Copyright © 2014 Elsevier Ltd. All rights reserved.
Spatiotemporal and random parameter panel data models of traffic crash fatalities in Vietnam.
Truong, Long T; Kieu, Le-Minh; Vu, Tuan A
2016-09-01
This paper investigates factors associated with traffic crash fatalities in 63 provinces of Vietnam during the period from 2012 to 2014. Random effect negative binomial (RENB) and random parameter negative binomial (RPNB) panel data models are adopted to consider spatial heterogeneity across provinces. In addition, a spatiotemporal model with conditional autoregressive priors (ST-CAR) is utilised to account for spatiotemporal autocorrelation in the data. The statistical comparison indicates the ST-CAR model outperforms the RENB and RPNB models. Estimation results provide several significant findings. For example, traffic crash fatalities tend to be higher in provinces with greater numbers of level crossings. Passenger distance travelled and road lengths are also positively associated with fatalities. However, hospital densities are negatively associated with fatalities. The safety impact of the national highway 1A, the main transport corridor of the country, is also highlighted. Copyright © 2016 Elsevier Ltd. All rights reserved.
Bahouth, George; Digges, Kennerly; Schulman, Carl
2012-01-01
This paper presents methods to estimate crash injury risk based on crash characteristics captured by some passenger vehicles equipped with Advanced Automatic Crash Notification technology. The resulting injury risk estimates could be used within an algorithm to optimize rescue care. Regression analysis was applied to the National Automotive Sampling System / Crashworthiness Data System (NASS/CDS) to determine how variations in a specific injury risk threshold would influence the accuracy of predicting crashes with serious injuries. The recommended thresholds for classifying crashes with severe injuries are 0.10 for frontal crashes and 0.05 for side crashes. The regression analysis of NASS/CDS indicates that these thresholds will provide sensitivity above 0.67 while maintaining a positive predictive value in the range of 0.20. PMID:23169132
Revised costs of large truck-and bus-involved crashes.
DOT National Transportation Integrated Search
2002-11-01
This study provides the latest estimates of the costs of highway crashes involving large trucks and buses by severity. Based on the latest data available, the estimated cost of police-reported crashes involving trucks with a gross weight rating of mo...
Xie, Meiquan; Cheng, Wen; Gill, Gurdiljot Singh; Zhou, Jiao; Jia, Xudong; Choi, Simon
2018-02-17
Most of the extensive research dedicated to identifying the influential factors of hit-and-run (HR) crashes has utilized typical maximum likelihood estimation binary logit models, and none have employed real-time traffic data. To fill this gap, this study focused on investigating factors contributing to HR crashes, as well as the severity levels of HR. This study analyzed 4-year crash and real-time loop detector data by employing hierarchical Bayesian models with random effects within a sequential logit structure. In addition to evaluation of the impact of random effects on model fitness and complexity, the prediction capability of the models was examined. Stepwise incremental sensitivity and specificity were calculated and receiver operating characteristic (ROC) curves were utilized to graphically illustrate the predictive performance of the model. Among the real-time flow variables, the average occupancy and speed from the upstream detector were observed to be positively correlated with HR crash possibility. The average upstream speed and speed difference between upstream and downstream speeds were correlated with the occurrence of severe HR crashes. In addition to real-time factors, other variables found influential for HR and severe HR crashes were length of segment, adverse weather conditions, dark lighting conditions with malfunctioning street lights, driving under the influence of alcohol, width of inner shoulder, and nighttime. This study suggests the potential traffic conditions of HR and severe HR occurrence, which refer to relatively congested upstream traffic conditions with high upstream speed and significant speed deviations on long segments. The above findings suggest that traffic enforcement should be directed toward mitigating risky driving under the aforementioned traffic conditions. Moreover, enforcement agencies may employ alcohol checkpoints to counter driving under the influence (DUI) at night. With regard to engineering improvements, wider inner shoulders may be constructed to potentially reduce HR cases and street lights should be installed and maintained in working condition to make roads less prone to such crashes.
Burst fractures of the lumbar spine in frontal crashes.
Kaufman, Robert P; Ching, Randal P; Willis, Margaret M; Mack, Christopher D; Gross, Joel A; Bulger, Eileen M
2013-10-01
In the United States, major compression and burst type fractures (>20% height loss) of the lumbar spine occur as a result of motor vehicle crashes, despite the improvements in restraint technologies. Lumbar burst fractures typically require an axial compressive load and have been known to occur during a non-horizontal crash event that involve high vertical components of loading. Recently these fracture patterns have also been observed in pure horizontal frontal crashes. This study sought to examine the contributing factors that would induce an axial compressive force to the lumbar spine in frontal motor vehicle crashes. We searched the National Automotive Sampling System (NASS, 1993-2011) and Crash Injury Research and Engineering Network (CIREN, 1996-2012) databases to identify all patients with major compression lumbar spine (MCLS) fractures and then specifically examined those involved in frontal crashes. National trends were assessed based on weighted NASS estimates. Using a case-control study design, NASS and CIREN cases were utilized and a conditional logistic regression was performed to assess driver and vehicle characteristics. CIREN case studies and biomechanical data were used to illustrate the kinematics and define the mechanism of injury. During the study period 132 NASS cases involved major compression lumbar spine fractures for all crash directions. Nationally weighted, this accounted for 800 cases annually with 44% of these in horizontal frontal crashes. The proportion of frontal crashes resulting in MCLS fractures was 2.5 times greater in late model vehicles (since 2000) as compared to 1990s models. Belted occupants in frontal crashes had a 5 times greater odds of a MCLS fracture than those not belted, and an increase in age also greatly increased the odds. In CIREN, 19 cases were isolated as horizontal frontal crashes and 12 of these involved a major compression lumbar burst fracture primarily at L1. All were belted and almost all occurred in late model vehicles with belt pretensioners and buckets seats. Major compression burst fractures of the lumbar spine in frontal crashes were induced via a dynamic axial force transmitted to the pelvis/buttocks into the seat cushion/pan involving belted occupants in late model vehicles with increasing age as a significant factor. Copyright © 2013 Elsevier Ltd. All rights reserved.
Multi-level hot zone identification for pedestrian safety.
Lee, Jaeyoung; Abdel-Aty, Mohamed; Choi, Keechoo; Huang, Helai
2015-03-01
According to the National Highway Traffic Safety Administration (NHTSA), while fatalities from traffic crashes have decreased, the proportion of pedestrian fatalities has steadily increased from 11% to 14% over the past decade. This study aims at identifying two zonal levels factors. The first is to identify hot zones at which pedestrian crashes occurs, while the second are zones where crash-involved pedestrians came from. Bayesian Poisson lognormal simultaneous equation spatial error model (BPLSESEM) was estimated and revealed significant factors for the two target variables. Then, PSIs (potential for safety improvements) were computed using the model. Subsequently, a novel hot zone identification method was suggested to combine both hot zones from where vulnerable pedestrians originated with hot zones where many pedestrian crashes occur. For the former zones, targeted safety education and awareness campaigns can be provided as countermeasures whereas area-wide engineering treatments and enforcement may be effective safety treatments for the latter ones. Thus, it is expected that practitioners are able to suggest appropriate safety treatments for pedestrian crashes using the method and results from this study. Copyright © 2015 Elsevier Ltd. All rights reserved.
Llopis-Castelló, David; Camacho-Torregrosa, Francisco Javier; García, Alfredo
2018-05-26
One of every four road fatalities occurs on horizontal curves of two-lane rural roads. To this regard, many studies have been undertaken to analyze the crash risk on this road element. Most of them were based on the concept of geometric design consistency, which can be defined as how drivers' expectancies and road behavior relate. However, none of these studies included a variable which represents and estimates drivers' expectancies. This research presents a new local consistency model based on the Inertial Consistency Index (ICI). This consistency parameter is defined as the difference between the inertial operating speed, which represents drivers' expectations, and the operating speed, which represents road behavior. The inertial operating speed was defined as the weighted average operating speed of the preceding road section. In this way, different lengths, periods of time, and weighting distributions were studied to identify how the inertial operating speed should be calculated. As a result, drivers' expectancies should be estimated considering 15 s along the segment and a linear weighting distribution. This was consistent with drivers' expectancies acquirement process, which is closely related to Short-Term Memory. A Safety Performance Function was proposed to predict the number of crashes on a horizontal curve and consistency thresholds were defined based on the ICI. To this regard, the crash rate increased as the ICI increased. Finally, the proposed consistency model was compared with previous models. As a conclusion, the new Inertial Consistency Index allowed a more accurate estimation of the number of crashes and a better assessment of the consistency level on horizontal curves. Therefore, highway engineers have a new tool to identify where road crashes are more likely to occur during the design stage of both new two-lane rural roads and improvements of existing highways. Copyright © 2018 Elsevier Ltd. All rights reserved.
Evaluating the risk from depleted uranium after the Boeing 747-258F crash in Amsterdam, 1992.
Uijt de Haag, P A; Smetsers, R C; Witlox, H W; Krüs, H W; Eisenga, A H
2000-08-28
On 4 October 1992, a large cargo plane crashed into an apartment building in the Bijlmermeer quarter of Amsterdam. In the years following the accident, an increasing number of people started reporting health complaints, which they attributed to exposure to dangerous substances after the crash. Since the aircraft had been carrying depleted uranium as counterbalance weights and about 150 kg uranium had been found missing after clearance of the crash site, exposure to uranium oxide particles was pointed out as the possible cause of their health complaints. Six years after the accident, a risk analysis was therefore carried out to investigate whether the health complaints could be attributed to exposure to uranium oxide set free during the accident. The scientific challenge was to come up with reliable results, knowing that - considering the late date - virtually no data were available to validate any calculated result. The source term of uranium was estimated using both generic and specific data. Various dispersion models were applied in combination with the local setting and the meteorological conditions at the time of the accident to estimate the exposure of bystanders during the fire caused by the crash. Emphasis was given to analysing the input parameters, inter-comparing the various models and comparing model results with the scarce information available. Uranium oxide formed in the fire has a low solubility, making the chemical toxicity to humans less important than the radiotoxicity. Best-estimate results indicated that bystanders may have been exposed to a radiation dose of less than 1 microSv, whereas a worst-case approach indicated an upper limit of less than 1 mSv. This value is considerably less than the radiation dose for which acute effects are to be expected. It is therefore considered to be improbable that the missing uranium had indeed led to the health complaints reported.
Bayesian spatiotemporal crash frequency models with mixture components for space-time interactions.
Cheng, Wen; Gill, Gurdiljot Singh; Zhang, Yongping; Cao, Zhong
2018-03-01
The traffic safety research has developed spatiotemporal models to explore the variations in the spatial pattern of crash risk over time. Many studies observed notable benefits associated with the inclusion of spatial and temporal correlation and their interactions. However, the safety literature lacks sufficient research for the comparison of different temporal treatments and their interaction with spatial component. This study developed four spatiotemporal models with varying complexity due to the different temporal treatments such as (I) linear time trend; (II) quadratic time trend; (III) Autoregressive-1 (AR-1); and (IV) time adjacency. Moreover, the study introduced a flexible two-component mixture for the space-time interaction which allows greater flexibility compared to the traditional linear space-time interaction. The mixture component allows the accommodation of global space-time interaction as well as the departures from the overall spatial and temporal risk patterns. This study performed a comprehensive assessment of mixture models based on the diverse criteria pertaining to goodness-of-fit, cross-validation and evaluation based on in-sample data for predictive accuracy of crash estimates. The assessment of model performance in terms of goodness-of-fit clearly established the superiority of the time-adjacency specification which was evidently more complex due to the addition of information borrowed from neighboring years, but this addition of parameters allowed significant advantage at posterior deviance which subsequently benefited overall fit to crash data. The Base models were also developed to study the comparison between the proposed mixture and traditional space-time components for each temporal model. The mixture models consistently outperformed the corresponding Base models due to the advantages of much lower deviance. For cross-validation comparison of predictive accuracy, linear time trend model was adjudged the best as it recorded the highest value of log pseudo marginal likelihood (LPML). Four other evaluation criteria were considered for typical validation using the same data for model development. Under each criterion, observed crash counts were compared with three types of data containing Bayesian estimated, normal predicted, and model replicated ones. The linear model again performed the best in most scenarios except one case of using model replicated data and two cases involving prediction without including random effects. These phenomena indicated the mediocre performance of linear trend when random effects were excluded for evaluation. This might be due to the flexible mixture space-time interaction which can efficiently absorb the residual variability escaping from the predictable part of the model. The comparison of Base and mixture models in terms of prediction accuracy further bolstered the superiority of the mixture models as the mixture ones generated more precise estimated crash counts across all four models, suggesting that the advantages associated with mixture component at model fit were transferable to prediction accuracy. Finally, the residual analysis demonstrated the consistently superior performance of random effect models which validates the importance of incorporating the correlation structures to account for unobserved heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.
Zaloshnja, Eduard; Miller, Ted; Council, Forrest; Persaud, Bhagwant
2004-01-01
This paper presents estimates for both the economic and comprehensive costs per crash for three police-coded severity groupings within 16 selected crash types and within two speed limit categories (
Zaloshnja, Eduard; Miller, Ted; Council, Forrest; Persaud, Bhagwant
2004-01-01
This paper presents estimates for both the economic and comprehensive costs per crash for three police-coded severity groupings within 16 selected crash types and within two speed limit categories (<=45 and >=50 mph). The economic costs are hard dollar costs. The comprehensive costs include economic costs and quality of life losses. We merged previously developed costs per victim keyed on the Abbreviated Injury Scale (AIS) into US crash data files that scored injuries in both the AIS and police-coded severity scales to produce per crash estimates. The most costly crashes were non-intersection fatal/disabling injury crashes on a road with a speed limit of 50 miles per hour or higher where multiple vehicles crashed head-on or a single vehicle struck a human (over 1.69 and $1.16 million per crash, respectively). The annual cost of police-reported run-off-road collisions, which include both rollovers and object impacts, represented 34% of total costs. PMID:15319129
Evaluation of the Scottsdale Loop 101 automated speed enforcement demonstration program.
Shin, Kangwon; Washington, Simon P; van Schalkwyk, Ida
2009-05-01
Speeding is recognized as a major contributing factor in traffic crashes. In order to reduce speed-related crashes, the city of Scottsdale, Arizona implemented the first fixed-camera photo speed enforcement program (SEP) on a limited access freeway in the US. The 9-month demonstration program spanning from January 2006 to October 2006 was implemented on a 6.5 mile urban freeway segment of Arizona State Route 101 running through Scottsdale. This paper presents the results of a comprehensive analysis of the impact of the SEP on speeding behavior, crashes, and the economic impact of crashes. The impact on speeding behavior was estimated using generalized least square estimation, in which the observed speeds and the speeding frequencies during the program period were compared to those during other periods. The impact of the SEP on crashes was estimated using 3 evaluation methods: a before-and-after (BA) analysis using a comparison group, a BA analysis with traffic flow correction, and an empirical Bayes BA analysis with time-variant safety. The analysis results reveal that speeding detection frequencies (speeds> or =76 mph) increased by a factor of 10.5 after the SEP was (temporarily) terminated. Average speeds in the enforcement zone were reduced by about 9 mph when the SEP was implemented, after accounting for the influence of traffic flow. All crash types were reduced except rear-end crashes, although the estimated magnitude of impact varies across estimation methods (and their corresponding assumptions). When considering Arizona-specific crash related injury costs, the SEP is estimated to yield about $17 million in annual safety benefits.
Bakhtiyari, Mahmood; Delpisheh, Ali; Monfared, Ayad Bahadori; Kazemi-Galougahi, Mohammad Hassan; Mehmandar, Mohammad Reza; Riahi, Mohammad; Salehi, Masoud; Mansournia, Mohammad Ali
2015-01-01
Traffic crashes are multifactorial events caused by human factors, technical issues, and environmental conditions. The present study aimed to determine the role of human factors in traffic crashes in Iran using the proportional odds regression model. The database of all traffic crashes in Iran in 2010 (n = 592, 168) registered through the "COM.114" police forms was investigated. Human risk factors leading to traffic crashes were determined and the odds ratio (OR) of each risk factor was estimated using an ordinal regression model and adjusted for potential confounding factors such as age, gender, and lighting status within and outside of cities. The drivers' mean age ± standard deviation was 34.1 ± 14.0 years. The most prevalent risk factors leading to death within cities were disregarding traffic rules and regulations (45%), driver rushing (31%), and alcohol consumption (12.3%). Using the proportional odds regression model, alcohol consumption was the most significant human risk factor in traffic crashes within cities (OR = 6.5, 95% confidence interval [CI], 4.88-8.65) and outside of cities (OR = 1.73, 95% CI, 1.22-3.29). Public health strategies and preventive policies should be focused on more common human risk factors such as disregarding traffic rules and regulations, drivers' rushing, and alcohol consumption due to their greater population attributable fraction and more intuitive impacts on society.
Anderson, R W G; Searson, D J
2015-02-01
A novel application of age-period-cohort methods are used to explain changes in vehicle based crash rates in New South Wales, Australia over the period 2003-2010. Models are developed using vehicle age, crash period and vehicle cohort to explain changes in the rate of single vehicle driver fatalities and injuries in vehicles less than 13 years of age. Large declines in risk are associated with vehicle cohorts built after about 1996. The decline in risk appears to have accelerated to 12 percent per vehicle cohort year for cohorts since 2004. Within each cohort, the risk of crashing appears to be a minimum at two years of age and increases as the vehicle ages beyond this. Period effects (i.e., other road safety measures) between 2003 and 2010 appear to have contributed to declines of up to about two percent per annum to the driver-fatality single vehicle crash rate, and possibly only negligible improvements to the driver-injury single vehicle crash rate. Vehicle improvements appear to have been responsible for a decline in per-vehicle crash risk of at least three percent per calendar year for both severity levels over the same period. Given the decline in risk associated with more recent vehicle cohorts and the dynamics of fleet turnover, continued declines in per-vehicle crash risk over coming years are almost certain. Copyright © 2014. Published by Elsevier Ltd.
Analysis of passenger-car crash injury severity in different work zone configurations.
Osman, Mohamed; Paleti, Rajesh; Mishra, Sabyasachee
2018-02-01
Work zone safety remains a priority to the Federal Highway Administration, State Highway Departments, highway engineers, and the traveling public. Work zones create a hospitable environment for crashes; an issue that gained tremendous share of attention in recent years. Therefore, every effort should be sought out to reduce the injury severity of crashes in work zones. In this paper we attempt to investigate factors contributing to the injury severity of passenger-car crashes in different work zone configurations. Considering the discrete ordinal nature of injury severity categories, a Mixed Generalized Ordered Response Probit (MGORP) modeling framework was developed. The model estimation was undertaken by compiling a database consisting of 10 years of crashes that involved at least one passenger car, and occurred in a work zone. Revealing the underlying factors contributing to injury severity levels for different work zone configurations will allow for distinguishing mitigation methods for higher severity outcomes that best suit each of the depicted work zone layouts. This can be accomplished through the implementation of specific safety measures based on the specific configuration of a work zone as a potential crash location. Elasticity analysis suggests that partial control of access, roadways classified as rural, crashes during evening times, crashes during weekends, and curved roadways are key factors that increase the likelihood of severe outcomes. Also, the effects of several covariates were found to vary across the different work zone configurations. Copyright © 2017 Elsevier Ltd. All rights reserved.
Iwamoto, Masami; Nakahira, Yuko; Kimpara, Hideyuki; Sugiyama, Takahiko; Min, Kyuengbo
2012-10-01
A few reports suggest differences in injury outcomes between cadaver tests and real-world accidents under almost similar conditions. This study hypothesized that muscle activity could primarily cause the differences, and then developed a human body finite element (FE) model with individual muscles. Each muscle was modeled as a hybrid model of bar elements with active properties and solid elements with passive properties. The model without muscle activation was firstly validated against five series of cadaver test data on impact responses in the anterior-posterior direction. The model with muscle activation levels estimated based on electromyography (EMG) data was secondly validated against four series of volunteer test data on bracing effects for stiffness and thickness of an upper arm muscle, and braced driver's responses under a static environment and a brake deceleration. A muscle controller using reinforcement learning (RL), which is a mathematical model of learning process in the basal ganglia associated with human postural controls, were newly proposed to estimate muscle activity in various occupant conditions including inattentive and attentive conditions. Control of individual muscles predicted by RL reproduced more human like head-neck motions than conventional control of two groups of agonist and antagonist muscles. The model and the controller demonstrated that head-neck motions of an occupant under an impact deceleration of frontal crash were different in between a bracing condition with maximal braking force and an occupant condition predicted by RL. The model and the controller have the potential to investigate muscular effects in various occupant conditions during frontal crashes.
Omitted variable bias in crash reduction factors.
DOT National Transportation Integrated Search
2015-09-01
Transportation planners and traffic engineers are increasingly turning to crash reduction factors to evaluate changes in road : geometric and design features in order to reduce crashes. Crash reduction factors are typically estimated based on segment...
Harland, Karisa K; Carney, Cher; McGehee, Daniel
2016-07-03
The objective of this study was to estimate the prevalence and odds of fleet driver errors and potentially distracting behaviors just prior to rear-end versus angle crashes. Analysis of naturalistic driving videos among fleet services drivers for errors and potentially distracting behaviors occurring in the 6 s before crash impact. Categorical variables were examined using the Pearson's chi-square test, and continuous variables, such as eyes-off-road time, were compared using the Student's t-test. Multivariable logistic regression was used to estimate the odds of a driver error or potentially distracting behavior being present in the seconds before rear-end versus angle crashes. Of the 229 crashes analyzed, 101 (44%) were rear-end and 128 (56%) were angle crashes. Driver age, gender, and presence of passengers did not differ significantly by crash type. Over 95% of rear-end crashes involved inadequate surveillance compared to only 52% of angle crashes (P < .0001). Almost 65% of rear-end crashes involved a potentially distracting driver behavior, whereas less than 40% of angle crashes involved these behaviors (P < .01). On average, drivers spent 4.4 s with their eyes off the road while operating or manipulating their cell phone. Drivers in rear-end crashes were at 3.06 (95% confidence interval [CI], 1.73-5.44) times adjusted higher odds of being potentially distracted than those in angle crashes. Fleet driver driving errors and potentially distracting behaviors are frequent. This analysis provides data to inform safe driving interventions for fleet services drivers. Further research is needed in effective interventions to reduce the likelihood of drivers' distracting behaviors and errors that may potentially reducing crashes.
Bayesian road safety analysis: incorporation of past evidence and effect of hyper-prior choice.
Miranda-Moreno, Luis F; Heydari, Shahram; Lord, Dominique; Fu, Liping
2013-09-01
This paper aims to address two related issues when applying hierarchical Bayesian models for road safety analysis, namely: (a) how to incorporate available information from previous studies or past experiences in the (hyper) prior distributions for model parameters and (b) what are the potential benefits of incorporating past evidence on the results of a road safety analysis when working with scarce accident data (i.e., when calibrating models with crash datasets characterized by a very low average number of accidents and a small number of sites). A simulation framework was developed to evaluate the performance of alternative hyper-priors including informative and non-informative Gamma, Pareto, as well as Uniform distributions. Based on this simulation framework, different data scenarios (i.e., number of observations and years of data) were defined and tested using crash data collected at 3-legged rural intersections in California and crash data collected for rural 4-lane highway segments in Texas. This study shows how the accuracy of model parameter estimates (inverse dispersion parameter) is considerably improved when incorporating past evidence, in particular when working with the small number of observations and crash data with low mean. The results also illustrates that when the sample size (more than 100 sites) and the number of years of crash data is relatively large, neither the incorporation of past experience nor the choice of the hyper-prior distribution may affect the final results of a traffic safety analysis. As a potential solution to the problem of low sample mean and small sample size, this paper suggests some practical guidance on how to incorporate past evidence into informative hyper-priors. By combining evidence from past studies and data available, the model parameter estimates can significantly be improved. The effect of prior choice seems to be less important on the hotspot identification. The results show the benefits of incorporating prior information when working with limited crash data in road safety studies. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.
Florida's weakened motorcycle helmet law: effects on death rates in motorcycle crashes.
Kyrychenko, Sergey Y; McCartt, Anne T
2006-03-01
Effective July 1, 2000, Florida's universal helmet law was amended to exclude riders ages 21 and older with insurance coverage providing at least 10,000 US dollars in medical benefits for injuries sustained in a motorcycle crash. Observed helmet use in Florida was reported to have declined from nearly 100% in 1998, before the law change, to 53% after. This study examined the effects of the law change on the likelihood of death, given involvement in a motorcycle crash. Rates of motorcyclist deaths per crash involvement in Florida for 2001-2002 (after the law change) were compared with those for 1998-1999 (before the law change). Before/after death rate ratios (95% CIs) were examined, and logistic regression models estimated the effect of the helmet law change on the odds of death in a crash, while controlling for rider gender, age, and seating position, and number of vehicles. The motorcyclist death rate increased significantly after the law change, from 30.8 to 38.8 deaths per 1,000 crash involvements. Motorcyclist death rates increased for single- and multiple-vehicle crashes, for male and female operators, and for riders of all ages including those younger than 21. After controlling for gender and age, the likelihood of death given involvement in a motorcycle crash was 25% higher than expected after the law change. It is estimated that 117 motorcyclist deaths could have been avoided during 2001-2002 if Florida's universal helmet law had remained in place. This study provides evidence of the life-saving benefits of universal helmet laws. The results also suggest that age-specific helmet laws are not effective in protecting the youngest drivers. This is not surprising, as these laws are largely unenforceable.
Storvik, Steven G; Campbell, Julius Q; Wheeler, Jeffrey B
2017-06-01
Rates of death because of asphyxia in motor vehicle crashes have been previously estimated using county and statewide data sets, but national estimates have not been reported. The literature regarding asphyxia in motor vehicle crashes primarily involves discussions about clinical findings, and crash-related variables have been sparsely reported. The current study calculated a nationwide fatality rate for asphyxia in motor vehicle crashes of 1.4%. Seventeen case studies of asphyxia were also reported providing crash-, vehicle-, and occupant-related variables. These included type of accident, crash severity, seat belt use, containment status, extent of occupant compartment intrusion, height, weight, and injury pattern. The data presented can be used to better understand the injury mechanism, identify risk factors, develop possible protective countermeasures, and create situational awareness for emergency responders and investigators.
Estimating under-reporting of road crash injuries to police using multiple linked data collections.
Watson, Angela; Watson, Barry; Vallmuur, Kirsten
2015-10-01
The reliance on police data for the counting of road crash injuries can be problematic, as it is well known that not all road crash injuries are reported to police which under-estimates the overall burden of road crash injuries. The aim of this study was to use multiple linked data sources to estimate the extent of under-reporting of road crash injuries to police in the Australian state of Queensland. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. The completeness of road crash cases reported to police was examined via discordance rates between the police data (QRCD) and the hospital data collections. In addition, the potential bias of this discordance (under-reporting) was assessed based on gender, age, road user group, and regional location. Results showed that the level of under-reporting varied depending on the data set with which the police data was compared. When all hospital data collections are examined together the estimated population of road crash injuries was approximately 28,000, with around two-thirds not linking to any record in the police data. The results also showed that the under-reporting was more likely for motorcyclists, cyclists, males, young people, and injuries occurring in Remote and Inner Regional areas. These results have important implications for road safety research and policy in terms of: prioritising funding and resources; targeting road safety interventions into areas of higher risk; and estimating the burden of road crash injuries. Copyright © 2015 Elsevier Ltd. All rights reserved.
Wang, Yonggang; Li, Linchao; Prato, Carlo G
2018-04-03
Although the taxi industry is playing an important role in Chinese everyday life, little attention has been posed towards occupational health issues concerning the taxi drivers' working conditions, driving behaviour and road safety. A cross-sectional survey was administered to 1021 taxi drivers from 21 companies in four Chinese cities and collected information about (i) sociodemographic characteristics, (ii) working conditions, (iii) frequency of daily aberrant driving behaviour, and (iv) involvement in property-damage-only (PDO) and personal injury (PI) crashes over the past two years. A hybrid bivariate model of crash involvement was specified: (i) the hybrid part concerned a latent variable model capturing unobserved traits of the taxi drivers; (ii) the bivariate part modelled jointly both types of crashes while capturing unobserved correlation between error terms. The survey answers paint a gloomy picture in terms of workload, as taxi drivers reported averages of 9.4 working hours per day and 6.7 working days per week that amount on average to about 63.0 working hours per week. Moreover, the estimates of the hybrid bivariate model reveal that increasing levels of fatigue, reckless behaviour and aggressive behaviour are positively related to a higher propensity of crash involvement. Lastly, the heavy workload is also positively correlated with the higher propensity of crashing, not only directly as a predictor of crash involvement, but also indirectly as a covariate of fatigue and aberrant driving behaviour. The findings from this study provide insights into potential strategies for preventive education and taxi industry management to improve the working conditions and hence reduce fatigue and road risk for the taxi drivers. Copyright © 2018 Elsevier Ltd. All rights reserved.
Sacchi, Emanuele; Sayed, Tarek; El-Basyouny, Karim
2016-09-01
Recently, important advances in road safety statistics have been brought about by methods able to address issues other than the choice of the best error structure for modeling crash data. In particular, accounting for spatial and temporal interdependence, i.e., the notion that the collision occurrence of a site or unit times depend on those of others, has become an important issue that needs further research. Overall, autoregressive models can be used for this purpose as they can specify that the output variable depends on its own previous values and on a stochastic term. Spatial effects have been investigated and applied mostly in the context of developing safety performance functions (SPFs) to relate crash occurrence to highway characteristics. Hence, there is a need for studies that attempt to estimate the effectiveness of safety countermeasures by including the spatial interdependence of road sites within the context of an observational before-after (BA) study. Moreover, the combination of temporal dynamics and spatial effects on crash frequency has not been explored in depth for SPF development. Therefore, the main goal of this research was to carry out a BA study accounting for spatial effects and temporal dynamics in evaluating the effectiveness of a road safety treatment. The countermeasure analyzed was the installation of traffic signals at unsignalized urban/suburban intersections in British Columbia (Canada). The full Bayes approach was selected as the statistical framework to develop the models. The results demonstrated that zone variation was a major component of total crash variability and that spatial effects were alleviated by clustering intersections together. Finally, the methodology used also allowed estimation of the treatment's effectiveness in the form of crash modification factors and functions with time trends. Copyright © 2016 Elsevier Ltd. All rights reserved.
Wang, Chen; Lu, Linjun; Lu, Jian; Wang, Tao
2016-01-01
In order to improve motorcycle safety, this article examines the correlation between crash avoidance maneuvers and injury severity sustained by motorcyclists, under multiple precrash conditions. Ten-year crash data for single-vehicle motorcycle crashes from the General Estimates Systems (GES) were analyzed, using partial proportional odds models (i.e., generalized ordered logit models). The modeling results show that "braking (no lock-up)" is associated with a higher probability of increased severity, whereas "braking (lock-up)" is associated with a higher probability of decreased severity, under all precrash conditions. "Steering" is associated with a higher probability of reduced injury severity when other vehicles are encroaching, whereas it is correlated with high injury severity under other conditions. "Braking and steering" is significantly associated with a higher probability of low severity under "animal encounter and object presence," whereas it is surprisingly correlated with high injury severity when motorcycles are traveling off the edge of the road. The results also show that a large number of motorcyclists did not perform any crash avoidance maneuvers or conducted crash avoidance maneuvers that are significantly associated with high injury severity. In general, this study suggests that precrash maneuvers are an important factor associated with motorcyclists' injury severity. To improve motorcycle safety, training/educational programs should be considered to improve safety awareness and adjust driving habits of motorcyclists. Antilock brakes and such systems are also promising, because they could effectively prevent brake lock-up and assist motorcyclists in maneuvering during critical conditions. This study also provides valuable information for the design of motorcycle training curriculum.
Frequency of target crashes for IntelliDrive safety systems
DOT National Transportation Integrated Search
2010-10-01
This report estimates the frequency of different crash types that would potentially be addressed by various categories of Intelligent Transportation Systems as part of the IntelliDriveSM safety systems program. Crash types include light-vehicle crash...
The risk of groundling fatalities from unintentional airplane crashes.
Thompson, K M; Rabouw, R F; Cooke, R M
2001-12-01
The crashes of four hijacked commercial planes on September 11, 2001, and the repeated televised images of the consequent collapse of the World Trade Center and one side of the Pentagon will inevitably change people's perceptions of the mortality risks to people on the ground from crashing airplanes. Goldstein and colleagues were the first to quantify the risk for Americans of being killed on the ground from a crashing airplane for unintentional events, providing average point estimates of 6 in a hundred million for annual risk and 4.2 in a million for lifetime risk. They noted that the lifetime risk result exceeded the commonly used risk management threshold of 1 in a million, and suggested that the risk to "groundlings" could be a useful risk communication tool because (a) it is a man-made risk (b) arising from economic activities (c) from which the victims derive no benefit and (d) exposure to which the victims cannot control. Their results have been used in risk communication. This analysis provides updated estimates of groundling fatality risks from unintentional crashes using more recent data and a geographical information system approach to modeling the population around airports. The results suggest that the average annual risk is now 1.2 in a hundred million and the lifetime risk is now 9 in ten million (below the risk management threshold). Analysis of the variability and uncertainty of this estimate, however, suggests that the exposure to groundling fatality risk varies by about a factor of approximately 100 in the spatial dimension of distance to an airport, with the risk declining rapidly outside the first 2 miles around an airport. We believe that the risk to groundlings from crashing airplanes is more useful in the context of risk communication when information about variability and uncertainty in the risk estimates is characterized, but we suspect that recent events will alter its utility in risk communication.
STOCK MARKET CRASH AND EXPECTATIONS OF AMERICAN HOUSEHOLDS*
HUDOMIET, PÉTER; KÉZDI, GÁBOR; WILLIS, ROBERT J.
2011-01-01
SUMMARY This paper utilizes data on subjective probabilities to study the impact of the stock market crash of 2008 on households’ expectations about the returns on the stock market index. We use data from the Health and Retirement Study that was fielded in February 2008 through February 2009. The effect of the crash is identified from the date of the interview, which is shown to be exogenous to previous stock market expectations. We estimate the effect of the crash on the population average of expected returns, the population average of the uncertainty about returns (subjective standard deviation), and the cross-sectional heterogeneity in expected returns (disagreement). We show estimates from simple reduced-form regressions on probability answers as well as from a more structural model that focuses on the parameters of interest and separates survey noise from relevant heterogeneity. We find a temporary increase in the population average of expectations and uncertainty right after the crash. The effect on cross-sectional heterogeneity is more significant and longer lasting, which implies substantial long-term increase in disagreement. The increase in disagreement is larger among the stockholders, the more informed, and those with higher cognitive capacity, and disagreement co-moves with trading volume and volatility in the market. PMID:21547244
Lerner, E Brooke; Cushman, Jeremy T; Blatt, Alan; Lawrence, Richard D; Shah, Manish N; Swor, Robert A; Brasel, Karen; Jurkovich, Gregory J
2011-01-01
To determine the accuracy of emergency medical services (EMS) provider assessments of motor vehicle damage when compared with measurements made by a professional crash reconstructionist. EMS providers caring for adult patients injured during a motor vehicle crash and transported to the regional trauma center in a midsized community were interviewed upon emergency department arrival. The interview collected provider estimates of crash mechanism of injury. For crashes that met a preset severity threshold, the vehicle's owner was asked to consent to having a crash reconstructionist assess the vehicle. The assessment included measuring intrusion and external automobile deformity. Vehicle damage was used to calculate change in velocity. Paired t-test, correlation, and kappa were used to compare EMS estimates and investigator-derived values. Ninety-one vehicles were enrolled; of these, 58 were inspected and 33 were excluded because the vehicle was not accessible. Six vehicles had multiple patients. Therefore, a total of 68 EMS estimates were compared with the inspection findings. Patients were 46% male, 28% were admitted to hospital, and 1% died. The mean EMS-estimated deformity was 18 inches and the mean measured deformity was 14 inches. The mean EMS-estimated intrusion was 5 inches and the mean measured intrusion was 4 inches. The EMS providers and the reconstructionist had 68% agreement for determination of external automobile deformity (kappa 0.26) and 88% agreement for determination of intrusion (kappa 0.27) when the 1999 American College of Surgeons Field Triage Decision Scheme criteria were applied. The mean (± standard deviation) EMS-estimated speed prior to the crash was 48 ± 13 mph and the mean reconstructionist-estimated change in velocity was 18 ± 12 mph (correlation -0.45). The EMS providers determined that 19 vehicles had rolled over, whereas the investigator identified 18 (kappa 0.96). In 55 cases, EMS and the investigator agreed on seat belt use; for the remaining 13 cases, there was disagreement (five) or the investigator was unable to make a determination (eight) (kappa 0.40). This study found that EMS providers are good at estimating rollover. Vehicle intrusion, deformity, and seat belt use appear to be more difficult for EMS to estimate, with only fair agreement with the crash reconstructionist. As expected, the EMS provider -estimated speed prior to the crash does not appear to be a reasonable proxy for change in velocity.
EMS Provider Assessment of Vehicle Damage Compared to a Professional Crash Reconstructionist
Lerner, E. Brooke; Cushman, Jeremy T.; Blatt, Alan; Lawrence, Richard; Shah, Manish N.; Swor, Robert; Brasel, Karen; Jurkovich, Gregory J.
2011-01-01
Objective To determine the accuracy of EMS provider assessments of motor vehicle damage, when compared to measurements made by a professional crash reconstructionist. Methods EMS providers caring for adult patients injured during a motor vehicle crash and transported to the regional trauma center in a midsized community were interviewed upon ED arrival. The interview collected provider estimates of crash mechanism of injury. For crashes that met a preset severity threshold, the vehicle’s owner was asked to consent to having a crash reconstructionist assess their vehicle. The assessment included measuring intrusion and external auto deformity. Vehicle damage was used to calculate change in velocity. Paired t-test and correlation were used to compare EMS estimates and investigator derived values. Results 91 vehicles were enrolled; of these 58 were inspected and 33 were excluded because the vehicle was not accessible. 6 vehicles had multiple patients. Therefore, a total of 68 EMS estimates were compared to the inspection findings. Patients were 46% male, 28% admitted to hospital, and 1% died. Mean EMS estimated deformity was 18” and mean measured was 14”. Mean EMS estimated intrusion was 5” and mean measured was 4”. EMS providers and the reconstructionist had 67% agreement for determination of external auto deformity (kappa 0.26), and 88% agreement for determination of intrusion (kappa 0.27) when the 1999 Field Triage Decision Scheme Criteria were applied. Mean EMS estimated speed prior to the crash was 48 mph±13 and mean reconstructionist estimated change in velocity was 18 mph±12 (correlation -0.45). EMS determined that 19 vehicles had rolled over while the investigator identified 18 (kappa 0.96). In 55 cases EMS and the investigator agreed on seatbelt use, for the remaining 13 cases there was disagreement (5) or the investigator was unable to make a determination (8) (kappa 0.40). Conclusions This study found that EMS providers are good at estimating rollover. Vehicle intrusion, deformity, and seatbelt use appear to be more difficult to estimate with only fair agreement with the crash reconstructionist. As expected, the EMS provider estimated speed prior to the crash does not appear to be a reasonable proxy for change in velocity. PMID:21815732
Safety analysis of urban arterials at the meso level.
Li, Jia; Wang, Xuesong
2017-11-01
Urban arterials form the main structure of street networks. They typically have multiple lanes, high traffic volume, and high crash frequency. Classical crash prediction models investigate the relationship between arterial characteristics and traffic safety by treating road segments and intersections as isolated units. This micro-level analysis does not work when examining urban arterial crashes because signal spacing is typically short for urban arterials, and there are interactions between intersections and road segments that classical models do not accommodate. Signal spacing also has safety effects on both intersections and road segments that classical models cannot fully account for because they allocate crashes separately to intersections and road segments. In addition, classical models do not consider the impact on arterial safety of the immediately surrounding street network pattern. This study proposes a new modeling methodology that will offer an integrated treatment of intersections and road segments by combining signalized intersections and their adjacent road segments into a single unit based on road geometric design characteristics and operational conditions. These are called meso-level units because they offer an analytical approach between micro and macro. The safety effects of signal spacing and street network pattern were estimated for this study based on 118 meso-level units obtained from 21 urban arterials in Shanghai, and were examined using CAR (conditional auto regressive) models that corrected for spatial correlation among the units within individual arterials. Results showed shorter arterial signal spacing was associated with higher total and PDO (property damage only) crashes, while arterials with a greater number of parallel roads were associated with lower total, PDO, and injury crashes. The findings from this study can be used in the traffic safety planning, design, and management of urban arterials. Copyright © 2017 Elsevier Ltd. All rights reserved.
Graduated driver licensing decal law: effect on young probationary drivers.
Curry, Allison E; Pfeiffer, Melissa R; Localio, Russell; Durbin, Dennis R
2013-01-01
Decal laws have been implemented internationally to facilitate police enforcement of graduated driver licensing (GDL) restrictions (e.g., passenger limit, nighttime curfew) but have not been evaluated. New Jersey implemented the first decal law in the U.S. on May 1, 2010. The aim of this study was to evaluate the effect of New Jersey's law on the rate of citations issued for violation of GDL restrictions and police-reported crashes among probationary drivers aged <21 years and to estimate the number of probationary drivers whose crashes were prevented by the law. New Jersey's licensing and crash databases were linked from January 1, 2008 to May 31, 2011, and each driver's license status, age, and outcome status were ascertained for each month. Monthly rates were calculated as the proportion of probationary drivers who experienced the outcome in that month. The pre-law period was defined as January 2008-January 2010 and the post-law period as May 2010-May 2011. Negative binomial regression models with robust SEs were used to determine the law's effect on crash and citation rates (adjusted for gender, seasonal trends, and overall trends) and estimate prevented crashes. Analyses were conducted in 2012. In the first year post-law, there was a 14% increase in the GDL citation rate (adjusted rate ratio 1.14 [95% CI=1.05, 1.24]); a 9% reduction in the police-reported crash rate (adjusted rate ratio 0.91 [95% CI=0.86, 0.97]), and an estimated 1624 young probationary drivers for whom a crash was prevented. Findings suggest that the law is positively affecting probationary drivers' safety. Results contribute to building the evidence base for the effectiveness of decal laws and provide valuable information to U.S. and international policymakers who are considering adding decal laws to enhance existing GDL laws. Copyright © 2013 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Strandroth, Johan
2015-03-01
When targeting a society free from serious and fatal road-traffic injuries, it has been a common practice in many countries and organizations to set up time-limited and quantified targets for the reduction of fatalities and injuries. In setting these targets EU and other organizations have recognized the importance to monitor and predict the development toward the target as well as the efficiency of road safety policies and interventions. This study aims to validate a method to forecast future road safety challenges by applying it to the fatal crashes in Sweden in 2000 and using the method to explain the change in fatalities based on the road safety interventions made until 2010. The estimation of the method is then compared to the true outcome in 2010. The aim of this study was to investigate if a residual of crashes produced by a partial analysis could constitute a sufficient base to describe the characteristics of future crashes. show that out of the 332 car occupants killed in 2000, 197 were estimated to constitute the residual in 2010. Consequently, 135 fatalities from 2000 were estimated by the model to be prevented by 2010. That is a predicted reduction of 41% compared to the reduction in the real outcome of 53%, from 332 in 2000 to 156 in 2010. The method was found able to generate a residual of crashes in 2010 from the crashes in 2000 that had a very similar nature, with regards to crash type, as the true outcome of 2010. It was also found suitable to handle double counting and system effects. However, future research is needed in order to investigate how external factors as well as random and systematic variation should be taken into account in a reliable manner. Copyright © 2015 Elsevier Ltd. All rights reserved.
2000 annual assessment : motor vehicle traffic crash fatality and injury estimates for 2000
DOT National Transportation Integrated Search
2001-11-01
This annual report, prepared as a slide presentation, contains estimates for motor vehicle traffic crashes in 2000 and the resulting injuries and fatalities. They are compared to estimates from the 1999 Final Files. These Annual Assessment estimates ...
Estimating seat belt effectiveness using matched-pair cohort methods.
Cummings, Peter; Wells, James D; Rivara, Frederick P
2003-01-01
Using US data for 1986-1998 fatal crashes, we employed matched-pair analysis methods to estimate that the relative risk of death among belted compared with unbelted occupants was 0.39 (95% confidence interval (CI) 0.37-0.41). This differs from relative risk estimates of about 0.55 in studies that used crash data collected prior to 1986. Using 1975-1998 data, we examined and rejected three theories that might explain the difference between our estimate and older estimates: (1) differences in the analysis methods; (2) changes related to car model year; (3) changes in crash characteristics over time. A fourth theory, that the introduction of seat belt laws would induce some survivors to claim belt use when they were not restrained, could explain part of the difference in our estimate and older estimates; but even in states without seat belt laws, from 1986 through 1998, the relative risk estimate was 0.45 (95% CI 0.39-0.52). All of the difference between our estimate and older estimates could be explained by some misclassification of seat belt use. Relative risk estimates would move away from 1, toward their true value, if misclassification of both the belted and unbelted decreased over time, or if the degree of misclassification remained constant, as the prevalence of belt use increased. We conclude that estimates of seat belt effects based upon data prior to 1986 may be biased toward 1 by misclassification.
Robertson, L S
1996-01-01
OBJECTIVES. Two phases of attempts to improve passenger car crash worthiness have occurred: minimum safety standards and publicized crash tests. This study evaluated these attempts, as well as changes in seat belt and alcohol use, in terms of their effect on occupant death and fatal crash rates. METHODS. Data on passenger car occupant fatalities and total involvement in fatal crashes, for 1975 through 1991, were obtained from the Fatal Accident Reporting System. Rates per mile were calculated through published sources on vehicle use by vehicle age. Regression estimates of effects of regulation, publicized crash tests, seat belt use and alcohol involvement were obtained. RESULTS. Substantial reductions in fatalities occurred in the vehicle model years from the late 1960s through most of the 1970s, when federal standards were applied. Some additional increments in reduced death rates, attributable to additional improved vehicle crashworthiness, occurred during the period of publicized crash tests. Increased seat belt use and reduced alcohol use also contributed significantly to reduced deaths. CONCLUSIONS. Minimum safety standards, crashworthiness improvements, seat belt use laws, and reduced alcohol use each contributed to a large reduction in passenger car occupant deaths. PMID:8561238
Recent trends in cyclist fatalities in Australia.
Boufous, Soufiane; Olivier, Jake
2016-08-01
The study examines trends in bicycling fatalities reported to the Australian police between 1991 and 2013. Trends were estimated using Poisson regression modelling. Overall, cycling fatalities decreased by 1.9% annually between 1991 and 2013. However, while deaths following multivehicle crashes decreased at a rate of 2.9% per annum (95% CI -4.0% to -1.8%), deaths from single vehicle crashes increased by 5.8% per annum (95% CI 4.1% to 7.5%). Over the study period, the average age of cyclists who died in single vehicle crashes (45.3 years, 95% CI 41.5 to 49.1) was significantly higher than cyclists who died in multivehicle crashes (36.2 years, 95% CI 34.7 to 37.7). The average age of deceased cyclists increased significantly for both types of crashes. The observed increase in single vehicle crashes need to be closely monitored in Australia and internationally. In-depth studies are needed to investigate the circumstances of fatal single bicycle crashes in order to develop appropriate countermeasures. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Ferguson, Susan A
2007-12-01
Electronic stability control (ESC) is designed to help drivers maintain heading control of their vehicles in high-speed or sudden maneuvers and on slippery roads. The wider proliferation of ESC across the vehicle fleet has allowed evaluation of its effects in real-world crashes in many countries, including Japan, Germany, Sweden, France, Great Britain, and the United States. This article provides a summary of the findings. Studies that examined the real-world effectiveness of ESC were reviewed. Crash effects have been examined for different roadways, using differing analytic methods, different crash severities, and different make/model vehicles including both cars and SUVs. The review discusses the methodological differences and examines the findings according to vehicle type, crash type and severity, and road conditions. The overwhelming majority of studies find that ESC is highly effective in reducing single-vehicle crashes in cars and SUVs. Fatal single-vehicle crashes involving cars are reduced by about 30-50% and SUVs by 50-70%. Fatal rollover crashes are estimated to be about 70-90% lower with ESC regardless of vehicle type. A number of studies find improved effectiveness in reducing crashes when road conditions are slippery. There is little or no effect of ESC in all multi-vehicle crashes; however, there is a 17-38% reduction in more serious, fatal multi-vehicle crashes. Given the extraordinary benefits of ESC in preventing crashes, especially those with more serious outcomes, the implementation of ESC should be accelerated to cover the full range of passenger vehicles in both developed and developing markets.
Effects of BMI on the risk and frequency of AIS 3+ injuries in motor-vehicle crashes.
Rupp, Jonathan D; Flannagan, Carol A C; Leslie, Andrew J; Hoff, Carrie N; Reed, Matthew P; Cunningham, Rebecca M
2013-01-01
Determine the effects of BMI on the risk of serious-to-fatal injury (Abbreviated Injury Scale ≥ 3 or AIS 3+) to different body regions for adults in frontal, nearside, farside, and rollover crashes. Multivariate logistic regression analysis was applied to a probability sample of adult occupants involved in crashes generated by combining the National Automotive Sampling System (NASS-CDS) with a pseudoweighted version of the Crash Injury Research and Engineering Network database. Logistic regression models were applied to weighted data to estimate the change in the number of occupants with AIS 3+ injuries if no occupants were obese. Increasing BMI increased risk of lower-extremity injury in frontal crashes, decreased risk of lower-extremity injury in nearside impacts, increased risk of upper-extremity injury in frontal and nearside crashes, and increased risk of spine injury in frontal crashes. Several of these findings were affected by interactions with gender and vehicle type. If no occupants in frontal crashes were obese, 7% fewer occupants would sustain AIS 3+ upper-extremity injuries, 8% fewer occupants would sustain AIS 3+ lower-extremity injuries, and 28% fewer occupants would sustain AIS 3+ spine injuries. Results of this study have implications on the design and evaluation of vehicle safety systems. Copyright © 2013 The Obesity Society.
Exploring the risk factors associated with the size and severity of roadway crashes in Riyadh.
Hassan, Hany M; Al-Faleh, Hesham
2013-12-01
Recently, growing concern has been shifting toward the necessity of improving traffic safety in the Kingdom of Saudi Arabia (KSA). KSA has a unique traffic safety problem in that: (a) it can be classified as a developed country in terms of the magnitude and quality of the roadway networks available and its compatibility with international standards; however, (b) it can also be considered a developing country as the rate of increase in the number of road crashes is substantial compared with relevant figures of other developing countries and other countries of the Gulf region. Hence, more research efforts are still needed. This paper examines the nature and causes of fatal and serious traffic crashes in KSA so that solutions and/or future studies can be suggested. Data from 11,545 reported fatal and injury traffic crashes that occurred in Riyadh (the capital of KSA) during the period 2004-2011 were analyzed by alternative and complementary methods. A logistic regression model was estimated and the results revealed that crash reason (speeding), damages in public property, day of the week, crash location (non-intersection location), and point of collision (head-on) were the significant variables affecting the binary target variable (fatal and non-fatal crashes). Additionally, the structural equation modeling approach was developed to identify and quantify the impacts of significant variables influencing crash size (e.g., no. of injuries, no. of vehicles involved in the crash). Crash size is one of the important indices that measure the level of safety of transportation facilities. The results showed that road factor was the most significant factor affecting the size of the crash followed by the driver and environment factors. Considering the results of this study, practical suggestions on how to improve traffic safety in KSA are also presented and discussed. © 2013.
Zhang, Meng; Khattak, Asad J; Liu, Jun; Clarke, David
2018-08-01
Rail-trespassing crashes that involve various levels of injuries to pedestrians are under-researched. Rail trespassing could occur at crossings where pedestrians are present at the wrong time and at non-crossings where pedestrians are not legally allowed to be present. This paper presents a comparative study examining rail-trespassing crashes in two contexts: highway-rail grade crossings vs. non-crossings. How pre-crash trespassing behaviors and other factors (e.g., crash time, locations, and socio-demographics) differ between grade crossings and non-crossings are explored. The analysis relies on a ten-year (2006-2015) database of rail-pedestrian trespassing crash records extracted from a Federal Railroad Administration safety database. Of these 7157 rail-pedestrian trespassing crashes, 6236 (87%) occurred at non-crossings, while 921 (13%) occurred at grade crossings. About 60% of the crashes were fatal at both crossings and non-crossings. The most prevalent pre-crash trespassing behavior is running or walking, 63% at grade crossings and 44% at non-crossings. Lying or sleeping account for 29% of non-crossing crashes, whereas they are 3.6% at grade crossings. A unique aspect of the study is that a diverse set of variables based on geographic variations across counties along with crash or injury data are modeled. Considering the data structure and heterogeneity that may exist due to unobserved factors, the multilevel mixed-effect ordered logistic regressions models are estimated. The results show that the correlates of injury severity differ across highway-rail grade crossings and non-crossings. For example, lying or sleeping on or near tracks contributed to higher chances of fatal injury in both contexts, however, they were relatively more injurious at grade crossings. The analytical results can provide guidance on railway safety improvement plans. Copyright © 2018. Published by Elsevier Ltd.
Considering built environment and spatial correlation in modeling pedestrian injury severity.
Prato, Carlo G; Kaplan, Sigal; Patrier, Alexandre; Rasmussen, Thomas K
2018-01-02
This study looks at mitigating and aggravating factors that are associated with the injury severity of pedestrians when they have crashes with another road user and overcomes existing limitations in the literature by focusing attention on the built environment and considering spatial correlation across crashes. Reports for 6,539 pedestrian crashes occurred in Denmark between 2006 and 2015 were merged with geographic information system resources containing detailed information about the built environment and exposure at the crash locations. A linearized spatial logit model estimated the probability of pedestrians sustaining a severe or fatal injury conditional on the occurrence of a crash with another road user. This study confirms previous findings about older pedestrians and intoxicated pedestrians being the most vulnerable road users and crashes with heavy vehicles and in roads with higher speed limits being related to the most severe outcomes. This study provides novel perspectives by showing positive spatial correlations of crashes with the same severity outcomes and emphasizing the role of the built environment in the proximity of the crash. This study emphasizes the need for thinking about traffic calming measures, illumination solutions, road maintenance programs, and speed limit reductions. Moreover, this study emphasizes the role of the built environment, because shopping areas, residential areas, and walking traffic density are positively related to a reduction in pedestrian injury severity. Often, these areas have in common a larger pedestrian mass that is more likely to make other road users more aware and attentive, whereas the same does not seem to apply to areas with lower pedestrian density.
A test-based method for the assessment of pre-crash warning and braking systems.
Bálint, András; Fagerlind, Helen; Kullgren, Anders
2013-10-01
In this paper, a test-based assessment method for pre-crash warning and braking systems is presented where the effectiveness of a system is measured by its ability to reduce the number of injuries of a given type or severity in car-to-car rear-end collisions. Injuries with whiplash symptoms lasting longer than 1 month and MAIS2+ injuries in both vehicles involved in the crash are considered in the assessment. The injury reduction resulting from the impact speed reduction due to a pre-crash system is estimated using a method which has its roots in the dose-response model. Human-machine interaction is also taken into account in the assessment. The results reflect the self-protection as well as the partner-protection performance of a pre-crash system in the striking vehicle in rear-end collisions and enable a comparison between two or more systems. It is also shown how the method may be used to assess the importance of warning as part of a pre-crash system. Copyright © 2013 Elsevier Ltd. All rights reserved.
Baker, Bryan C; Nolan, Joseph M; O'Neill, Brian; Genetos, Alexander P
2008-01-01
Passenger vehicles are designed to absorb crash energy in frontal crashes through deformation or crush of energy-absorbing structures forward of the occupant compartment. In collisions between cars and light trucks (i.e., pickups and SUVs), however, the capacity of energy-absorption structures may not be fully utilized because mismatches often exist between the heights of these structures in the colliding vehicles. In 2003 automakers voluntarily committed to new design standards aimed at reducing the height mismatches between cars and light trucks. By September 2009 all new light trucks will have either the primary front structure (typically the frame rails) or a secondary structure connected to the primary structure low enough to interact with the primary structures in cars, which for most cars is about the height of the front bumper. To estimate the overall benefit of the voluntary commitment, the real-world crash experience of light trucks already meeting the height-matching criteria was compared with that of light trucks not meeting the criteria for 2000-2003 model light trucks in collisions with passenger cars during calendar years 2001-2004. The estimated benefits of lower front energy-absorbing structure were a 19 percent reduction (p<0.05) in fatality risk to belted car drivers in front-to-front crashes with light trucks and a 19 percent reduction (p<0.05) in fatality risk to car drivers in front-to-driver-side crashes with light trucks.
FMCSA safety program effectiveness measurement : Intervention Model in fiscal year 2007
DOT National Transportation Integrated Search
2011-04-01
This report presents results from FMCSAs Roadside Intervention Model for fiscal year 2007. The model estimates the number of crashes avoided, as well as injuries avoided and lives saved, as a result of the Agencys roadside inspection program. T...
Investigation of Influential Factors for Bicycle Crashes Using a Spatiotemporal Model
NASA Astrophysics Data System (ADS)
Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.
2017-09-01
Despite the numerous potential advantages of indulging in bicycling, such as elevation of health and environment along with mitigation of congestion, the cyclists are a vulnerable group of commuters which is exposed to safety risks. This study aims to investigate the explanatory variables at transportation planning level which have a significant impact on the bicycle crashes. To account for the serial changes around the built environment, the linear time trend as well as time-varying coefficients are utilized for the covariates. These model modifications help account for the variations in the environment which may escape the incorporated variables due to lack of robustness in data. Also, to incorporate the interaction of roadway, demographic, and socioeconomic features within a Traffic Analysis Zone (TAZ), with the bicycle crashes of that area, a spatial correlation is integrated. This spatial correlation accounts for the spatially structured random effects which capture the unobserved heterogeneity and add towards building more comprehensive model with relatively precise estimates. Two different age groups, the student population in the TAZs, the presence of arterial roads and bike lanes, were observed to be statistically significant variables related with bicycle crashes. These observations will guide the transportation planning organizations which focus on the entity of TAZ while developing policies. The results of the current study establish a quantifies relationship between the significant factors and the crash count which will enable the planners to choose the most cost-efficient, yet most productive, factors which needs to be addressed for mitigation of crashes.
An Index For Rating the Total Secondary Safety of Vehicles from Real World Crash Data
Newstead, S.; Watson, L.; Cameron, M.
2007-01-01
This study proposes a total secondary safety index for light passenger vehicles that rates the relative performance of vehicles in protecting both their own occupants and other road users in the full range of real world crash circumstances. The index estimates the risk of death or serious injury to key road users in crashes involving light passenger vehicles across the full range of crash types. The proposed index has been estimated from real world crash data from Australasia and was able to identify vehicles that have superior or inferior total secondary safety characteristics compared with the average vehicle. PMID:18184497
Head-on crashes on two-way interurban roads: a public health concern in road safety.
Olabarria, Marta; Santamariña-Rubio, Elena; Marí-Dell'Olmo, Marc; Gotsens, Mercè; Novoa, Ana M; Borrell, Carme; Pérez, Katherine
2015-09-01
To describe the magnitude and characteristics of crashes and drivers involved in head-on crashes on two-way interurban roads in Spain between 2007 and 2012, and to identify the factors associated with the likelihood of head-on crashes on these roads compared with other types of crash. A cross-sectional study was conducted using the National Crash Register. The dependent variables were head-on crashes with injury (yes/no) and drivers involved in head-on crashes (yes/no). Factors associated with head-on crashes and with being a driver involved in a head-on crash versus other types of crash were studied using a multivariate robust Poisson regression model to estimate proportion ratios (PR) and confidence intervals (95% CI). There were 9,192 head-on crashes on two-way Spanish interurban roads. A total of 15,412 men and 3,862 women drivers were involved. Compared with other types of crash, head-on collisions were more likely on roads 7 m or more wide, on road sections with curves, narrowings or drop changes, on wet or snowy surfaces, and in twilight conditions. Transgressions committed by drivers involved in head-on crashes were driving in the opposite direction and incorrectly overtaking another vehicle. Factors associated with a lower probability of head-on crashes were the existence of medians (PR=0.57; 95%CI: 0.48-0.68) and a paved shoulder of less than 1.5 meters (PR=0.81; 95%CI: 0.77-0.86) or from 1.5 to 2.45 meters (PR=0.90; 95%CI: 0.84-0.96). This study allowed the characterization of crashes and drivers involved in head-on crashes on two-way interurban roads. The lower probability observed on roads with median strips point to these measures as an effective way to reduce these collisions. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.
Under-reporting of road traffic crash data in Ghana.
Salifu, Mohammed; Ackaah, Williams
2012-01-01
Having reliable estimates of the shortfalls in road traffic crash data is an important prerequisite for setting more realistic targets for crash/casualty reduction programmes and for a better appreciation of the socio-economic significance of road traffic crashes. This study was carried out to establish realistic estimates of the overall shortfall (under-reporting) in the official crash statistics in Ghana over an eight-year period (1997-2004). Surveys were conducted at hospitals and among drivers to generate relevant alternative data which were then matched against records in police crash data files and the official database. Overall shortfalls came from two sources, namely, 'non-reporting' and 'under-recording'. The results show that the level of non-reporting varied significantly with the severity of the crash from about 57% for property damage crashes through 8% for serious injury crashes to 0% for fatal crashes. Crashes involving cyclists and motorcyclists were also substantially non-reported. Under-recording on the other hand declined significantly over the period from an average of 37% in 1997-1998 to 27% in 2003-2004. Thus, the official statistics of road traffic crashes in Ghana are subject to significant shortfalls that need to be accounted for. Correction factors have therefore been suggested for adjusting the official data.
Park, Juneyoung; Abdel-Aty, Mohamed; Lee, Jaeyoung
2016-09-01
Although many researchers have estimated the crash modification factors (CMFs) for specific treatments (or countermeasures), there is a lack of prior studies that have explored the variation of CMFs. Thus, the main objectives of this study are: (a) to estimate CMFs for the installation of different types of roadside barriers, and (b) to determine the changes of safety effects for different crash types, severities, and conditions. Two observational before-after analyses (i.e. empirical Bayes (EB) and full Bayes (FB) approaches) were utilized in this study to estimate CMFs. To consider the variation of safety effects based on different vehicle, driver, weather, and time of day information, the crashes were categorized based on vehicle size (passenger and heavy), driver age (young, middle, and old), weather condition (normal and rain), and time difference (day time and night time). The results show that the addition of roadside barriers is safety effective in reducing severe crashes for all types and run-off roadway (ROR) crashes. On the other hand, it was found that roadside barriers tend to increase all types of crashes for all severities. The results indicate that the treatment might increase the total number of crashes but it might be helpful in reducing injury and severe crashes. In this study, the variation of CMFs was determined for ROR crashes based on the different vehicle, driver, weather, and time information. Based on the findings from this study, the variation of CMFs can enhance the reliability of CMFs for different roadway conditions in decision making process. Also, it can be recommended to identify the safety effects of specific treatments for different crash types and severity levels with consideration of the different vehicle, driver, weather, and time of day information. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.
Effects of rearview cameras and rear parking sensors on police-reported backing crashes.
Cicchino, Jessica B
2017-11-17
The objective of this study was to examine the effectiveness of rearview cameras, rear parking sensors, and both systems combined in preventing police-reported backing crashes. Negative binomial regression was used to compare rates of police-reported backing crash involvements per insured vehicle year in 22 U.S. states during 2009-2014 between passenger vehicle models with backing technologies and the same vehicle models where the optional systems were not purchased, controlling for other factors affecting crash risk. Rearview cameras were examined from four automakers, rear parking sensors from 2 automakers, and both systems combined from a single automaker. Rearview cameras reduced backing crash involvement rates by 17%. Reductions were larger for drivers 70 and older (36%) than for drivers younger than 70 (16%); however, estimates for older and younger drivers did not differ significantly from one another. The Buick Lucerne's rear parking sensor system reduced backing crash involvement rates significantly by 34%, but the reduction for Mercedes-Benz vehicles fit with a sensor system was small and not statistically significant. When averaged between the 2 automakers, effects were significantly larger for drivers 70 and older (38% reduction) than for drivers younger than 70 (1% increase); effects were significant for older but not younger drivers. Backing crash involvement rates were 13% lower among Mercedes-Benz vehicles with a rearview camera and parking sensors than among vehicles without, but this finding was not significant. Rearview cameras are effective in preventing police-reported backing crashes. Effects of rear parking sensors are less straightforward; it is unclear whether the Buick Lucerne system's benefits are due to the older age of its drivers, characteristics of the vehicle or system, or a combination. Systems may be especially beneficial to older drivers who might have limitations that make backing challenging. Although effect estimates did not differ significantly between older and younger drivers for both system types, the magnitude of the differences was large and the pattern of results was consistent across 6 of the 7 systems examined. When rear visibility systems become required equipment on new passenger vehicles in 2018, rearview cameras can be expected to prevent 1 in 6 backing crashes reported to police that involve equipped vehicles.
Edge localized mode rotation and the nonlinear dynamics of filaments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Morales, J. A.; Bécoulet, M.; Garbet, X.
2016-04-15
Edge Localized Modes (ELMs) rotating precursors were reported few milliseconds before an ELM crash in several tokamak experiments. Also, the reversal of the filaments rotation at the ELM crash is commonly observed. In this article, we present a mathematical model that reproduces the rotation of the ELM precursors as well as the reversal of the filaments rotation at the ELM crash. Linear ballooning theory is used to establish a formula estimating the rotation velocity of ELM precursors. The linear study together with nonlinear magnetohydrodynamic simulations give an explanation to the rotations observed experimentally. Unstable ballooning modes, localized at the pedestal,more » grow and rotate in the electron diamagnetic direction in the laboratory reference frame. Approaching the ELM crash, this rotation decreases corresponding to the moment when the magnetic reconnection occurs. During the highly nonlinear ELM crash, the ELM filaments are cut from the main plasma due to the strong sheared mean flow that is nonlinearly generated via the Maxwell stress tensor.« less
Motor vehicle traffic crash fatality and injury estimates for 2000
DOT National Transportation Integrated Search
2001-01-01
This brochure, prepared from a slide presentation, contains the Early Assessment estimates for motor vehicle traffic crashes in 2000 and the resulting injuries and fatalities. They are compared to estimates from the 1999 Annual Files. These Early Ass...
Saha, Dibakar; Alluri, Priyanka; Gan, Albert
2017-01-01
The Highway Safety Manual (HSM) presents statistical models to quantitatively estimate an agency's safety performance. The models were developed using data from only a few U.S. states. To account for the effects of the local attributes and temporal factors on crash occurrence, agencies are required to calibrate the HSM-default models for crash predictions. The manual suggests updating calibration factors every two to three years, or preferably on an annual basis. Given that the calibration process involves substantial time, effort, and resources, a comprehensive analysis of the required calibration factor update frequency is valuable to the agencies. Accordingly, the objective of this study is to evaluate the HSM's recommendation and determine the required frequency of calibration factor updates. A robust Bayesian estimation procedure is used to assess the variation between calibration factors computed annually, biennially, and triennially using data collected from over 2400 miles of segments and over 700 intersections on urban and suburban facilities in Florida. Bayesian model yields a posterior distribution of the model parameters that give credible information to infer whether the difference between calibration factors computed at specified intervals is credibly different from the null value which represents unaltered calibration factors between the comparison years or in other words, zero difference. The concept of the null value is extended to include the range of values that are practically equivalent to zero. Bayesian inference shows that calibration factors based on total crash frequency are required to be updated every two years in cases where the variations between calibration factors are not greater than 0.01. When the variations are between 0.01 and 0.05, calibration factors based on total crash frequency could be updated every three years. Copyright © 2016 Elsevier Ltd. All rights reserved.
Bae, Tae Soo; Loan, Peter; Choi, Kuiwon; Hong, Daehie; Mun, Mu Seong
2010-12-01
When car crash experiments are performed using cadavers or dummies, the active muscles' reaction on crash situations cannot be observed. The aim of this study is to estimate muscles' response of the major muscle groups using three-dimensional musculoskeletal model by dynamic simulations of low-speed sled-impact. The three-dimensional musculoskeletal models of eight subjects were developed, including 241 degrees of freedom and 86 muscles. The muscle parameters considering limb lengths and the force-generating properties of the muscles were redefined by optimization to fit for each subject. Kinematic data and external forces measured by motion tracking system and dynamometer were then input as boundary conditions. Through a least-squares optimization algorithm, active muscles' responses were calculated during inverse dynamic analysis tracking the motion of each subject. Electromyography for major muscles at elbow, knee, and ankle joints was measured to validate each model. For low-speed sled-impact crash, experiment and simulation with optimized and unoptimized muscle parameters were performed at 9.4 m/h and 10 m/h and muscle activities were compared among them. The muscle activities with optimized parameters were closer to experimental measurements than the results without optimization. In addition, the extensor muscle activities at knee, ankle, and elbow joint were found considerably at impact time, unlike previous studies using cadaver or dummies. This study demonstrated the need to optimize the muscle parameters to predict impact situation correctly in computational studies using musculoskeletal models. And to improve accuracy of analysis for car crash injury using humanlike dummies, muscle reflex function, major extensor muscles' response at elbow, knee, and ankle joints, should be considered.
Analysis of light vehicle crashes and pre-crash scenarios based on the 2000 General Estimates System
DOT National Transportation Integrated Search
2003-02-01
This report analyzes the problem of light vehicle crashes in the United States to support the development and assessment of effective crash avoidance systems as part of the U.S. Department of Transportation's Intelligent Vehicle Initiative. The analy...
Mandatory Physician Reporting of At-Risk Drivers: The Older Driver Example.
Agimi, Yll; Albert, Steven M; Youk, Ada O; Documet, Patricia I; Steiner, Claudia A
2018-05-08
In a number of states, physicians are mandated by state law to report at-risk drivers to licensing authorities. Often these patients are older adult drivers who may exhibit unsafe driving behaviors, have functional/cognitive impairments, or are diagnosed with conditions such as Alzheimer's disease and/or seizure disorders. The hypothesis that mandatory physician reporting laws reduce the rate of crash-related hospitalizations among older adult drivers was tested. Using retrospective data (2004-2009), this study identified 176,066 older driver crash-related hospitalizations, from the State Inpatient Databases. Three age-specific negative binomial generalized estimating equation models were used to estimate the effect of physician reporting laws on state's incidence rate of crash-related hospitalizations among older drivers. No evidence was found for an independent association between mandatory physician reporting laws and a lower crash hospitalization rate among any of the age groups examined. The main predictor of interest, mandatory physician reporting, failed to explain any significant variation in crash hospitalization rates, when adjusting for other state-specific laws and characteristics. Vision testing at in-person license renewal was a significant predictor of lower crash hospitalization rate, ranging from incidence rate ratio of 0.77 (95% confidence interval 0.62-0.94) among 60- to 64-year olds to 0.83 (95% confidence interval 0.67-0.97) among 80- to 84-year olds. Physician reporting laws and age-based licensing requirements are often at odds with older driver's need to maintain independence. This study examines this balance and finds no evidence of the benefits of mandatory physician reporting requirements on driver crash hospitalizations, suggesting that physician mandates do not yet yield significant older driver safety benefits, possibly to the detriment of older driver's well-being and independence.
Bergen, Gwen; Peterson, Cora; Ederer, David; Florence, Curtis; Haileyesus, Tadesse; Kresnow, Marcie-jo; Xu, Likang
2014-01-01
Background Motor vehicle crashes are a leading cause of death and injury in the United States. The purpose of this study was to describe the current health burden and medical and work loss costs of nonfatal crash injuries among vehicle occupants in the United States. Methods CDC analyzed data on emergency department (ED) visits resulting from nonfatal crash injuries among vehicle occupants in 2012 using the National Electronic Injury Surveillance System – All Injury Program (NEISS-AIP) and the Healthcare Cost and Utilization Project National Inpatient Sample (HCUP-NIS). The number and rate of all ED visits for the treatment of crash injuries that resulted in the patient being released and the number and rate of hospitalizations for the treatment of crash injuries were estimated, as were the associated number of hospital days and lifetime medical and work loss costs. Results In 2012, an estimated 2,519,471 ED visits resulted from nonfatal crash injuries, with an estimated lifetime medical cost of $18.4 billion (2012 U.S. dollars). Approximately 7.5% of these visits resulted in hospitalizations that required an estimated 1,057,465 hospital days in 2012. Conclusions Nonfatal crash injuries occur frequently and result in substantial costs to individuals, employers, and society. For each motor vehicle crash death in 2012, eight persons were hospitalized, and 100 were treated and released from the ED. Implications for Public Health Public health practices and laws, such as primary seat belt laws, child passenger restraint laws, ignition interlocks to prevent alcohol impaired driving, sobriety checkpoints, and graduated driver licensing systems have demonstrated effectiveness for reducing motor vehicle crashes and injuries. They might also substantially reduce associated ED visits, hospitalizations, and medical costs. PMID:25299606
Cell phone use while driving and attributable crash risk.
Farmer, Charles M; Braitman, Keli A; Lund, Adrian K
2010-10-01
Prior research has estimated that crash risk is 4 times higher when talking on a cell phone versus not talking. The objectives of this study were to estimate the extent to which drivers talk on cell phones while driving and to compute the implied annual number of crashes that could have been avoided if driver cell phone use were restricted. A national survey of approximately 1200 U.S. drivers was conducted. Respondents were asked to approximate the amount of time spent driving during a given day, number of cell phone calls made or received, and amount of driving time spent talking on a cell phone. Population attributable risk (PAR) was computed for each combination of driver gender, driver age, day of week, and time of day. These were multiplied by the corresponding crash counts to estimate the number of crashes that could have been avoided. On average, drivers were talking on cell phones approximately 7 percent of the time while driving. Rates were higher on weekdays (8%), in the afternoon and evening (8%), and for drivers younger than 30 (16%). Based on these use rates, restricting cell phones while driving could have prevented an estimated 22 percent (i.e., 1.3 million) of the crashes in 2008. Although increased rates of cell phone use while driving should be leading to increased crash rates, crash rates have been declining. Reasons for this paradox are unclear. One possibility is that the increase in cell phone use and crash risk due to cell phone use have been overestimated. Another possibility is that cell phone use has supplanted other driving distractions that were similarly hazardous.
Wu, Lingtao; Lord, Dominique
2017-05-01
This study further examined the use of regression models for developing crash modification factors (CMFs), specifically focusing on the misspecification in the link function. The primary objectives were to validate the accuracy of CMFs derived from the commonly used regression models (i.e., generalized linear models or GLMs with additive linear link functions) when some of the variables have nonlinear relationships and quantify the amount of bias as a function of the nonlinearity. Using the concept of artificial realistic data, various linear and nonlinear crash modification functions (CM-Functions) were assumed for three variables. Crash counts were randomly generated based on these CM-Functions. CMFs were then derived from regression models for three different scenarios. The results were compared with the assumed true values. The main findings are summarized as follows: (1) when some variables have nonlinear relationships with crash risk, the CMFs for these variables derived from the commonly used GLMs are all biased, especially around areas away from the baseline conditions (e.g., boundary areas); (2) with the increase in nonlinearity (i.e., nonlinear relationship becomes stronger), the bias becomes more significant; (3) the quality of CMFs for other variables having linear relationships can be influenced when mixed with those having nonlinear relationships, but the accuracy may still be acceptable; and (4) the misuse of the link function for one or more variables can also lead to biased estimates for other parameters. This study raised the importance of the link function when using regression models for developing CMFs. Copyright © 2017 Elsevier Ltd. All rights reserved.
Desktop reference for crash reduction factors
DOT National Transportation Integrated Search
2007-09-01
This Desktop Reference documents the estimates of the crash reduction that might be expected if a specific countermeasure or group of countermeasures is implemented with respect to intersections, roadway departure and other non-intersection crashes, ...
Brar, Sukhvir S
2014-09-01
Quasi-induced exposure analysis was used to estimate annual fatal crash involvement rates for validly licensed, suspended or revoked (S/R), and unlicensed drivers in California from 1987 through 2009 using fatal crash data obtained from the National Highway Traffic Safety Administration's Fatality Analysis Reporting System and crash culpability determinations from the California Highway Patrol's Statewide Integrated Traffic Records System. Although there was some year-to-year fluctuation in the annual estimates, S/R and unlicensed drivers were over-involved as at-fault drivers in fatal crashes during every year of the 23-year time period relative to validly licensed drivers. The fatal crash involvement ratios combined across all years were 0.86 for validly licensed drivers, 2.23 for S/R drivers, and 2.34 for unlicensed drivers. Hence, compared to validly licensed drivers, the odds of being at-fault for a fatal crash were 160% higher for S/R drivers (involvement ratio=2.60) and 173% higher for unlicensed drivers (involvement ratio=2.73). The excess risks of S/R and unlicensed drivers are somewhat lower than estimates found in a prior study using the same technique, but the results nonetheless provide evidence that S/R and unlicensed drivers are much more hazardous on the road than are validly licensed drivers and emphasize the importance of using strong countermeasures-including vehicle impoundment-to reduce their high crash risk. These findings support interventions to help reduce driving among S/R and unlicensed drivers. Published by Elsevier Ltd.
Kusano, Kristofer; Gorman, Thomas I; Sherony, Rini; Gabler, Hampton C
2014-01-01
Single-vehicle collisions involve only 10 percent of all occupants in crashes in the United States, yet these same crashes account for 31 percent of all fatalities. Along with other vehicle safety advancements, lane departure warning (LDW) systems are being introduced to mitigate the harmful effects of single-vehicle collisions. The objective of this study is to quantify the number of crashes and seriously injured drivers that could have been prevented in the United States in 2012 had all vehicles been equipped with LDW. In order to estimate the potential injury reduction benefits of LDW in the vehicle fleet, a comprehensive crash and injury simulation model was developed. The model's basis was 481 single-vehicle collisions extracted from the NASS-CDS for year 2012. Each crash was simulated in 2 conditions: (1) as it occurred and (2) as if the driver had an LDW system. By comparing the simulated vehicle's off-road trajectory before and after LDW, the reduction in the probability of a crash was determined. The probability of a seriously injured occupant (Maximum Abbreviated Injury Score [MAIS] 3+) given a crash was computed using injury risk curves with departure velocity and seat belt use as predictors. Each crash was simulated between 18 and 216 times to account for variable driver reaction, road, and vehicle conditions. Finally, the probability of a crash and seriously injured driver was summed over all simulations to determine the benefit of LDW. A majority of roads where departure crashes occurred had 2 lanes and were undivided. As a result, 58 percent of crashes had no shoulder. LDW will not be as effective on roads with no shoulder as on roads with large shoulders. LDW could potentially prevent 28.9 percent of all road departure crashes caused by the driver drifting out of his or her lane, resulting in a 24.3 percent reduction in the number of seriously injured drivers. The results of this study show that LDW, if widely adopted, could significantly mitigate a harmful crash type. Larger shoulder width and the presence of lane markings, determined by manual examination of scene photographs, increased the effectiveness of LDW. This result suggests that highway systems should be modified to maximize LDW effectiveness by expanding shoulders and regularly painting lane lines.
Effectiveness of an improved road safety policy in Ethiopia: an interrupted time series study.
Abegaz, Teferi; Berhane, Yemane; Worku, Alemayehu; Assrat, Abebe
2014-05-31
In recent years, there has been an increasing interest in implementing road safety policy by different low income countries. However; the evidence is scarce on its success in the reduction of crashes, injuries and deaths. This study was conducted to assess whether road crashes, injuries and fatalities was reduced following the road safety regulation introduced as of September 2007 by Oromia Regional State Transport Bureau. Routine road traffic accident data for the year 2002-2011were collected from sixteen traffic police offices. Data on average daily vehicle flow was obtained from the Ethiopian Road Authority. Interrupted time series design using segmented linear regression model was applied to estimate the effect of an improved road safety policy. A total of 4,053 crashes occurred on Addis Ababa - Adama/Hawassa main road. Of these crashes, almost half 46.4% (1,880) were property damage, 29.4% (1,193) were fatal and 24.2% (980) injury crashes, resulting 1,392 fatalities and 1,749 injuries. There were statistically significant reductions in non-injury crashes and deaths. Non-injury crash was reduced by 19% and fatality by 12.4% in the first year of implementing the revised transport safety regulation. Although revised road safety policy helped in reducing motor vehicle crashes and associated fatalities, the overall incidence rate is still very high. Further action is required to avoid unnecessary loss of lives.
Crash risk factors for interstate large trucks in North Carolina.
Teoh, Eric R; Carter, Daniel L; Smith, Sarah; McCartt, Anne T
2017-09-01
Provide an updated examination of risk factors for large truck involvements in crashes resulting in injury or death. A matched case-control study was conducted in North Carolina of large trucks operated by interstate carriers. Cases were defined as trucks involved in crashes resulting in fatal or non-fatal injury, and one control truck was matched on the basis of location, weekday, time of day, and truck type. The matched-pair odds ratio provided an estimate of the effect of various driver, vehicle, or carrier factors. Out-of-service (OOS) brake violations tripled the risk of crashing; any OOS vehicle defect increased crash risk by 362%. Higher historical crash rates (fatal, injury, or all crashes) of the carrier were associated with increased risk of crashing. Operating on a short-haul exemption increased crash risk by 383%. Antilock braking systems reduced crash risk by 65%. All of these results were statistically significant at the 95% confidence level. Other safety technologies also showed estimated benefits, although not statistically significant. With the exception of the finding that short-haul exemption is associated with increased crash risk, results largely bolster what is currently known about large truck crash risk and reinforce current enforcement practices. Results also suggest vehicle safety technologies can be important in lowering crash risk. This means that as safety technology continues to penetrate the fleet, whether from voluntary usage or government mandates, reductions in large truck crashes may be achieved. Practical application: Results imply that increased enforcement and use of crash avoidance technologies can improve the large truck crash problem. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.
Safety model assessment and two-lane urban crash model
DOT National Transportation Integrated Search
2008-10-01
There are many reasons to be concerned with estimating the frequency and social costs of highway accidents, but most reasons are motivated by a desire to minimize these costs to the extent feasible. Competition for scarce resources is a practical nec...
Determinants of pedestrian and bicyclist crash severity by party at fault in San Francisco, CA.
Salon, Deborah; McIntyre, Andrew
2018-01-01
Pedestrian and bicyclist safety is of growing concern, especially given the increasing numbers of urban residents choosing to walk and bike. Sharing the roads with automobiles, these road users are particularly vulnerable. An intuitive conceptual model is proposed of the determinants of injury severity in crashes between vehicles and nonmotorized road users. Using 10 years of crash data from San Francisco, CA, we estimate logistic regression models to illuminate key determinants of crash severity for both pedestrian and bicyclist collisions. The analyses are separated by party at fault to test the novel hypothesis that environmental factors affecting driver speed and reaction time may be especially important when the driver is not at fault. Pedestrian results are broadly consistent with prior research, and offer considerable support for this hypothesis. The strongest predictors of injury severity include pedestrian advanced age, driver sobriety, vehicle type, and a set of variables that help determine driver speed and reaction time. Bicyclist results were weaker overall, and the distinction by party at fault was less important. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ghadiriyan Arani, M.; Pahlavani, P.; Effati, M.; Noori Alamooti, F.
2017-09-01
Today, one of the social problems influencing on the lives of many people is the road traffic crashes especially the highway ones. In this regard, this paper focuses on highway of capital and the most populous city in the U.S. state of Georgia and the ninth largest metropolitan area in the United States namely Atlanta. Geographically weighted regression and general centrality criteria are the aspects of traffic used for this article. In the first step, in order to estimate of crash intensity, it is needed to extract the dual graph from the status of streets and highways to use general centrality criteria. With the help of the graph produced, the criteria are: Degree, Pageranks, Random walk, Eccentricity, Closeness, Betweenness, Clustering coefficient, Eigenvector, and Straightness. The intensity of crash point is counted for every highway by dividing the number of crashes in that highway to the total number of crashes. Intensity of crash point is calculated for each highway. Then, criteria and crash point were normalized and the correlation between them was calculated to determine the criteria that are not dependent on each other. The proposed hybrid approach is a good way to regression issues because these effective measures result to a more desirable output. R2 values for geographically weighted regression using the Gaussian kernel was 0.539 and also 0.684 was obtained using a triple-core cube. The results showed that the triple-core cube kernel is better for modeling the crash intensity.
Isaksson-Hellman, Irene; Lindman, Magdalena
2016-09-01
The aim of the present study was to evaluate the crash mitigation performance of low-speed automated emergency braking collision avoidance technologies by examining crash rates, car damage, and personal injuries. Insurance claims data were used to identify rear-end frontal collisions, the specific situations where the low-speed automated emergency braking system intervenes. We compared cars of the same model (Volvo V70) with and without the low-speed automated emergency braking system (AEB and no AEB, respectively). Distributions of spare parts required for car repair were analyzed to identify car damage, and crash severity was estimated by comparing the results with laboratory crash tests. Repair costs and occupant injuries were investigated for both the striking and the struck vehicle. Rear-end frontal collisions were reduced by 27% for cars with low-speed AEB compared to cars without the system. Those of low severity were reduced by 37%, though more severe crashes were not reduced. Accordingly, the number of injured occupants in vehicles struck by low-speed AEB cars was reduced in low-severity crashes. In offset crash configurations, the system was found to be less effective. This study adds important information about the safety performance of collision avoidance technologies, beyond the number of crashes avoided. By combining insurance claims data and information from spare parts used, the study demonstrates a mitigating effect of low-speed AEB in real-world traffic.
Mortality from motorcycle crashes: the baby-boomer cohort effect.
Puac-Polanco, Victor; Keyes, Katherine M; Li, Guohua
2016-12-01
Motorcyclists are known to be at substantially higher risk per mile traveled of dying from crashes than car occupants. In 2014, motorcycling made up less than 1 % of person-miles traveled but 13 % of the total mortality from motor-vehicle crashes in the United States. We assessed the cohort effect of the baby-boomers (i.e., those born between 1946 and 1964) in motorcycle crash mortality from 1975 to 2014 in the United States. Using mortality data for motorcycle occupants from the Fatality Analysis Reporting System, we performed an age-period-cohort analysis using the multiphase method and the intrinsic estimator method. Baby-boomers experienced the highest mortality rates from motorcycle crashes at age 20-24 years and continued to experience excess mortality after age 40 years. After removing the effects of age and period, the estimated mortality risk from motorcycle crashes for baby-boomers was 48 % higher than that of the referent cohort (those born between 1930 and 1934, rate ratio 1.48; 95 % CI: 1.01, 2.18). Results from the multiphase method and the intrinsic estimator method were consistent. The baby-boomers have experienced significantly higher mortality from motorcycle crashes than other birth cohorts. To reduce motorcycle crash mortality, intervention programs specifically tailored for the baby-boomer generation are warranted.
Left-turn phase: permissive, protected, or both? A quasi-experimental design in New York City.
Chen, Li; Chen, Cynthia; Ewing, Reid
2015-03-01
The practice of left-turn phasing selection (permissive, protected-only, or both) varies from one locality to another. The literature evidence on this issue is equally mixed and insufficient. In this study, we evaluate the safety impacts of changing left-turn signal phasing from permissive to protected/permissive or protected-only at 68 intersections in New York City using a rigorous quasi-experimental design accompanied with regression modeling. Changes in police reported crashes including total crashes, multiple-vehicle crashes, left-turn crashes, pedestrian crashes and bicyclist crashes were compared between before period and after period for the treatment group and comparison group by means of negative binomial regression using a Generalized Estimating Equations (GEE) technique. Confounding factors such as the built environment characteristics that were not controlled in comparison group selection are accounted for by this approach. The results show that the change of permissive left-turn signal phasing to protected/permissive or protected-only signal phasing does not result in a significant reduction in intersection crashes. Though the protected-only signal phasing does reduce the left-turn crashes and pedestrian crashes, this reduction was offset by a possible increase in over-taking crashes. These results suggest that left-turn phasing should not be treated as a universal solution that is always better than the permissive control for left-turn vehicles. The selection and implementation of left-turn signal phasing needs to be done carefully, considering potential trade-offs between safety and delay, and many other factors such as geometry, traffic flows and operations. Copyright © 2014 Elsevier Ltd. All rights reserved.
Vanderschuren, Marianne
2008-03-01
Intelligent Transport Systems (ITS) can facilitate the delivery of a wide range of policy objectives. There are six main objectives/benefits identified in the international literature: Safety (reduction of (potential) crashes), mobility (reduction of delays and travel times), efficiency (optimise the use of existing infrastructure), productivity (cost saving), energy/environment and customer satisfaction [Mitretek Systems, 2001. Intelligent Transport System Benefits: 2001 update, Under Contract to the Federal Highway Administration, US Department of Transportation, Washington, DC, US]. In the South African context, there is an interest for measures that can reduce (potential) crashes. In South Africa the number of year on year traffic related fatalities is still increasing. In 2005 the number of fatalities was 15393 (from 14135 in 2004) while the estimated costs for the same period increased from R8.89-billion to R9.99-billion [RTMC, 2007. Interim Road Traffic and Fatal Crash Report 2006, Road Traffic Management Corporation, Pretoria, SA]. Given the extent of the road safety problem and the potential benefits of ITS, the need for further research is apparent. A study with regards to the potential of different types of models (macroscopic, mesoscopic and miscroscopic simulation models) led to the use of Paramics. Two corridors and three types of ITS measures were investigated and safety benefits were estimated.
Zhang, Yuting; Yan, Xuedong; Li, Xiaomeng; Wu, Jiawei; Dixit, Vinayak V
2018-06-19
Red-light running (RLR) has been identified as one of the prominent contributing factors involved in signalized intersection crashes. In order to reduce RLR crashes, primarily, a better understanding of RLR behavior and crashes is needed. In this study, three RLR crash types were extracted from the general estimates system (GES), including go-straight (GS) RLR vehicle colliding with go-straight non-RLR vehicle, go-straight RLR vehicle colliding with left-turn (LT) non-RLR vehicle, and left-turn RLR vehicle colliding with go-straight non-RLR vehicle. Then, crash features within each crash type scenario were compared, and risk analyses of GS RLR and LT RLR were also conducted. The results indicated that for the GS RLR driver, the speed limit displayed the highest effects on the percentages of GS RLR collision scenarios. For the LT RLR driver, the number of lanes displayed the highest effects on the percentages of LT RLR collision scenarios. Additionally, the drivers who were older than 50 years, distracted, and had a limited view were more likely to be involved in LT RLR accidents. Furthermore, the speeding drivers were more likely to be involved in GS RLR accidents. These findings could give a comprehensive understanding of RLR crash features and propensities for each RLR crash type.
Curry, Allison E; Pfeiffer, Melissa R; Elliott, Michael R; Durbin, Dennis R
2015-12-01
New Jersey (NJ) implemented the first-in-the-US Graduated Driver Licensing (GDL) decal provision in May 2010 for young drivers with learner's permits or intermediate licenses. Previous analyses found an association between the provision and crash reduction among intermediate drivers. The aim of this study is to examine the association between NJ's provision and GDL citation and crash rates among drivers aged <21 years with learner's permits. We estimated monthly per-driver rates from January 2006 through June 2012. Negative binomial modeling compared pre and post decal crash rates adjusted for gender, age, calendar month, and gas price. The monthly GDL citation rate was two per 10,000 drivers in the predecal and postdecal periods. Crashes were rare and rates declined similarly pre and post decal (adjusted rate ratio of postdecal vs predecal slope: 1.04 (0.97 to 1.12)). NJ's GDL decal provision was not associated with a change in citation or crash rates among young NJ drivers with learner's permits. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Passenger vehicle safety in Australasia for different driver groups.
Keall, Michael D; Newstead, Stuart
2011-05-01
Vehicle fleets in developed countries have benefitted from improved technology and regulation leading to safer vehicles. Nevertheless, for various reasons the public do not necessarily choose particular makes and models of cars according to their safety performance. This study aimed to identify areas for potential crashworthiness improvement in the Australasian fleets by studying the distribution of these fleets according to vehicle age and estimated crashworthiness. We used an existing database that encompassed the vast majority of the crash fleets studied, with existing estimates of crashworthiness generated by the Australasian Used Car Safety Ratings project. There were clear tendencies for older and younger people to be driving less safe vehicles that were also generally older. Given that older drivers are more fragile, and hence more liable to be injured in crashes, and younger drivers have a greater propensity to crash, it is clearly undesirable that these driver groups have the least crashworthy vehicles. Some suggestions are made to encourage safer vehicle choices. Copyright © 2010 Elsevier Ltd. All rights reserved.
Crash energy absorption of two-segment crash box with holes under frontal load
NASA Astrophysics Data System (ADS)
Choiron, Moch. Agus; Sudjito, Hidayati, Nafisah Arina
2016-03-01
Crash box is one of the passive safety components which designed as an impact energy absorber during collision. Crash box designs have been developed in order to obtain the optimum crashworthiness performance. Circular cross section was first investigated with one segment design, it rather influenced by its length which is being sensitive to the buckling occurrence. In this study, the two-segment crash box design with additional holes is investigated and deformation behavior and crash energy absorption are observed. The crash box modelling is performed by finite element analysis. The crash test components were impactor, crash box, and fixed rigid base. Impactor and the fixed base material are modelled as a rigid, and crash box material as bilinear isotropic hardening. Crash box length of 100 mm and frontal crash velocity of 16 km/jam are selected. Crash box material of Aluminum Alloy is used. Based on simulation results, it can be shown that holes configuration with 2 holes and ¾ length locations have the largest crash energy absorption. This condition associated with deformation pattern, this crash box model produces axisymmetric mode than other models.
Tavakoli Kashani, Ali; Rabieyan, Rahim; Besharati, Mohammad Mehdi
2016-01-01
Abstract: Background: In Iran more than 25% of crash fatalities belong to motorcycle operators and passengers in the recent years, from which about 20% are related to passenger fatalities. Methods: The aim of this study was to investigate the motorcycle operator and passenger characteristics as well as other contributory factors that may affect the fatality risk of motorcyclists involved in traffic crashes. To this end, motorcycle crash data between 2009 and 2012 was extracted from Iran traffic crash database and a logistic regression analysis was performed to obtain odds ratio estimates for each of the study variables. Results: The fatality risk of motorcyclists has a direct relationship with the number of pillion passengers carried. Results also indicate that the amount of increase in the likelihood of having a fatality in a motorcycles crash is considerably higher when the operator is accompanied by a male passenger of the same age. Furthermore, results showed that if the crash is occurred in the darkness, on curves, in rural areas and on highways, then the crash would be more likely to be fatal. Moreover, the head-on collisions, older operators, unlicensed operators and not using a safety helmet were found to increase the likelihood of a fatality in a motorcycle crash. Conclusions: Preventative measures such as, imposing stricter rules regarding safety helmet usage and confining the number of pillion passengers to one, might be implemented to reduce the fatality risk in motorcycle crashes. In addition, more appropriate infrastructures for penalizing offending motorcyclists could also reduce the frequency of law violations such as not wearing helmet or riding without motorcycle license, which in turn, would result into a reduction in the fatality risk of motorcycle crashes. PMID:26420217
Analysis of lane change crashes
DOT National Transportation Integrated Search
2003-03-01
This report defines the problem of lane change crashes in the United States (U.S.) based on data from the 1999 National Automotive Sampling System/General Estimates System (GES) crash database of the National Highway Traffic Safety Administration. Th...
Keall, Michael; Frith, William
2004-12-01
It is well established that older drivers' fragility is an important factor associated with higher levels of fatal crash involvement for older drivers. There has been less research on age-related fragility with respect to the sort of minor injuries that are more common in injury crashes. This study estimates a quantity that is related to injury fragility: the probability that a driver or a passenger of that driver will be injured in crashes involving two cars. The effects of other factors apart from drivers' fragility are included in this measure, including the fragility of the passengers, the crashworthiness of cars driven, seatbelt use by the occupants, and characteristics of crashes (including configuration and impact speed). The car occupant injury liability estimates appropriately includes these factors to adjust risk curves by age, gender, and speed limit accounting for overrepresentation in crashes associated with fragility and these other factors.
Estimation of potential safety benefits for pedestrian crash avoidance/mitigation systems.
DOT National Transportation Integrated Search
2017-04-01
This report presents and exercises a methodology to estimate the effectiveness and potential safety benefits of production pedestrian crash avoidance/mitigation systems. The analysis focuses on light vehicles moving forward and striking a pedestrian ...
Comparative analysis of PA-31-350 Chieftain (N44LV) accident and NASA crash test data
NASA Technical Reports Server (NTRS)
Hayduk, R. J.
1979-01-01
A full scale, controlled crash test to simulate the crash of a Piper PA-31-350 Chieftain airplane is described. Comparisons were performed between the simulated crash and the actual crash in order to assess seat and floor behavior, and to estimate the acceleration levels experienced in the craft at the time of impact. Photographs, acceleration histories, and the tested airplane crash data is used to augment the accident information to better define the crash conditions. Measured impact parameters are presented along with flight path velocity and angle in relation to the impact surface.
Exploring the determinants of pedestrian-vehicle crash severity in New York City.
Aziz, H M Abdul; Ukkusuri, Satish V; Hasan, Samiul
2013-01-01
Pedestrian-vehicle crashes remain a major concern in New York City due to high percentage of fatalities. This study develops random parameter logit models for explaining pedestrian injury severity levels of New York City accounting for unobserved heterogeneity in the population and across the boroughs. A log-likelihood ratio test for joint model suitability suggests that separate models for each of the boroughs should be estimated. Among many variables, road characteristics (e.g., number of lanes, grade, light condition, road surface, etc.), traffic attributes (e.g., presence of signal control, type of vehicle, etc.), and land use (e.g., parking facilities, commercial and industrial land use, etc.) are found to be statistically significant in the estimated model. The study also suggests that the set of counter measures should be different for different boroughs in the New York City and the priority ranks of countermeasures should be different as well. Copyright © 2012 Elsevier Ltd. All rights reserved.
Comparing the effects of age, BMI and gender on severe injury (AIS 3+) in motor-vehicle crashes.
Carter, Patrick M; Flannagan, Carol A C; Reed, Matthew P; Cunningham, Rebecca M; Rupp, Jonathan D
2014-11-01
The effects of age, body mass index (BMI) and gender on motor vehicle crash (MVC) injuries are not well understood and current prevention efforts do not effectively address variability in occupant characteristics. (1) Characterize the effects of age, BMI and gender on serious-to-fatal MVC injury. (2) Identify the crash modes and body regions where the effects of occupant characteristics on the numbers of occupants with injury is largest, and thereby aid in prioritizing the need for human surrogates that represent different types of occupant characteristics and adaptive restraint systems that consider these characteristics. Multivariate logistic regression was used to model the effects of occupant characteristics (age, BMI, gender), vehicle and crash characteristics on serious-to-fatal injuries (AIS 3+) by body region and crash mode using the 2000-2010 National Automotive Sampling System (NASS-CDS) dataset. Logistic regression models were applied to weighted crash data to estimate the change in the number of annual injured occupants with AIS 3+ injury that would occur if occupant characteristics were limited to their 5th percentiles (age≤17 years old, BMI≤19kg/m(2)) or male gender. Limiting age was associated with a decrease in the total number of occupants with head [8396, 95% CI 6871-9070] and thorax injuries [17,961, 95% CI 15,960-18,859] across all crash modes, decreased occupants with spine [3843, 95% CI 3065-4242] and upper extremity [3578, 95% CI 1402-4439] injuries in frontal and rollover crashes and decreased abdominal [1368, 95% CI 1062-1417] and lower extremity [4584, 95% CI 4012-4995] injuries in frontal impacts. The age effect was modulated by gender with older females more likely to have thorax and upper extremity injuries than older males. Limiting BMI was associated with 2069 [95% CI 1107-2775] fewer thorax injuries in nearside crashes, and 5304 [95% CI 4279-5688] fewer lower extremity injuries in frontal crashes. Setting gender to male resulted in fewer occupants with head injuries in farside crashes [1999, 95% CI 844-2685] and fewer thorax [5618, 95% CI 4212-6272], upper [3804, 95% CI 1781-4803] and lower extremity [2791, 95% CI 2216-3256] injuries in frontal crashes. Results indicate that age provides the greater relative contribution to injury when compared to gender and BMI, especially for thorax and head injuries. Restraint systems that account for the differential injury risks associated with age, BMI and gender could have a meaningful effect on injury in motor-vehicle crashes. Computational models of humans that represent older, high BMI, and female occupants are needed for use in simulations of particular types of crashes to develop these restraint systems. Copyright © 2014 Elsevier Ltd. All rights reserved.
[Motor vehicle crash fatalities at 30 days in Spain].
Pérez, Katherine; Pérez, Catherine; Cirera, Eva; Borrell, Carme; Plasencia, Antoni
2006-01-01
To assess level of fulfillment and utility of the hospital discharge register (HDR) as a complementary source of information for estimating the number of deaths at 30 days due to motor vehicle crashes in Spain. It is a cross-sectional study were we compared the number of people injured due to motor vehicle crashes hospitalised in a public hospital (HDR), in Spain during 2001, with the number of people severely injured or killed due to motor vehicle crashes reported by the police database (Dirección General de Tráfico, DGT) for the same year. A descriptive analysis was carried out by age, sex and region (Autonomous Community), as well as an estimation of the percentage of under-reporting of deaths by the DGT based on two assumptions. Police reported 27,272 severe injuries and 4,811 deaths during first 24 hours after the crash and after applying a fatality adjustment factor estimated 706 more deaths up to 30 days after the crash. The HDR reported 40,174 urgent hospitalisations. Of these, 1,099 died during the day of hospitalisation or within the following 30 days. The police only notified 68% of all cases that required hospitalisation. According to the number of deaths reported by police and contrasted with hospital register, estimations of the number of deaths at 30 days made by police could represent a level of under-reporting of between 3% and 6.6%, depending on the assumption considered. This study showed that the HDR is an information source that complements police statistics and is useful to estimate the number of deaths and non-fatal injuries due to motor vehicle crashes in Spain.
From a market of dreamers to economical shocks
NASA Astrophysics Data System (ADS)
Owhadi, Houman
2004-11-01
Over the past years an intense work has been undertaken to understand the origin of the crashes and bubbles of financial markets. The explanations of these crashes have been grounded on the hypothesis of behavioral and social correlations between the agents in interacting particle models or on a feedback of the stock prices on trading behaviors in mean-field models (here bubbles and crashes are seen as collective hysteria). In this paper, we will introduce a market model as a particle system with no other interaction between the agents than the fact that to be able to sell, somebody must be willing to buy and no feedback of the price on their trading behavior. We will show that this model crashes in finite estimable time. Although the age of the market does not appear in the price dynamic the population of traders taken as a whole system is maturing towards collapse. The wealth distribution among the agents follows the second law of thermodynamics and with probability one an agent (or a minority of agents) will accumulate a large portion of the total wealth, at some point this disproportion in the wealth distribution becomes unbearable for the market leading to its collapse. We believe that the origin of the collapse in our model could be of some relevance in understanding long-term economic cycles such as the Kondratiev cycle.
A classification tree based modeling approach for segment related crashes on multilane highways.
Pande, Anurag; Abdel-Aty, Mohamed; Das, Abhishek
2010-10-01
This study presents a classification tree based alternative to crash frequency analysis for analyzing crashes on mid-block segments of multilane arterials. The traditional approach of modeling counts of crashes that occur over a period of time works well for intersection crashes where each intersection itself provides a well-defined unit over which to aggregate the crash data. However, in the case of mid-block segments the crash frequency based approach requires segmentation of the arterial corridor into segments of arbitrary lengths. In this study we have used random samples of time, day of week, and location (i.e., milepost) combinations and compared them with the sample of crashes from the same arterial corridor. For crash and non-crash cases, geometric design/roadside and traffic characteristics were derived based on their milepost locations. The variables used in the analysis are non-event specific and therefore more relevant for roadway safety feature improvement programs. First classification tree model is a model comparing all crashes with the non-crash data and then four groups of crashes (rear-end, lane-change related, pedestrian, and single-vehicle/off-road crashes) are separately compared to the non-crash cases. The classification tree models provide a list of significant variables as well as a measure to classify crash from non-crash cases. ADT along with time of day/day of week are significantly related to all crash types with different groups of crashes being more likely to occur at different times. From the classification performance of different models it was apparent that using non-event specific information may not be suitable for single vehicle/off-road crashes. The study provides the safety analysis community an additional tool to assess safety without having to aggregate the corridor crash data over arbitrary segment lengths. Copyright © 2010. Published by Elsevier Ltd.
1996 Traffic Crashes, Injuries, and Fatalities: Preliminary Report
DOT National Transportation Integrated Search
1997-03-01
This report contains preliminary estimates of the number of police reported : crashes, injuries, and fatalities for 1996. Trend data are presented using : these estimates. The trend for the fatality rate per 100 million vehicle miles : of travel is a...
Shirazi, Mohammadali; Reddy Geedipally, Srinivas; Lord, Dominique
2017-01-01
Severity distribution functions (SDFs) are used in highway safety to estimate the severity of crashes and conduct different types of safety evaluations and analyses. Developing a new SDF is a difficult task and demands significant time and resources. To simplify the process, the Highway Safety Manual (HSM) has started to document SDF models for different types of facilities. As such, SDF models have recently been introduced for freeway and ramps in HSM addendum. However, since these functions or models are fitted and validated using data from a few selected number of states, they are required to be calibrated to the local conditions when applied to a new jurisdiction. The HSM provides a methodology to calibrate the models through a scalar calibration factor. However, the proposed methodology to calibrate SDFs was never validated through research. Furthermore, there are no concrete guidelines to select a reliable sample size. Using extensive simulation, this paper documents an analysis that examined the bias between the 'true' and 'estimated' calibration factors. It was indicated that as the value of the true calibration factor deviates further away from '1', more bias is observed between the 'true' and 'estimated' calibration factors. In addition, simulation studies were performed to determine the calibration sample size for various conditions. It was found that, as the average of the coefficient of variation (CV) of the 'KAB' and 'C' crashes increases, the analyst needs to collect a larger sample size to calibrate SDF models. Taking this observation into account, sample-size guidelines are proposed based on the average CV of crash severities that are used for the calibration process. Copyright © 2016 Elsevier Ltd. All rights reserved.
Crash energy absorption of two-segment crash box with holes under frontal load
DOE Office of Scientific and Technical Information (OSTI.GOV)
Choiron, Moch Agus, E-mail: agus-choiron@ub.ac.id; Sudjito,; Hidayati, Nafisah Arina
Crash box is one of the passive safety components which designed as an impact energy absorber during collision. Crash box designs have been developed in order to obtain the optimum crashworthiness performance. Circular cross section was first investigated with one segment design, it rather influenced by its length which is being sensitive to the buckling occurrence. In this study, the two-segment crash box design with additional holes is investigated and deformation behavior and crash energy absorption are observed. The crash box modelling is performed by finite element analysis. The crash test components were impactor, crash box, and fixed rigid base.more » Impactor and the fixed base material are modelled as a rigid, and crash box material as bilinear isotropic hardening. Crash box length of 100 mm and frontal crash velocity of 16 km/jam are selected. Crash box material of Aluminum Alloy is used. Based on simulation results, it can be shown that holes configuration with 2 holes and ¾ length locations have the largest crash energy absorption. This condition associated with deformation pattern, this crash box model produces axisymmetric mode than other models.« less
Assessment of aircraft crash frequency for the Hanford site 200 Area tank farms
DOE Office of Scientific and Technical Information (OSTI.GOV)
OBERG, B.D.
2003-03-22
Two factors, the near-airport crash frequency and the non-airport crash frequency, enter into the estimate of the annual aircraft crash frequency at a facility. The near-airport activities, Le., takeoffs and landings from any of the airports in a 23-statute-mile (smi) (20-nautical-mile, [nmi]) radius of the facilities, do not significantly contribute to the annual aircraft crash frequency for the 200 Area tank farms. However, using the methods of DOE-STD-3014-96, the total frequency of an aircraft crash for the 200 Area tank farms, all from non-airport operations, is calculated to be 7.10E-6/yr. Thus, DOE-STD-3014-96 requires a consequence analysis for aircraft crash. Thismore » total frequency consists of contributions from general aviation, helicopter activities, commercial air carriers and air taxis, and from large and small military aircraft. The major contribution to this total is from general aviation with a frequency of 6.77E-6/yr. All other types of aircraft have less than 1E-6/yr crash frequencies. The two individual aboveground facilities were in the realm of 1E-7/yr crash frequencies: 204-AR Waste Unloading Facility at 1.56E-7, and 242-T Evaporator at 8.62E-8. DOE-STD-3009-94, ''Preparation Guide for U.S. Department of Energy Nonreactor Nuclear Facility Documented Safety Analyses'', states that external events, such as aircraft crashes, are referred to as design basis accidents (DBA) and analyzed as such: ''if frequency of occurrence is estimated to exceed 10{sup -6}/yr conservatively calculated'' DOE-STD-3014-96 considers its method for estimating aircraft crash frequency as being conservative. Therefore, DOE-STD-3009-94 requires DBA analysis of an aircraft crash into the 200 Area tank farms. DOE-STD-3009-94 also states that beyond-DBAs are not evaluated for external events. Thus, it requires only a DBA analysis of the effects of an aircraft crash into the 200 Area tank farms. There are two attributes of an aircraft crash into a Hanford waste storage tank, which produce radiological and toxicological effects: the physical-crash, tank-dome-collapse activity, and the ensuing fire from the broken-up fuel.« less
Zhu, He; Wilson, Fernando A; Stimpson, Jim P; Araz, Ozgur M; Kim, Jungyoon; Chen, Baojiang; Wu, Li-Tzy
2016-09-01
This study examined the association between gasoline prices and hospitalizations for motorcycle and nonmotorcycle motor vehicle crash (MVC) injuries. Data on inpatient hospitalizations were obtained from the 2001 to 2010 Nationwide Inpatient Sample. Panel feasible generalized least squares models were used to estimate the effects of monthly inflation-adjusted gasoline prices on hospitalization rates for MVC injuries and to predict the impact of increasing gasoline taxes. On the basis of the available data, a $1.00 increase in the gasoline tax was associated with an estimated 8348 fewer annual hospitalizations for nonmotorcycle MVC injuries, and reduced hospital costs by $143 million. However, the increase in the gasoline tax was also associated with an estimated 3574 more annual hospitalizations for motorcycle crash injuries, and extended hospital costs by $73 million. This analysis of some existing data suggest that the increased utilization and costs of hospitalization from motorcycle crash injuries associated with an increase in the price of gasoline are likely to substantially offset reductions in nonmotorcycle MVC injuries. A policy decision to increase the gasoline tax could improve traffic safety if the increased tax is paired with public health interventions to improve motorcycle safety.
Nonfatal motor-vehicle animal crash-related injuries--United States, 2001-2002.
2004-08-06
In 2000, an estimated 6.1 million light-vehicle (e.g., passenger cars, sport utility vehicles, vans, and pickup trucks) crashes on U.S. roadways were reported to police. Of these reported crashes, 247,000 (4.0%) involved incidents in which the motor vehicle (MV) directly hit an animal on the roadway. Each year, an estimated 200 human deaths result from crashes involving animals (i.e., deaths from a direct MV animal collision or from a crash in which a driver tried to avoid an animal and ran off the roadway). To characterize nonfatal injuries from these incidents, CDC analyzed data from the National Electronic Injury Surveillance System-All Injury Program (NEISS-AIP). This report summarizes the results of that analysis, which indicated that, during 2001-2002, an estimated 26,647 MV occupants per year were involved in crashes from encounters with animals (predominantly deer) in a roadway and treated for nonfatal injuries in U.S. hospital emergency departments (EDs). Cost-effective measures targeting both drivers (e.g., speed reduction and early warnings) and animals (e.g., fencing and underpasses) are needed to reduce injuries associated with MV collisions involving animals.
Hosseinpour, Mehdi; Yahaya, Ahmad Shukri; Sadullah, Ahmad Farhan
2014-01-01
Head-on crashes are among the most severe collision types and of great concern to road safety authorities. Therefore, it justifies more efforts to reduce both the frequency and severity of this collision type. To this end, it is necessary to first identify factors associating with the crash occurrence. This can be done by developing crash prediction models that relate crash outcomes to a set of contributing factors. This study intends to identify the factors affecting both the frequency and severity of head-on crashes that occurred on 448 segments of five federal roads in Malaysia. Data on road characteristics and crash history were collected on the study segments during a 4-year period between 2007 and 2010. The frequency of head-on crashes were fitted by developing and comparing seven count-data models including Poisson, standard negative binomial (NB), random-effect negative binomial, hurdle Poisson, hurdle negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models. To model crash severity, a random-effect generalized ordered probit model (REGOPM) was used given a head-on crash had occurred. With respect to the crash frequency, the random-effect negative binomial (RENB) model was found to outperform the other models according to goodness of fit measures. Based on the results of the model, the variables horizontal curvature, terrain type, heavy-vehicle traffic, and access points were found to be positively related to the frequency of head-on crashes, while posted speed limit and shoulder width decreased the crash frequency. With regard to the crash severity, the results of REGOPM showed that horizontal curvature, paved shoulder width, terrain type, and side friction were associated with more severe crashes, whereas land use, access points, and presence of median reduced the probability of severe crashes. Based on the results of this study, some potential countermeasures were proposed to minimize the risk of head-on crashes. Copyright © 2013 Elsevier Ltd. All rights reserved.
Lord, Dominique; Washington, Simon P; Ivan, John N
2005-01-01
There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states-perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of "excess" zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to "excess" zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed-and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros.
Nilsson, Daniel; Lindman, Magdalena; Victor, Trent; Dozza, Marco
2018-04-01
Single-vehicle run-off-road crashes are a major traffic safety concern, as they are associated with a high proportion of fatal outcomes. In addressing run-off-road crashes, the development and evaluation of advanced driver assistance systems requires test scenarios that are representative of the variability found in real-world crashes. We apply hierarchical agglomerative cluster analysis to define similarities in a set of crash data variables, these clusters can then be used as the basis in test scenario development. Out of 13 clusters, nine test scenarios are derived, corresponding to crashes characterised by: drivers drifting off the road in daytime and night-time, high speed departures, high-angle departures on narrow roads, highways, snowy roads, loss-of-control on wet roadways, sharp curves, and high speeds on roads with severe road surface conditions. In addition, each cluster was analysed with respect to crash variables related to the crash cause and reason for the unintended lane departure. The study shows that cluster analysis of representative data provides a statistically based method to identify relevant properties for run-off-road test scenarios. This was done to support development of vehicle-based run-off-road countermeasures and driver behaviour models used in virtual testing. Future studies should use driver behaviour from naturalistic driving data to further define how test-scenarios and behavioural causation mechanisms should be included. Copyright © 2018 Elsevier Ltd. All rights reserved.
Russo, Brendan J; Savolainen, Peter T
2018-08-01
Median-crossover crashes are among the most hazardous events that can occur on freeways, often resulting in severe or fatal injuries. The primary countermeasure to reduce the occurrence of such crashes is the installation of a median barrier. When installation of a median barrier is warranted, transportation agencies are faced with the decision among various alternatives including concrete barriers, beam guardrail, or high-tension cable barriers. Each barrier type differs in terms of its deflection characteristics upon impact, the required installation and maintenance costs, and the roadway characteristics (e.g., median width) where installation would be feasible. This study involved an investigation of barrier performance through an in-depth analysis of crash frequency and severity data from freeway segments where high-tension cable, thrie-beam, and concrete median barriers were installed. A comprehensive manual review of crash reports was conducted to identify crashes in which a vehicle left the roadway and encroached into the median. This review also involved an examination of crash outcomes when a barrier strike occurred, which included vehicle containment, penetration, or re-direction onto the travel lanes. The manual review of crash reports provided critical supplementary information through narratives and diagrams not normally available through standard fields on police crash report forms. Statistical models were estimated to identify factors that affect the frequency, severity, and outcomes of median-related crashes, with particular emphases on differences between segments with varying median barrier types. Several roadway-, traffic-, and environmental-related characteristics were found to affect these metrics, with results varying across the different barrier types. The results of this study provide transportation agencies with important guidance as to the in-service performance of various types of median barrier. Copyright © 2018 Elsevier Ltd. All rights reserved.
Chand, Sai; Dixit, Vinayak V
2018-03-01
The repercussions from congestion and accidents on major highways can have significant negative impacts on the economy and environment. It is a primary objective of transport authorities to minimize the likelihood of these phenomena taking place, to improve safety and overall network performance. In this study, we use the Hurst Exponent metric from Fractal Theory, as a congestion indicator for crash-rate modeling. We analyze one month of traffic speed data at several monitor sites along the M4 motorway in Sydney, Australia and assess congestion patterns with the Hurst Exponent of speed (H speed ). Random Parameters and Latent Class Tobit models were estimated, to examine the effect of congestion on historical crash rates, while accounting for unobserved heterogeneity. Using a latent class modeling approach, the motorway sections were probabilistically classified into two segments, based on the presence of entry and exit ramps. This will allow transportation agencies to implement appropriate safety/traffic countermeasures when addressing accident hotspots or inadequately managed sections of motorway. Copyright © 2017 Elsevier Ltd. All rights reserved.
Amr, Sania; Braver, Elisa R.; Langenberg, Patricia; Zhan, Min; Smith, Gordon S.; Dischinger, Patricia C.
2013-01-01
PURPOSE To determine whether traffic court appearances and different court verdicts were associated with risk of subsequent speeding citations and crashes. METHODS A cohort of 29,754 Maryland drivers ticketed for speeding who either went to court or paid fines by mail in May/June 2003 was followed for 3 years. Drivers appearing in court were categorized by verdicts: 1) not guilty, 2) suspension of prosecution/no prosecution (STET/NP), 3) case dismissed, 4) probation before judgment and fines (PBJ), or 5) fines and demerit points. Cox proportional hazard models were used to estimate adjusted hazard ratios (AHR). RESULTS Court appearances were associated with lower risk of subsequent speeding citations (AHR = 0.92; 95% CI: 0.88-0.96), but higher risk of crashes (AHR=1.25; 95% CI: 1.16-1.35). PBJ was associated with significantly lower repeat speeding tickets (AHR = 0.83; 95% CI = 0.75-0.91) and a non-significant decrease in crashes (AHR = 0.87; 95% CI 0.75-1.02). Both repeat speeding tickets and subsequent crashes were significantly lower in the STET/NP group. CONCLUSIONS PBJ and STET/NP may reduce speeding and crashes, but neither verdict eliminated excess crash risk among drivers who choose court appearances. Randomized controlled evaluations of speeding countermeasures are needed to inform traffic safety policies. PMID:21684176
Evolution of the crashworthiness and aggressivity of the Spanish car fleet.
Gómez Méndez, Alvaro; Aparicio Izquierdo, Francisco; Arenas Ramírez, Blanca
2010-11-01
This paper investigates the relationship between a passenger car's year of registration and its crashworthiness and aggressivity in real-world crashes. Crashworthiness is defined as the ability of a car to protect its own occupants, and has been evaluated in single and two-car crashes. Aggressivity is defined as the ability to protect users travelling in other vehicles, and has been evaluated only in two-car crashes. The dependent variable is defined as the proportion of injured drivers who are killed or seriously injured; following previous research, we refer to this magnitude as injury severity. A decrease in the injury severity of a driver is interpreted as an improvement in the crashworthiness of their car; similarly, a decrease in the injury severity of the opponent driver is regarded as an improvement in aggressivity. Data have been extracted from the Spanish Road Accident Database, which contains information on every accident registered by the police in which at least one person was injured. Two types of regression models have been used: logistic regression models in single-car crashes, and generalised estimating equations (GEE) models in two-car crashes. GEE allow to take account of the correlation between the injury severities of drivers involved in the same crash. The independent variables considered have been: year of registration of the subject car (crashworthiness component), year of registration of the opponent car (aggressivity component), and several factors related to road, driver and environment. Our models confirm that crashworthiness has largely improved in two-car crashes: when crashing into the average opponent car, drivers of cars registered before 1985 have a significantly higher probability of being killed or seriously injured than drivers of cars registered in 2000-2005 (odds ratio: 1.80; 95% confidence interval: 1.61; 2.01). In single-car crashes, the improvement in crashworthiness is very slight (odds ratio: 1.04; 95% confidence interval: 0.93; 1.16). On the other hand, we have also found a significant worsening in aggressivity in two-car crashes: the driver of the average car has a significantly lower probability of being killed or seriously injured when crashing into a car registered before 1985, than when crashing into a car registered in 2000-2005 (odds ratio: 0.52; 95% confidence interval: 0.45; 0.60). Our results are consistent with a large amount of previous research that has reported significant improvements in the protection of car occupants. They also add to some recent studies that have found a worsening in the aggressivity of modern cars. This trend may be reflecting the impact of differences in masses and travel speeds, as well as the influence of consumer choices. The precise reasons have to be investigated. Also, the causes have to be found for so large a discrepancy between crashworthiness in single and two-car crashes. 2010 Elsevier Ltd. All rights reserved.
Drug and alcohol crash risk : a case-control study.
DOT National Transportation Integrated Search
2016-12-01
This study used a case-control design to estimate the risk of crashes involving drivers using drugs, alcohol or both. Data was collected in Virginia Beach, Virginia, for 20 months. The study obtained biological measures on more than 3,000 crash...
Identification of driver errors : overview and recommendations
DOT National Transportation Integrated Search
2002-08-01
Driver error is cited as a contributing factor in most automobile crashes, and although estimates vary by source, driver error is cited as the principal cause of from 45 to 75 percent of crashes. However, the specific errors that lead to crashes, and...
DOT National Transportation Integrated Search
1991-12-01
In 1988, an estimated 14.8 million motor vehicle crashes involved 47,000 deaths and almost 5,000,000 injuries. More than 4.8 million years of life and functioning were lost. Crash costs totalled $334 billion. They included $71 billion in out-of pocke...
Lee, Chris; Li, Xuancheng
2014-10-01
This study analyzes driver's injury severity in single- and two-vehicle crashes and compares the effects of explanatory variables among various types of crashes. The study identified factors affecting injury severity and their effects on severity levels using 5-year crash records for provincial highways in Ontario, Canada. Considering heteroscedasticity in the effects of explanatory variables on injury severity, the heteroscedastic ordered logit (HOL) models were developed for single- and two-vehicle crashes separately. The results of the models show that there exists heteroscedasticity for young drivers (≤30), safety equipment and ejection in the single-vehicle crash model, and female drivers, safety equipment and head-on collision in the two-vehicle crash models. The results also show that young car drivers have opposite effects between single-car and car-car crashes, and sideswipe crashes have opposite effects between car-car and truck-truck crashes. The study demonstrates that separate HOL models for single-vehicle and different types of two-vehicle crashes can identify differential effects of factors on driver's injury severity. Copyright © 2014 Elsevier Ltd. All rights reserved.
Farmer, C M
2001-05-01
Fatal crash rates for passenger cars and vans were compared for the last model year before four-wheel antilock brakes were introduced and the first model year for which antilock brakes were standard equipment. A prior study, based on fatal crash experience through 1995, reported that vehicle models with antilock brakes were more likely than identical but 1-year-earlier models to be involved in crashes fatal to their own occupants, but were less likely to be involved in crashes fatal to occupants of other vehicles. Overall, there was no significant effect of antilocks on the likelihood of fatal crashes. Similar analyses, based on fatal crash experience during 1996-98, yielded very different results. During 1996-98, vehicles with antilock brakes were again less likely than earlier models to be involved in crashes fatal to occupants of other vehicles, but they were no longer overinvolved in crashes fatal to their own occupants.
Implications of Functional Capacity Loss and Fatality for Vehicle Safety Prioritization.
McMurry, Timothy L; Sherwood, Chris; Poplin, Gerald S; Seguí-Gómez, María; Crandall, Jeff
2015-01-01
We investigate the use of the Functional Capacity Index (FCI) as a tool for establishing vehicle safety priorities by comparing the life year burden of injuries to the burden of fatality in frontal and side automotive crashes. We demonstrate FCI's utility by investigating in detail the resulting disabling injuries and their life year costs. We selected occupants in the 2000-2013 NASS-CDS database involved in frontal and side crashes, merged their injuries with FCI, and then used the merged data to estimate each occupant's overall functional loss. Lifetime functional loss was assessed by combining this measure of impairment with the occupants' expected future life spans, estimated from the Social Security Administration's Actuarial Life Table. Frontal crashes produce a large number of disabling injuries, particularly to the lower extremities. In our population, these crashes are estimated to account for approximately 400,000 life years lost to disability in comparison with 500,000 life years lost to fatality. Victims of side crashes experienced a higher rate of fatality but a significantly lower rate of disabling injury (0.3 vs. 1.0%), resulting in approximately 370,000 life years lost to fatality versus 50,000 life years lost to disability. The burden of disabling injuries to car crash survivors should be considered when setting vehicle safety design priorities. In frontal crashes this burden in life years is similar to the burden attributable to fatality.
DOT National Transportation Integrated Search
2017-08-01
This FMCSA-sponsored research investigated the claim that motor carriers have a substantial number of crashes in their own records that are not contained in the Motor Carrier Management Information System (MCMIS) crash file. Based on the results of t...
Time series trends of the safety effects of pavement resurfacing.
Park, Juneyoung; Abdel-Aty, Mohamed; Wang, Jung-Han
2017-04-01
This study evaluated the safety performance of pavement resurfacing projects on urban arterials in Florida using the observational before and after approaches. The safety effects of pavement resurfacing were quantified in the crash modification factors (CMFs) and estimated based on different ranges of heavy vehicle traffic volume and time changes for different severity levels. In order to evaluate the variation of CMFs over time, crash modification functions (CMFunctions) were developed using nonlinear regression and time series models. The results showed that pavement resurfacing projects decrease crash frequency and are found to be more safety effective to reduce severe crashes in general. Moreover, the results of the general relationship between the safety effects and time changes indicated that the CMFs increase over time after the resurfacing treatment. It was also found that pavement resurfacing projects for the urban roadways with higher heavy vehicle volume rate are more safety effective than the roadways with lower heavy vehicle volume rate. Based on the exploration and comparison of the developed CMFucntions, the seasonal autoregressive integrated moving average (SARIMA) and exponential functional form of the nonlinear regression models can be utilized to identify the trend of CMFs over time. Copyright © 2017 Elsevier Ltd. All rights reserved.
A new analysis of the effects of the Asian crisis of 1997 on emergent markets
NASA Astrophysics Data System (ADS)
Mariani, M. C.; Liu, Y.
2007-07-01
This work is devoted to the study of the Asian crisis of 1997, and its consequences on emerging markets. We have done so by means of a phase transition model. We have analyzed the crashes on leading indices of Hong Kong (HSI), Turkey (XU100), Mexico (MMX), Brazil (BOVESPA) and Argentina (MERVAL). We were able to obtain optimum values for the critical date, corresponding to the most probable date of the crash. The estimation of the critical date was excellent except for the MERVAL index; this improvement is due to a previous analysis of the parameters involved. We only used data from before the true crash date in order to obtain the predicted critical date. This article's conclusions are largely obtained via ad hoc empirical methods.
The effects of drug and alcohol consumption on driver injury severities in single-vehicle crashes.
Behnood, Ali; Mannering, Fred L
2017-07-04
It is well known that alcohol and drugs influence driving behavior by affecting the central nervous system, awareness, vision, and perception/reaction times, but the resulting effect on driver injuries in car crashes is not fully understood. The purpose of this study was to identify factors affecting the injury severities of unimpaired, alcohol-impaired, and drug-impaired drivers. The current article applies a random parameters logit model to study the differences in injury severities among unimpaired, alcohol-impaired, and drug-impaired drivers. Using data from single-vehicle crashes in Cook County, Illinois, over a 9-year period from January 1, 2004, to December 31, 2012, separate models for unimpaired, alcohol-impaired, and drug-impaired drivers were estimated. A wide range of variables potentially affecting driver injury severity was considered, including roadway and environmental conditions, driver attributes, time and location of the crash, and crash-specific factors. The estimation results show significant differences in the determinants of driver injury severities across groups of unimpaired, alcohol-impaired, and drug-impaired drivers. The findings also show that unimpaired drivers are understandably more responsive to variations in lighting, adverse weather, and road conditions, but these drivers also tend to have much more heterogeneity in their behavioral responses to these conditions, relative to impaired drivers. In addition, age and gender were found to be important determinants of injury severity, but the effects varied significantly across all drivers, particularly among alcohol-impaired drivers. The model estimation results show that statistically significant differences exist in driver injury severities among the unimpaired, alcohol-impaired, and drug-impaired driver groups considered. Specifically, we find that unimpaired drivers tend to have more heterogeneity in their injury outcomes in the presence potentially adverse weather and road surface conditions. This makes sense because one would expect unimpaired drivers to apply their full knowledge/judgment range to deal with these conditions, and the variability of this range across the driver population (with different driving experiences, etc.) should be great. In contrast, we find, for the most part, that alcohol-impaired and drug-impaired drivers have far less heterogeneity in the factors that affect injury severity, suggesting an equalizing effect resulting from the decision-impairing substance.
Toll facilities in the United States : bridges, roads, tunnels, ferries
DOT National Transportation Integrated Search
2000-09-01
Speeding is one of the most prevalent factors related to traffic crashes. The economic cost to society of speeding-related crashes is estimated to be $27.7 billion annually. In 1998, speeding was a factor in about one-third of all fatal crashes. Pres...
Direct medical costs of motorcycle crashes in Ontario
Pincus, Daniel; Wasserstein, David; Nathens, Avery B.; Bai, Yu Qing; Redelmeier, Donald A.; Wodchis, Walter P.
2017-01-01
BACKGROUND: There is no reliable estimate of costs incurred by motorcycle crashes. Our objective was to calculate the direct costs of all publicly funded medical care provided to individuals after motorcycle crashes compared with automobile crashes. METHODS: We conducted a population-based, matched cohort study of adults in Ontario who presented to hospital because of a motorcycle or automobile crash from 2007 through 2013. For each case, we identified 1 control absent a motor vehicle crash during the study period. Direct costs for each case and control were estimated in 2013 Canadian dollars from the payer perspective using methodology that links health care use to individuals over time. We calculated costs attributable to motorcycle and automobile crashes within 2 years using a difference-in-differences approach. RESULTS: We identified 26 831 patients injured in motorcycle crashes and 281 826 injured in automobile crashes. Mean costs attributable to motorcycle and automobile crashes were $5825 and $2995, respectively (p < 0.001). The rate of injury was triple for motorcycle crashes compared with automobile crashes (2194 injured annually/100 000 registered motorcycles v. 718 injured annually/100 000 registered automobiles; incidence rate ratio [IRR] 3.1, 95% confidence interval [CI] 2.8 to 3.3, p < 0.001). Severe injuries, defined as those with an Abbreviated Injury Scale ≥ 3, were 10 times greater (125 severe injuries annually/100 000 registered motorcycles v. 12 severe injuries annually/100 000 registered automobiles; IRR 10.4, 95% CI 8.3 to 13.1, p < 0.001). INTERPRETATION: Considering both the attributable cost and higher rate of injury, we found that each registered motorcycle in Ontario costs the public health care system 6 times the amount of each registered automobile. Medical costs may provide an additional incentive to improve motorcycle safety. PMID:29158454
Comparing the Effects of Age, BMI and Gender on Severe Injury (AIS 3+) in Motor-Vehicle Crashes
Carter, Patrick M.; Flannagan, Carol A.C.; Reed, Matthew P.; Cunningham, Rebecca M.; Rupp, Jonathan D.
2016-01-01
Background The effects of age, body mass index (BMI) and gender on motor vehicle crash (MVC) injuries are not well understood and current prevention efforts do not effectively address variability in occupant characteristics. Objectives 1) Characterize the effects of age, BMI and gender on serious-to-fatal MVC injury 2) Identify the crash modes and body regions where the effects of occupant characteristics onthe numbers of occupants with injuryis largest, and thereby aid in prioritizing the need forhuman surrogates that the represent different types of occupant characteristics and adaptive restraint systems that consider these characteristics. Methods Multivariate logistic regression was used to model the effects of occupant characteristics (age, BMI, gender), vehicle and crash characteristics on serious-to-fatal injuries (AIS 3+) by body region and crash mode using the 2000-2010 National Automotive Sampling System (NASS-CDS) dataset. Logistic regression models were applied to weighted crash data to estimate the change in the number of annual injured occupants with AIS 3+ injury that would occur if occupant characteristics were limited to their 5th percentiles (age ≤ 17 years old, BMI ≤ 19 kg/m2) or male gender. Results Limiting age was associated with a decrease inthe total number of occupants with head [8,396, 95% CI 6,871-9,070] and thorax injuries [17,961, 95% CI 15,960 – 18,859] across all crash modes, decreased occupants with spine [3,843, 95% CI 3,065 – 4,242] and upper extremity [3,578, 95% CI 1,402 – 4,439] injuries in frontal and rollover crashes and decreased abdominal [1,368, 95% CI 1,062 – 1,417] and lower extremity [4,584, 95% CI 4,012 – 4,995] injuries in frontal impacts. The age effect was modulated by gender with older females morelikely to have thorax and upper extremity injuries than older males. Limiting BMI was associated with 2,069 [95% CI 1,107 – 2,775] fewer thorax injuries in nearside crashes, and 5,304 [95% CI 4,279 – 5,688] fewer lower extremity injuries in frontal crashes. Setting gender to male resulted in fewer occupants with head injuries in farside crashes [1,999, 95% CI 844 – 2,685] and fewer thorax [5,618, 95% CI 4,212 – 6,272], upper [3,804, 95% CI 1,781 – 4,803] and lower extremity [2,791, 95% CI 2,216 – 3,256] injuries in frontal crashes. Results indicate that age provides the greater relative contribution to injury when compared to gender and BMI, especially for thorax and head injuries. Conclusions Restraint systems that account for the differential injury risks associated with age, BMI and gender could have a meaningful effect on injury in motor-vehicle crashes. Computational models of humans that represent older, high BMI, and female occupants are needed for use in simulations of particular types of crashes to develop these restraint systems. PMID:25061920
Impact of roadway geometric features on crash severity on rural two-lane highways.
Haghighi, Nima; Liu, Xiaoyue Cathy; Zhang, Guohui; Porter, Richard J
2018-02-01
This study examines the impact of a wide range of roadway geometric features on the severity outcomes of crashes occurred on rural two-lane highways. We argue that crash data have a hierarchical structure which needs to be addressed in modeling procedure. Moreover, most of previous studies ignored the impact of geometric features on crash types when developing crash severity models. We hypothesis that geometric features are more likely to determine crash type, and crash type together with other occupant, environmental and vehicle characteristics determine crash severity outcome. This paper presents an application of multilevel models to successfully capture both hierarchical structure of crash data and indirect impact of geometric features on crash severity. Using data collected in Illinois from 2007 to 2009, multilevel ordered logit model is developed to quantify the impact of geometric features and environmental conditions on crash severity outcome. Analysis results revealed that there is a significant variation in severity outcomes of crashes occurred across segments which verifies the presence of hierarchical structure. Lower risk of severe crashes is found to be associated with the presence of 10-ft lane and/or narrow shoulders, lower roadside hazard rate, higher driveway density, longer barrier length, and shorter barrier offset. The developed multilevel model offers greater consistency with data generating mechanism and can be utilized to evaluate safety effects of geometric design improvement projects. Published by Elsevier Ltd.
Fatal crash involvement and laws against alcohol-impaired driving.
Zador, P L; Lund, A K; Fields, M; Weinberg, K
1989-01-01
It is estimated that in 1985 about 1,560 fewer drivers were involved in fatal crashes because of three types of drinking-driving laws. The laws studied were per se laws that define driving under the influence using blood alcohol concentration (BAC) thresholds; laws that provide for administrative license suspension or revocation prior to conviction for driving under the influence (often referred to as "administrative per se" laws); and laws that mandate jail or community service for first convictions of driving under the influence. It is estimated that if all 48 of the contiguous states adopted laws similar to those studied here, and if these new laws had effects comparable to those reported here, another 2,600 fatal driver involvements could be prevented each year. During hours when typically at least half of all fatally injured drivers have a BAC over 0.10 percent, administrative suspension/revocation is estimated to reduce the involvement of drivers in fatal crashes by about 9 percent; during the same hours, first offense mandatory jail/community service laws are estimated to have reduced driver involvement by about 6 percent. The effect of per se laws was estimated to be a 6 percent reduction during hours when fatal crashes typically are less likely to involve alcohol. These results are based on analyses of drivers involved in fatal crashes in the 48 contiguous states of the United States during the years 1978 to 1985.
Wang, Jung-Han; Abdel-Aty, Mohamed; Wang, Ling
2017-07-01
There have been plenty of studies intended to use different methods, for example, empirical Bayes before-after methods, to get accurate estimation of CMFs. All of them have different assumptions toward crash count if there was no treatment. Additionally, another major assumption is that multiple sites share the same true CMF. Under this assumption, the CMF at an individual intersection is randomly drawn from a normally distributed population of CMFs at all intersections. Since CMFs are non-zero values, the population of all CMFs might not follow normal distributions, and even if it does, the true mean of CMFs at some intersections may be different from that at others. Therefore, a bootstrap method based on before-after empirical Bayes theory was proposed to estimate CMFs, but it did not make distributional assumptions. This bootstrap procedure has the added benefit of producing a measure of CMF stability. Furthermore, based on the bootstrapped CMF, a new CMF precision rating method was proposed to evaluate the reliability of CMFs. This study chose 29 urban four-legged intersections as treated sites, and their controls were changed from stop-controlled to signal-controlled. Meanwhile, 124 urban four-legged stop-controlled intersections were selected as reference sites. At first, different safety performance functions (SPFs) were applied to five crash categories, and it was found that each crash category had different optimal SPF form. Then, the CMFs of these five crash categories were estimated using the bootstrap empirical Bayes method. The results of the bootstrapped method showed that signalization significantly decreased Angle+Left-Turn crashes, and its CMF had the highest precision. While, the CMF for Rear-End crashes was unreliable. For KABCO, KABC, and KAB crashes, their CMFs were proved to be reliable for the majority of intersections, but the estimated effect of signalization may be not accurate at some sites. Copyright © 2017 Elsevier Ltd. All rights reserved.
Gasoline prices and traffic crashes in Alabama, 1999-2009.
Chi, Guangqing; McClure, Timothy E; Brown, David B
2012-09-01
The price of gasoline has been found to be negatively associated with traffic crashes in a limited number of studies. However, most of the studies have focused either on fatal crashes only or on all crashes but measured over a very short time period. In this study, we examine gasoline price effects on all traffic crashes by demographic groups in the state of Alabama from 1999 to 2009. Using negative binomial regression techniques to examine monthly data from 1999 to 2009 in the state of Alabama, we estimate the effects of changes in gasoline price on changes in automobile crashes. We also examine how these effects differ by age group (16-20, 21-25, 26-30, 31-64, and 65+), gender (male and female), and race/ethnicity (non-Hispanic white, non-Hispanic black, and Hispanic). The results show that gasoline prices have both short-term and long-term effects on reducing total traffic crashes and crashes of each age, gender, and race/ethnicity group (except Hispanic due to data limitations). The short-term and long-term effects are not statistically different for each individual demographic group. Gasoline prices have a stronger effect in reducing crashes involving drivers aged 16 to 20 than crashes involving drivers aged 31 to 64 and 65+ in the short term; the effects, however, are not statistically different across other demographic groups. Although gasoline price increases are not favored, our findings show that gasoline price increases (or decreases) are associated with reductions (or increases) in the incidence of traffic crashes. If gasoline prices had remained at the 1999 level of $1.41 from 1999 to 2009, applying the estimated elasticities would result in a predicted increase in total crashes of 169,492 (or 11.3%) from the actual number of crashes. If decision makers wish to reduce traffic crashes, increasing gasoline taxes is a possible option-however, doing so would increase travel costs and lead to equity concerns. These findings may help to shape transportation safety planning and policy making.
Antilock brakes and the risk of driver injury in a crash: a case-control study.
Cummings, Peter; Grossman, David C
2007-09-01
While antilock brakes can improve steering and reduce stopping distance in some test situations, there is little evidence that they reduce the risk of crash-related injury. We sought to estimate the association between presence of antilock brakes and the risk of driver injury. We conducted a case-control study using claims data from the Insurance Corporation of British Columbia, Canada, for passenger vehicles insured during July 1, 2003, to June 30, 2004. Cases were 5000 vehicles with a driver crash injury during the study period. Controls were 49,994 vehicles insured at the mid-point of the study interval. The adjusted risk ratio for a crash with driver injury in a vehicle with antilock brakes was 1.06 (95% confidence interval, 0.95-1.17), compared with a vehicle without antilock brakes. If this estimated association is causal, antilock brakes do not prevent crash-related driver injuries.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wenzel, Tom P.
2016-05-20
Previous analyses have indicated that mass reduction is associated with an increase in crash frequency (crashes per VMT), but a decrease in fatality or casualty risk once a crash has occurred, across all types of light-duty vehicles. These results are counter-intuitive: one would expect that lighter, and perhaps smaller, vehicles have better handling and shorter braking distances, and thus should be able to avoid crashes that heavier vehicles cannot. And one would expect that heavier vehicles would have lower risk once a crash has occurred than lighter vehicles. However, these trends occur under several alternative regression model specifications. This reportmore » tests whether these results continue to hold after accounting for crash severity, by excluding crashes that result in relatively minor damage to the vehicle(s) involved in the crash. Excluding non-severe crashes from the initial LBNL Phase 2 and simultaneous two-stage regression models for the most part has little effect on the unexpected relationships observed in the baseline regression models. This finding suggests that other subtle differences in vehicles and/or their drivers, or perhaps biases in the data reported in state crash databases, are causing the unexpected results from the regression models.« less
Braver, Elisa R; Scerbo, Marge; Kufera, Joseph A; Alexander, Melvin T; Volpini, Karen; Lloyd, Joseph P
2008-03-01
After automakers were allowed the option of using sled tests for unbelted male dummies to certify the frontal crash performance of vehicles, most frontal air bags were depowered, starting in model year 1998, to reduce deaths and serious injuries arising from air bag deployments. Concern has been expressed that depowering air bags could compromise the protection of adult occupants. This study aimed to determine the effects of changes in air bag designs on risk of death among front-seat occupants. Deaths among drivers and right-front passengers per involvement in frontal police-reported crashes during calendar years 1998-2004 were compared among vehicles with sled-certified air bags (model years 1998-2004) and first-generation air bags (model years 1994-97). Frontal crash deaths were identified from the Fatality Analysis Reporting System. National estimates of police-reported crashes were derived from the National Automotive Sampling System/General Estimates System. Sled certification status for model years 1998-2004 was ascertained from published federal data and a survey of automobile manufacturers. Passenger cars, pickup trucks, sport utility vehicles, and minivans were studied. Stratified analyses were done to compute risk ratios (RR) and 95% confidence intervals (95% CI) for driver and right-front passenger deaths by air bag generation and crash, vehicle, and driver characteristics. In frontal crashes, overall RRs were 0.89 for driver deaths (95% CI = 0.74-1.08) and 0.89 for right-front passenger deaths (95% CI = 0.74-1.07) in sled-certified vehicles compared with first-generation air bag-equipped vehicles. Child right-front passengers (ages 0-4, 5-9) in vehicles with sled-certified air bags had statistically significant reductions in risk of dying in frontal collisions, including a 65% reduced risk among ages 0-4 (RR = 0.35; 95% CI = 0.21-0.60). No differences in effects of sled-certified air bags were observed between drivers ages 15-59 and 60-74 in sled-certified vehicles, both of whom had RRs slightly below 0.90 (non-significant). Among occupants killed in sled-certified vehicles, police-reported belt use was somewhat higher than in first-generation vehicles. No differences in risk of frontal crash deaths were observed between adult occupants with sled-certified and first-generation air bags. Consistent with reports of decreases in air bag-related deaths, this study observed significant reductions in frontal deaths among child passengers seated in the right-front position in sled-certified vehicles. Higher restraint use rates among children in sled-certified vehicles and other vehicle design changes might have contributed partially to these reductions.
Scherer, Michael; Fell, James C; Thomas, Sue; Voas, Robert B
2015-01-01
In this study, we aimed to determine whether three minimum legal drinking age 21 (MLDA-21) laws-dram shop liability, responsible beverage service (RBS) training, and state control of alcohol sales-have had an impact on underage drinking and driving fatal crashes using annual state-level data, and compared states with strong laws to those with weak laws to examine their effect on beer consumption and fatal crash ratios. Using the Fatality Analysis Reporting System, we calculated the ratio of drinking to nondrinking drivers under age 21 involved in fatal crashes as our key outcome measure. We used structural equation modeling to evaluate the three MLDA-21 laws. We controlled for covariates known to impact fatal crashes including: 17 additional MLDA-21 laws; administrative license revocation; blood alcohol concentration limits of.08 and.10 for driving; seat belt laws; sobriety checkpoint frequency; unemployment rates; and vehicle miles traveled. Outcome variables, in addition to the fatal crash ratios of drinking to nondrinking drivers under age 21 included state per capita beer consumption. Dram shop liability laws were associated with a 2.4% total effect decrease (direct effects: β =.019, p =.018). Similarly, RBS training laws were associated with a 3.6% total effect decrease (direct effect: β =.048, p =.001) in the ratio of drinking to nondrinking drivers under age 21 involved in fatal crashes. There was a significant relationship between dram shop liability law strength and per capita beer consumption, F (4, 1528) = 24.32, p <.001, partial η(2) =.016, showing states with strong dram shop liability laws (Mean (M) = 1.276) averaging significantly lower per capita beer consumption than states with weak laws (M = 1.340). Dram shop liability laws and RBS laws were both associated with significantly reduced per capita beer consumption and fatal crash ratios. In practical terms, this means that dram shop liability laws are currently associated with saving an estimated 64 lives in the 45 jurisdictions that currently have the law. If the remaining 6 states adopted the dram shop law, an additional 9 lives could potentially be saved annually. Similarly, RBS training laws are associated with saving an estimated 83 lives in the 37 jurisdictions that currently have the laws. If the remaining 14 states adopted these RBS training laws, we estimate that an additional 28 lives could potentially be saved.
Scherer, Michael; Fell, James C.; Thomas, Sue; Voas, Robert B.
2015-01-01
Objectives In this study, we aimed to determine whether three minimum legal drinking age 21 (MLDA-21) laws—dram shop liability, responsible beverage service (RBS) training, and state control of alcohol sales—have had an impact on underage drinking-and-driving fatal crashes using annual state-level data, and compared states with strong laws to those with weak laws to examine their effect on beer consumption and fatal crash ratios. Methods Using the Fatality Analysis Reporting System, we calculated the ratio of drinking to nondrinking drivers under age 21 involved in fatal crashes as our key outcome measure. We used structural equation modeling to evaluate the three MLDA-21 laws. We controlled for covariates known to impact fatal crashes including: 17 additional MLDA-21 laws; administrative license revocation; blood alcohol concentration limits of .08 and .10 for driving; seat belt laws; sobriety checkpoint frequency; unemployment rates; and vehicle miles traveled. Outcome variables, in addition to the fatal crash ratios of drinking to nondrinking drivers under age 21 included state per capita beer consumption. Results Dram shop liability laws were associated with a 2.4% total effect decrease (direct effects: β = .019, p = .018). Similarly, RBS training laws were associated with a 3.6% total effect decrease (direct effects: β = .048, p = .001) in the ratio of drinking to nondrinking drivers under age 21 involved in fatal crashes. There was a significant relationship between dram shop liability law strength and per capita beer consumption, F (4, 1528) = 24.32, p < .001, partial η2 = .016, showing states with strong dram shop liability laws (Mean (M) = 1.276) averaging significantly lower per capita beer consumption than states with weak laws (M = 1.340). Conclusions Dram shop liability laws and RBS laws were both associated with significantly reduced per capita beer consumption and fatal crash ratios. In practical terms, this means that dram shop liability laws are currently associated with saving an estimated 64 lives in the 45 jurisdictions that currently have the law. If the remaining 6 states adopted the dram shop law, an additional 9 lives could potentially be saved annually. Similarly, RBS training laws are associated with saving an estimated 83 lives in the 37 jurisdictions that currently have the law. If the remaining 14 states adopted these RBS training laws, we estimate that an additional 28 lives could potentially be saved. PMID:26436244
Saha, Dibakar; Alluri, Priyanka; Gan, Albert; Wu, Wanyang
2018-02-21
The objective of this study was to investigate the relationship between bicycle crash frequency and their contributing factors at the census block group level in Florida, USA. Crashes aggregated over the census block groups tend to be clustered (i.e., spatially dependent) rather than randomly distributed. To account for the effect of spatial dependence across the census block groups, the class of conditional autoregressive (CAR) models were employed within the hierarchical Bayesian framework. Based on four years (2011-2014) of crash data, total and fatal-and-severe injury bicycle crash frequencies were modeled as a function of a large number of variables representing demographic and socio-economic characteristics, roadway infrastructure and traffic characteristics, and bicycle activity characteristics. This study explored and compared the performance of two CAR models, namely the Besag's model and the Leroux's model, in crash prediction. The Besag's models, which differ from the Leroux's models by the structure of how spatial autocorrelation are specified in the models, were found to fit the data better. A 95% Bayesian credible interval was selected to identify the variables that had credible impact on bicycle crashes. A total of 21 variables were found to be credible in the total crash model, while 18 variables were found to be credible in the fatal-and-severe injury crash model. Population, daily vehicle miles traveled, age cohorts, household automobile ownership, density of urban roads by functional class, bicycle trip miles, and bicycle trip intensity had positive effects in both the total and fatal-and-severe crash models. Educational attainment variables, truck percentage, and density of rural roads by functional class were found to be negatively associated with both total and fatal-and-severe bicycle crash frequencies. Published by Elsevier Ltd.
DOT National Transportation Integrated Search
2004-08-01
Significant variations in the reporting of hazardous materials incident costs are illustrated using a case study of the March 2004 crash of a fuel tanker truck on Interstate 95 in Bridgeport, Connecticut. Three separate cost estimates are presented, ...
DOT National Transportation Integrated Search
2017-08-01
This study estimated a significant amount of underreporting to the MCMIS crash file by the States, for the carriers who cooperated in the study. For the study carriers, it appears that the MCMIS file contained about 66 percent of their reportable cra...
DOT National Transportation Integrated Search
1998-11-01
In this annual report, Traffic Safety Facts 1997: A Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System, the National Highway Traffic Safety Administration (NHTSA) presents descriptive ...
DOT National Transportation Integrated Search
2007-01-01
In this annual report, Traffic Safety Facts 2007: A Compilation of Motor Vehicle Crash Data from the Fatality : Analysis Reporting System and the General Estimates System, the National Highway Traffic Safety Administration : (NHTSA) presents descript...
DOT National Transportation Integrated Search
2008-01-01
In this annual report, Traffic Safety Facts 2008: A Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System, the National Highway Traffic Safety Administration (NHTSA) presents descriptive ...
DOT National Transportation Integrated Search
2009-01-01
In this annual report, Traffic Safety Facts 2009: A Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System, the National Highway Traffic Safety Administration (NHTSA) presents descriptive ...
Cafiso, Salvatore; D'Agostino, Carmelo; Persaud, Bhagwant
2017-04-03
A new European Union (EU) regulation for safety barriers, which is based on performance, has encouraged road agencies to perform an upgrade of old barriers, with the expectation that there will be safety benefits at the retrofitted sites. The new class of barriers was designed and installed in compliance with the 1998 (European Norm) EN 1317 standards for road restraint systems, which lays down common requirements for the testing and certification of road restraint systems in all countries of the European Committee for Standardization (CEN). Both the older and new barriers are made of steel and are installed in such a way as to avoid vehicle intrusion, but the older ones are thought to be only effective at low speeds and large angles of impact. The new standard seeks to remedy this by providing better protection at higher speeds. This article seeks to quantify the effect on the frequency of fatal and injury crashes of retrofitting motorways with barriers meeting the new standards. The estimation of the crash modification was carried out by performing an empirical Bayes before-after analysis based on data from the A18 Messina-Catania motorway in Italy. The methodology has the great advantage to account for the regression to the mean effects. Besides, to account for time trend effects and dispersion of crash data, a modified calibration methodology of safety performance was used. This study, based on data collected on 76 km of motorway in the period 2000-2012, derived Crash Modification Factor point estimates that indicate reductions of 72% for run-off-road fatal and injury crashes and 38% in total fatal and injury crashes that could be expected by upgrading an old safety barrier by complying with new EU 1317 standards. The estimated benefit-cost ratio of 5.57 for total crashes indicates that the treatment is cost effective. The magnitude of this benefit indicates that the retrofits are cost-effective even for total crashes and should continue in any European country inasmuch as the estimated Crash Modification Factors are based on treatment sites that are reasonably representative of all European motorways.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wenzel, Tom
NHTSA recently completed a logistic regression analysis updating its 2003, 2010, and 2012 studies of the relationship between vehicle mass and US fatality risk per vehicle mile traveled (VMT; Kahane 2010, Kahane 2012, Puckett 2016). The new study updates the 2012 analysis using FARS data from 2005 to 2011 for model year 2003 to 2010. Using the updated databases, NHTSA estimates that reducing vehicle mass by 100 pounds while holding footprint fixed would increase fatality risk per VMT by 1.49% for lighter-than-average cars and by 0.50% for heavierthan- average cars, but reduce risk by 0.10% for lighter-than-average light-duty trucks, bymore » 0.71% for heavier-than-average light-duty trucks, and by 0.99% for CUVs/minivans. Using a jack knife method to estimate the statistical uncertainty of these point estimates, NHTSA finds that none of these estimates are statistically significant at the 95% confidence level; however, the 1.49% increase in risk associated with mass reduction in lighter-than-average cars, and the 0.71% and 0.99% decreases in risk associated with mass reduction in heavier-than-average light trucks and CUVs/minivans, are statistically significant at the 90% confidence interval. The effect of mass reduction on risk that NHTSA estimated in 2016 is more beneficial than in its 2012 study, particularly for light trucks and CUVs/minivans. The 2016 NHTSA analysis estimates that reducing vehicle footprint by one square foot while holding mass constant would increase fatality risk per VMT by 0.28% in cars, by 0.38% in light trucks, and by 1.18% in CUVs and minivans.This report replicates the 2016 NHTSA analysis, and reproduces their main results. This report uses the confidence intervals output by the logistic regression models, which are smaller than the intervals NHTSA estimated using a jack-knife technique that accounts for the sampling error in the FARS fatality and state crash data. In addition to reproducing the NHTSA results, this report also examines the NHTSA data in slightly different ways to get a deeper understanding of the relationship between vehicle weight, footprint, and safety. The results of the NHTSA baseline results, and these alternative analyses, are summarized in Table ES.1; statistically significant estimates, based on the confidence intervals output by the logistic regression models, are shown in red in the tables. We found that NHTSA’s reasonable assumption that all vehicles will have ESC installed by 2017 in its baseline regression model slightly increases the estimated increase in risk from mass reduction in cars, but substantially decreases the estimated increase in risk from footprint reduction in all three vehicle types (Alternative 1 in Table ES.1; explained in more detail in Section 2.1 of this report). This is because NHTSA projects ESC to substantially reduce the number of fatalities in rollovers and crashes with stationary objects, and mass reduction appears to reduce risk, while footprint reduction appears to increase risk, in these types of crashes, particularly in cars and CUVs/minivans. A single regression model including all crash types results in slightly different estimates of the relationship between decreasing mass and risk, as shown in Alternative 2 in Table ES.1.« less
Rising gasoline prices increase new motorcycle sales and fatalities.
Zhu, He; Wilson, Fernando A; Stimpson, Jim P; Hilsenrath, Peter E
2015-12-01
We examined whether sales of new motorcycles was a mechanism to explain the relationship between motorcycle fatalities and gasoline prices. The data came from the Motorcycle Industry Council, Energy Information Administration and Fatality Analysis Reporting System for 1984-2009. Autoregressive integrated moving average (ARIMA) regressions estimated the effect of inflation-adjusted gasoline price on motorcycle sales and logistic regressions estimated odds ratios (ORs) between new and old motorcycle fatalities when gasoline prices increase. New motorcycle sales were positively correlated with gasoline prices (r = 0.78) and new motorcycle fatalities (r = 0.92). ARIMA analysis estimated that a US$1 increase in gasoline prices would result in 295,000 new motorcycle sales and, consequently, 233 new motorcycle fatalities. Compared to crashes on older motorcycle models, those on new motorcycles were more likely to be young riders, occur in the afternoon, in clear weather, with a large engine displacement, and without alcohol involvement. Riders on new motorcycles were more likely to be in fatal crashes relative to older motorcycles (OR 1.14, 95 % confidence interval (CI) 1.02-1.28) when gasoline prices increase. Our findings suggest that, in response to increasing gasoline prices, people tend to purchase new motorcycles, and this is accompanied with significantly increased crash risk. There are several policy mechanisms that can be used to lower the risk of motorcycle crash injuries through the mechanism of gas prices and motorcycle sales such as raising awareness of motorcycling risks, enhancing licensing and testing requirements, limiting motorcycle power-to-weight ratios for inexperienced riders, and developing mandatory training programs for new riders.
NASA Astrophysics Data System (ADS)
Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.
2017-09-01
Traffic safety is a major concern in the transportation industry due to immense monetary and emotional burden caused by crashes of various severity levels, especially the injury and fatality ones. To reduce such crashes on all public roads, the safety management processes are commonly implemented which include network screening, problem diagnosis, countermeasure identification, and project prioritization. The selection of countermeasures for potential mitigation of crashes is governed by the influential factors which impact roadway crashes. Crash prediction model is the tool widely adopted by safety practitioners or researchers to link various influential factors to crash occurrences. Many different approaches have been used in the past studies to develop better fitting models which also exhibit prediction accuracy. In this study, a crash prediction model is developed to investigate the vehicular crashes occurring at roadway segments. The spatial and temporal nature of crash data is exploited to form a spatiotemporal model which accounts for the different types of heterogeneities among crash data and geometric or traffic flow variables. This study utilizes the Poisson lognormal model with random effects, which can accommodate the yearly variations in explanatory variables and the spatial correlations among segments. The dependency of different factors linked with roadway geometric, traffic flow, and road surface type on vehicular crashes occurring at segments was established as the width of lanes, posted speed limit, nature of pavement, and AADT were found to be correlated with vehicle crashes.
A review of the analytical simulation of aircraft crash dynamics
NASA Technical Reports Server (NTRS)
Fasanella, Edwin L.; Carden, Huey D.; Boitnott, Richard L.; Hayduk, Robert J.
1990-01-01
A large number of full scale tests of general aviation aircraft, helicopters, and one unique air-to-ground controlled impact of a transport aircraft were performed. Additionally, research was also conducted on seat dynamic performance, load-limiting seats, load limiting subfloor designs, and emergency-locator-transmitters (ELTs). Computer programs were developed to provide designers with methods for predicting accelerations, velocities, and displacements of collapsing structure and for estimating the human response to crash loads. The results of full scale aircraft and component tests were used to verify and guide the development of analytical simulation tools and to demonstrate impact load attenuating concepts. Analytical simulation of metal and composite aircraft crash dynamics are addressed. Finite element models are examined to determine their degree of corroboration by experimental data and to reveal deficiencies requiring further development.
Built environment effects on cyclist injury severity in automobile-involved bicycle crashes.
Chen, Peng; Shen, Qing
2016-01-01
This analysis uses a generalized ordered logit model and a generalized additive model to estimate the effects of built environment factors on cyclist injury severity in automobile-involved bicycle crashes, as well as to accommodate possible spatial dependence among crash locations. The sample is drawn from the Seattle Department of Transportation bicycle collision profiles. This study classifies the cyclist injury types as property damage only, possible injury, evident injury, and severe injury or fatality. Our modeling outcomes show that: (1) injury severity is negatively associated with employment density; (2) severe injury or fatality is negatively associated with land use mixture; (3) lower likelihood of injuries is observed for bicyclists wearing reflective clothing; (4) improving street lighting can decrease the likelihood of cyclist injuries; (5) posted speed limit is positively associated with the probability of evident injury and severe injury or fatality; (6) older cyclists appear to be more vulnerable to severe injury or fatality; and (7) cyclists are more likely to be severely injured when large vehicles are involved in crashes. One implication drawn from this study is that cities should increase land use mixture and development density, optimally lower posted speed limits on streets with both bikes and motor vehicles, and improve street lighting to promote bicycle safety. In addition, cyclists should be encouraged to wear reflective clothing. Copyright © 2015 Elsevier Ltd. All rights reserved.
Estimating Rates of Motor Vehicle Crashes Using Medical Encounter Data: A Feasibility Study
2015-11-05
used to develop more detailed predictive risk models as well as strategies for preventing specific types of MVCs. Systematic Review of Evidence... used to estimate rates of accident-related injuries more generally,9 but not with specific reference to MVCs. For the present report, rates of...precise rate estimates based on person-years rather than active duty strength, (e) multivariable effects of specific risk /protective factors after
Evaluation of Vehicle-Based Crash Severity Metrics.
Tsoi, Ada H; Gabler, Hampton C
2015-01-01
Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes. The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000-2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2-) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy. The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric estimate to be a significant predictor in the model (p < 0.05). For the belted drivers, both OIV and VPI were significantly better predictors of serious injury than delta-v (p < 0.05). For the unbelted drivers, there was no statistically significant difference between delta-v, OIV, VPI, and ASI. The broad findings of this study suggest it is feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.
Analysis of the frequency and severity of rear-end crashes in work zones.
Qi, Yi; Srinivasan, Raghavan; Teng, Hualiang; Baker, Robert
2013-01-01
The objective of this study was to identify the factors that influence the frequency and severity of rear-end crashes in work zones because rear-end crashes represent a significant proportion of crashes that occur in work zones. Truncated count data models were developed to identify influencing factors on the frequency of read-end crashes in work zones and ordered probit models were developed to evaluate influencing factors on the severity of rear-end crashes in work zones. Most of the variables identified in this study for these 2 models were significant at the 95 percent level. The statistics for models indicate that the 2 developed models are appropriate compared to alternative models. Major findings related to the frequency of rear-end crashes include the following: (1) work zones for capacity and pavement improvements have the highest frequency compared to other types of work zones; (2) work zones controlled by flaggers are associated with more rear-end crashes compared to those controlled by arrow boards; and (3) work zones with alternating one-way traffic tended to have more rear-end crashes compared to those with lane shifts. Major findings related to the severity of the rear-end crashes include the following: (1) rear-end crashes associated with alcohol, night, pedestrians, and roadway defects are more severe, and those associated with careless backing, stalled vehicles, slippery roadways, and misunderstanding flagging signals are less severe; (2) truck involvement and a large number of vehicles in a crash are both associated with increased severity, and (3) rear-end crashes that happened in work zones for bridge, capacity, and pavement are likely to be more severe than others.
A Bayesian ridge regression analysis of congestion's impact on urban expressway safety.
Shi, Qi; Abdel-Aty, Mohamed; Lee, Jaeyoung
2016-03-01
With the rapid growth of traffic in urban areas, concerns about congestion and traffic safety have been heightened. This study leveraged both Automatic Vehicle Identification (AVI) system and Microwave Vehicle Detection System (MVDS) installed on an expressway in Central Florida to explore how congestion impacts the crash occurrence in urban areas. Multiple congestion measures from the two systems were developed. To ensure more precise estimates of the congestion's effects, the traffic data were aggregated into peak and non-peak hours. Multicollinearity among traffic parameters was examined. The results showed the presence of multicollinearity especially during peak hours. As a response, ridge regression was introduced to cope with this issue. Poisson models with uncorrelated random effects, correlated random effects, and both correlated random effects and random parameters were constructed within the Bayesian framework. It was proven that correlated random effects could significantly enhance model performance. The random parameters model has similar goodness-of-fit compared with the model with only correlated random effects. However, by accounting for the unobserved heterogeneity, more variables were found to be significantly related to crash frequency. The models indicated that congestion increased crash frequency during peak hours while during non-peak hours it was not a major crash contributing factor. Using the random parameter model, the three congestion measures were compared. It was found that all congestion indicators had similar effects while Congestion Index (CI) derived from MVDS data was a better congestion indicator for safety analysis. Also, analyses showed that the segments with higher congestion intensity could not only increase property damage only (PDO) crashes, but also more severe crashes. In addition, the issues regarding the necessity to incorporate specific congestion indicator for congestion's effects on safety and to take care of the multicollinearity between explanatory variables were also discussed. By including a specific congestion indicator, the model performance significantly improved. When comparing models with and without ridge regression, the magnitude of the coefficients was altered in the existence of multicollinearity. These conclusions suggest that the use of appropriate congestion measure and consideration of multicolilnearity among the variables would improve the models and our understanding about the effects of congestion on traffic safety. Copyright © 2015 Elsevier Ltd. All rights reserved.
Alcohol-related risk of driver fatalities: an update using 2007 data.
Voas, Robert B; Torres, Pedro; Romano, Eduardo; Lacey, John H
2012-05-01
The purpose of this study was to determine whether the relative risk of being involved in an alcohol-related crash has changed over the decade from 1996 to 2007, a period during which there has been little evidence of a reduction in the percentage of all fatal crashes involving alcohol. We compared blood-alcohol information for the 2006 and 2007 crash cases (N = 6,863, 22.8% of them women) drawn from the U.S. Fatality Analysis Reporting System (FARS) with control blood-alcohol data from participants in the 2007 U.S. National Roadside Survey (N = 6,823). Risk estimates were computed and compared with those previously obtained from the 1996 FARS and roadside survey data. Although the adult relative risk of being involved in a fatal alcohol-related crash apparently did not change from 1996 to 2007, the risk for involvement in an alcohol-related crash for underage women has increased to the point where it has become the same as that for underage men. Further, the risk that sober underage men will become involved in a fatal crash has doubled over the 1996-2007 period. Compared with estimates obtained from a decade earlier, young women in this study are at an increased risk of involvement in alcohol-related crashes. Similarly, underage sober drivers in this study are more at risk of involvement in a crash than they were a decade earlier.
Quality of traffic flow on urban arterial streets and its relationship with safety.
Dixit, Vinayak V; Pande, Anurag; Abdel-Aty, Mohamed; Das, Abhishek; Radwan, Essam
2011-09-01
The two-fluid model for vehicular traffic flow explains the traffic on arterials as a mix of stopped and running vehicles. It describes the relationship between the vehicles' running speed and the fraction of running vehicles. The two parameters of the model essentially represent 'free flow' travel time and level of interaction among vehicles, and may be used to evaluate urban roadway networks and urban corridors with partially limited access. These parameters are influenced by not only the roadway characteristics but also by behavioral aspects of driver population, e.g., aggressiveness. Two-fluid models are estimated for eight arterial corridors in Orlando, FL for this study. The parameters of the two-fluid model were used to evaluate corridor level operations and the correlations of these parameters' with rates of crashes having different types/severity. Significant correlations were found between two-fluid parameters and rear-end and angle crash rates. Rate of severe crashes was also found to be significantly correlated with the model parameter signifying inter-vehicle interactions. While there is need for further analysis, the findings suggest that the two-fluid model parameters may have potential as surrogate measures for traffic safety on urban arterial streets. Copyright © 2011 Elsevier Ltd. All rights reserved.
Zaloshnja, Eduard; Miller, Ted; Romano, Eduardo; Spicer, Rebecca
2004-05-01
This paper presents costs per US motor vehicle crash victim differentiated into many more diagnostic categories than prior estimates. These unit costs, which include the first keyed to the 1990 edition of Abbreviated Injury Scale (AIS) threat-to-life severity scores, are reported by body part, whether a fracture/dislocation was involved, and the maximum AIS score among the victim's injuries. This level of detail allows for a more accurate estimation of the social costs of motor vehicle crashes. It also allows for reliable analyses of interventions targeting narrow ranges of injuries. The paper updates the medical care data underlying the US crash costs from 1979 to 1986 to the mid 1990s and improves on prior productivity cost estimates. In addition to presenting the latest generation of crash victim costs, this paper analyzes the effects of applying injury costs classified by AIS code from the 1985 edition to injury incidence data coded with the 1990 edition of AIS. This long-standing practice results in inaccurate cost-benefit analyses that typically overestimate benefits. This problem is more acute when old published costs adjusted for inflation are used rather than the recent costs.
Naimi, Timothy S; Xuan, Ziming; Sarda, Vishnudas; Hadland, Scott E; Lira, Marlene C; Swahn, Monica H; Voas, Robert B; Heeren, Timothy C
2018-05-29
Motor vehicle crashes are a leading cause of mortality. However, the association between the restrictiveness of the alcohol policy environment (ie, based on multiple existing policies) and alcohol-related crash fatalities has not been characterized previously to date. To examine the association between the restrictiveness of state alcohol policy environments and the likelihood of alcohol involvement among those dying in motor vehicle crashes in the United States. This investigation was a repeated cross-sectional study in which state alcohol policies (operationalized by the Alcohol Policy Scale [APS]) from 1999 to 2014 were related to motor vehicle crash fatalities from 2000 to 2015 using data from the Fatality Analysis Reporting System (1-year lag). Alternating logistic regression models and generalized estimating equations were used to account for clustering of multiple deaths within a crash and of multiple crashes occurring within states. The study also examined independent associations of mutually exclusive subgroups of policies, including consumption-oriented policies vs driving-oriented policies. The study setting was the 50 US states. Participants were 505 614 decedents aged at least 21 years from motor vehicle crashes from 2000 to 2015. Odds that a crash fatality was alcohol related (fatality stemmed from a crash in which ≥1 driver had a blood alcohol concentration [BAC] ≥0.08%). From 2000 to 2015, there were 505 614 adult motor vehicle crash fatalities in the United States, of which 178 795 (35.4%) were alcohol related. Each 10-percentage point increase in the APS score (corresponding to more restrictive state policies) was associated with reduced individual-level odds of alcohol involvement in a crash fatality (adjusted odds ratio [aOR], 0.90; 95% CI, 0.89-0.91); results were consistent among most demographic and crash-type strata. More restrictive policies also had protective associations with alcohol involvement among crash fatalities associated with BACs from greater than 0.00% to less than 0.08%. After accounting for driving-oriented policies, consumption-oriented policies were independently protective for alcohol-related crash fatalities (aOR, 0.97; 95% CI, 0.96-0.98 based on a 10-percentage point increased APS score). Strengthening alcohol policies, including those that do not specifically target impaired driving, could reduce alcohol-related crash fatalities. Policies may also protect against crash fatalities involving BAC levels below the current legal limit for driving in the United States.
Wenzel, Tom
2013-10-01
The National Highway Traffic Safety Administration (NHTSA) recently updated its 2003 and 2010 logistic regression analyses of the effect of a reduction in light-duty vehicle mass on US societal fatality risk per vehicle mile traveled (VMT; Kahane, 2012). Societal fatality risk includes the risk to both the occupants of the case vehicle as well as any crash partner or pedestrians. The current analysis is the most thorough investigation of this issue to date. This paper replicates the Kahane analysis and extends it by testing the sensitivity of his results to changes in the definition of risk, and the data and control variables used in the regression models. An assessment by Lawrence Berkeley National Laboratory (LBNL) indicates that the estimated effect of mass reduction on risk is smaller than in Kahane's previous studies, and is statistically non-significant for all but the lightest cars (Wenzel, 2012a). The estimated effects of a reduction in mass or footprint (i.e. wheelbase times track width) are small relative to other vehicle, driver, and crash variables used in the regression models. The recent historical correlation between mass and footprint is not so large to prohibit including both variables in the same regression model; excluding footprint from the model, i.e. allowing footprint to decrease with mass, increases the estimated detrimental effect of mass reduction on risk in cars and crossover utility vehicles (CUVs)/minivans, but has virtually no effect on light trucks. Analysis by footprint deciles indicates that risk does not consistently increase with reduced mass for vehicles of similar footprint. Finally, the estimated effects of mass and footprint reduction are sensitive to the measure of exposure used (fatalities per induced exposure crash, rather than per VMT), as well as other changes in the data or control variables used. It appears that the safety penalty from lower mass can be mitigated with careful vehicle design, and that manufacturers can reduce mass as a strategy to increase their vehicles' fuel economy and reduce greenhouse gas emissions without necessarily compromising societal safety. Published by Elsevier Ltd.
Bahouth, George; Graygo, Jill; Digges, Kennerly; Schulman, Carl; Baur, Peter
2014-01-01
The objectives of this study are to (1) characterize the population of crashes meeting the Centers for Disease Control and Prevention (CDC)-recommended 20% risk of Injury Severity Score (ISS)>15 injury and (2) explore the positive and negative effects of an advanced automatic crash notification (AACN) system whose threshold for high-risk indications is 10% versus 20%. Binary logistic regression analysis was performed to predict the occurrence of motor vehicle crash injuries at both the ISS>15 and Maximum Abbreviated Injury Scale (MAIS) 3+ level. Models were trained using crash characteristics recommended by the CDC Committee on Advanced Automatic Collision Notification and Triage of the Injured Patient. Each model was used to assign the probability of severe injury (defined as MAIS 3+ or ISS>15 injury) to a subset of NASS-CDS cases based on crash attributes. Subsequently, actual AIS and ISS levels were compared with the predicted probability of injury to determine the extent to which the seriously injured had corresponding probabilities exceeding the 10% and 20% risk thresholds. Models were developed using an 80% sample of NASS-CDS data from 2002 to 2012 and evaluations were performed using the remaining 20% of cases from the same period. Within the population of seriously injured (i.e., those having one or more AIS 3 or higher injuries), the number of occupants whose injury risk did not exceed the 10% and 20% thresholds were estimated to be 11,700 and 18,600, respectively, each year using the MAIS 3+ injury model. For the ISS>15 model, 8,100 and 11,000 occupants sustained ISS>15 injuries yet their injury probability did not reach the 10% and 20% probability for severe injury respectively. Conversely, model predictions suggested that, at the 10% and 20% thresholds, 207,700 and 55,400 drivers respectively would be incorrectly flagged as injured when their injuries had not reached the AIS 3 level. For the ISS>15 model, 87,300 and 41,900 drivers would be incorrectly flagged as injured when injury severity had not reached the ISS>15 injury level. This article provides important information comparing the expected positive and negative effects of an AACN system with thresholds at the 10% and 20% levels using 2 outcome metrics. Overall, results suggest that the 20% risk threshold would not provide a useful notification to improve the quality of care for a large number of seriously injured crash victims. Alternately, a lower threshold may increase the over triage rate. Based on the vehicle damage observed for crashes reaching and exceeding the 10% risk threshold, we anticipate that rescue services would have been deployed based on current Public Safety Answering Point (PSAP) practices.
A joint econometric analysis of seat belt use and crash-related injury severity.
Eluru, Naveen; Bhat, Chandra R
2007-09-01
This paper formulates a comprehensive econometric structure that recognizes two important issues in crash-related injury severity analysis. First, the impact of a factor on injury severity may be moderated by various observed and unobserved variables specific to an individual or to a crash. Second, seat belt use is likely to be endogenous to injury severity. That is, it is possible that intrinsically unsafe drivers do not wear seat belts and are the ones likely to be involved in high injury severity crashes because of their unsafe driving habits. The preceding issues are considered in the current research effort through the development of a comprehensive model of seat belt use and injury severity that takes the form of a joint correlated random coefficients binary-ordered response system. To our knowledge, this is the first instance of such a model formulation and application not only in the safety analysis literature, but in the econometrics literature in general. The empirical analysis is based on the 2003 General Estimates System (GES) data base. Several types of variables are considered to explain seat belt use and injury severity levels, including driver characteristics, vehicle characteristics, roadway design attributes, environmental factors, and crash characteristics. The results, in addition to confirming the effects of various explanatory variables, also highlight the importance of (a) considering the moderating effects of unobserved individual/crash-related factors on the determinants of injury severity and (b) seat belt use endogeneity. From a policy standpoint, the results suggest that seat belt non-users, when apprehended in the act, should perhaps be subjected to both a fine (to increase the chances that they wear seat belts) as well as mandatory enrollment in a defensive driving course (to attempt to change their aggressive driving behaviors).
Yang, King H.
2015-01-01
Aortic injury (AI) leading to disruption of the aorta is an uncommon but highly lethal consequence of trauma in modern society. Most recent estimates range from 7,500 to 8,000 cases per year from a variety of causes. It is observed that more than 80% of occupants who suffer an aortic injury die at the scene due to exsanguination into the chest cavity. It is evident that effective means of substantially improving the outcome of motor vehicle crash-induced AIs is by preventing the injury in the first place. In the current study, 16 design of computer experiments (DOCE) were carried out with varying levels of principal direction of force (PDOF), impact velocity, impact height, and impact position of the bullet vehicle combined with occupant seating positions in the case vehicle to determine the effects of these factors on aortic injury. Further, a combination of real world crash data reported in the Crash Injury Research and Engineering Network (CIREN) database, Finite Element (FE) vehicle models, and the Wayne State Human Body Model-II (WSHBM-II) indicates that occupant seating position, impact height, and PDOF, in that order play, a primary role in aortic injury. PMID:26448781
Fatal crashes of passenger vehicles before and after adding antilock braking systems.
Farmer, C M; Lund, A K; Trempel, R E; Braver, E R
1997-11-01
Fatal crash rates of passenger cars and vans were compared for the last model year before four-wheel antilock brakes were introduced and the first model year for which antilock brakes were standard equipment. Vehicles selected for analysis had no other significant design changes between the model years being compared, and the model years with and without antilocks were no more than two years apart. The overall fatal crash rates were similar for the two model years. However, the vehicles with antilocks were significantly more likely to be involved in crashes fatal to their own occupants, particularly single-vehicle crashes. Conversely, antilock vehicles were less likely to be involved in crashes fatal to occupants of other vehicles or nonoccupants (pedestrians, bicyclists). Overall, antilock brakes appear to have had little effect on fatal crash involvement. Further study is needed to better understand why fatality risk has increased for occupants of antilock vehicles.
DOT National Transportation Integrated Search
2005-01-01
Fatal crash data from FARS and nonfatal crash data from GES are presented in this report in five chapters. Chapter 1, Trends, presents data from all years of FARS (1975 through 2004) and GES (1988 through 2004). The remaining chapters present d...
Baron-Epel, Orna; Obid, Samira; Fertig, Shahar; Gitelman, Victoria
2016-01-01
Involvement in car crashes is higher among Israeli Arabs compared to Jews. This study characterized perceived descriptive driving norms (PDDNs) within and outside Arab towns/villages and estimated their association with involvement in car crashes. Arab drivers (594) living in 19 towns and villages were interviewed in face-to-face interviews. The questionnaire included questions about involvement in car crashes, PDDNs within and outside the towns/villages, attitudes toward traffic safety laws, traffic law violations, and socioeconomic and demographic variables. PDDNs represent individuals' perceptions on how safe other people typically drive. The low scores indicate a low percentage of drivers performing unsafe behaviors (safer driving-related norms). A structural equation modeling analysis was applied to identify factors associated with PDDNs and involvement in car crashes. A large difference was found in PDDNs within and outside the towns/villages. Mostly, the respondents reported higher rates of unsafe PDDNs within the towns/villages (mean = 3.76, SD = 0.63) and lower rates of PDDNs outside the towns/villages (mean = 2.12, SD = 0.60). PDDNs outside the towns/villages were associated with involvement in a car crash (r = -0.12, P <.01), but those within the towns/villages were not. Within the towns/villages, attitudes toward traffic laws and PDDNs were positively associated with traffic law violations (r = 0.56, P <.001; r = 0.11, P <.001 respectively), where traffic law violations were directly associated with involvement in a car crash (r = -0.14, P <.001). Unsafe PDDNs may add directly and indirectly to unsafe driving and involvement in car crashes in Arab Israelis. Because PDDNs outside towns/villages were better, increased law enforcement within towns/villages may improve these norms and decrease involvement in car crashes.
The new car assessment program: does it predict the relative safety of vehicles in actual crashes?
Nirula, Ram; Mock, Charles N; Nathens, Avery B; Grossman, David C
2004-10-01
Federal motor vehicle safety standards are based on crash test dummy analyses that estimate the relative risk of traumatic brain injury (TBI) and severe thoracic injury (STI) by quantifying head (Head Injury Criterion [HIC]) and chest (Chest Gravity Score [CGS]) acceleration. The New Car Assessment Program (NCAP) combines these probabilities to yield the vehicle's five-star rating. The validity of the NCAP system as it relates to an actual motor vehicle crash (MVC) remains undetermined. We therefore sought to determine whether HIC and CGS accurately predict TBI and STI in actual crashes, and compared the NCAP five-star rating system to the rates of TBI and/or STI in actual MVCs. We analyzed frontal crashes with restrained drivers from the 1994 to 1998 National Automotive Sampling System. The relationship of HIC and CGS to the probabilities of TBI and STI derived from crash tests were respectively compared with the HIC-TBI and CGS-STI risk relationships observed in actual crashes while controlling for covariates. Receiver operating characteristic curves determined the sensitivity and specificity of HIC and CGS as predictors of TBI and STI, respectively. Estimates of the likelihood of TBI and/or STI (in actual MVCs) were compared with the expected probabilities of TBI and STI (determined by crash test analysis), as they relate to NCAP ratings. The crash tests overestimate TBI likelihood at HIC scores >800 and underestimate it at scores <500. STI likelihood is overestimated when CGS exceeds 40 g. Receiver operating characteristic curves demonstrated poor sensitivity and specificity of HIC and CGS in predicting injury. The actual MVC injury probability estimates did not vary between vehicles of different NCAP rating. HIC and CGS are poor predictors of TBI and STI in actual MVCs. The NCAP five-star rating system is unable to differentiate vehicles of varying crashworthiness in actual MVCs. More sensitive parameters need to be developed and incorporated into vehicle crash safety testing to provide consumers and automotive manufacturers with useful tools with which to measure vehicle safety.
Elliott, Michael R; Kallan, Michael J; Durbin, Dennis R; Winston, Flaura K
2006-06-01
To provide an estimate of benefit, if any, of child restraint systems over seat belts alone for children aged from 2 through 6 years. Cohort study. A sample of children in US passenger vehicle crashes was obtained from the National Highway Transportation Safety Administration by combining cases involving a fatality from the US Department of Transportation Fatality Analysis Reporting System with a probability sample of cases without a fatality from the National Automotive Sampling System. Children in tow-away [corrected] crashes occurring between 1998 and 2003. Use of child restraint systems (rear-facing and forward-facing car seats, and shield and belt-positioning booster seats) vs seat belts. Potentially confounding variables included seating position, vehicle type, model year, driver and passenger ages, and driver survival status. Death of child passengers from injuries incurred during the crash. Compared with seat belts, child restraints, when not seriously misused (eg, unattached restraint, child restraint system harness not used, 2 children restrained with 1 seat belt) were associated with a 28% reduction in risk for death (relative risk, 0.72; 95% confidence interval, 0.54-0.97) in children aged 2 through 6 years after adjusting for seating position, vehicle type, model year, driver and passenger ages, and driver survival status. When including cases of serious misuse, the effectiveness estimate was slightly lower (21%) (relative risk, 0.79; 95% confidence interval, 0.59-1.05). Based on these findings as well as previous epidemiological and biomechanical evidence for child restraint system effectiveness in reducing nonfatal injury risk, efforts should continue to promote use of child restraint systems through improved laws and with education and disbursement programs.
Vachal, Kimberly; Tumuhairwe, Esther K; Berwick, Mark
2009-04-01
The North Dakota Legislature recently passed a law exempting the state's agricultural truck fleet from a federal safety program requirement for rear-guard equipment on large trucks. This equipment has been shown to reduce crash severity when a passenger vehicle collides with the rear of the truck. This study uses truck fleet, truck crash, and injury severity data to estimate the public safety benefit derived from passenger-vehicle underride protection during rear-end crashes involving large agricultural trucks in North Dakota. A benefit-cost analysis of crash injury avoidance is developed based on the frequency and severity of rear-end truck collisions in North Dakota between 2001 and 2007. The injury avoidance benefits and commercial vehicle safety grant benefits are estimated to be $11.4 to $20.2 million during the seven-year depreciable truck life. The public safety benefits for rear-impact guards are higher than the estimated lifetime cost for the equipment and maintenance of $8.1 million.
Quantifying the safety effects of horizontal curves on two-way, two-lane rural roads.
Gooch, Jeffrey P; Gayah, Vikash V; Donnell, Eric T
2016-07-01
The objective of this study is to quantify the safety performance of horizontal curves on two-way, two-lane rural roads relative to tangent segments. Past research is limited by small samples sizes, outdated statistical evaluation methods, and unreported standard errors. This study overcomes these drawbacks by using the propensity scores-potential outcomes framework. The impact of adjacent curves on horizontal curve safety is also explored using a cross-sectional regression model of only horizontal curves. The models estimated in the present study used eight years of crash data (2005-2012) obtained from over 10,000 miles of state-owned two-lane rural roads in Pennsylvania. These data included information on roadway geometry (e.g., horizontal curvature, lane width, and shoulder width), traffic volume, roadside hazard rating, and the presence of various low-cost safety countermeasures (e.g., centerline and shoulder rumble strips, curve and intersection warning pavement markings, and aggressive driving pavement dots). Crash prediction is performed by means of mixed effects negative binomial regression using the explanatory variables noted previously, as well as attributes of adjacent horizontal curves. The results indicate that both the presence of a horizontal curve and its degree of curvature must be considered when predicting the frequency of total crashes on horizontal curves. Both are associated with an increase in crash frequency, which is consistent with previous findings in the literature. Mixed effects negative binomial regression models for total crash frequency on horizontal curves indicate that the distance to adjacent curves is not statistically significant. However, the degree of curvature of adjacent curves in close proximity (within 0.75 miles) was found to be statistically significant and negatively correlated with crash frequency on the subject curve. This is logical, as drivers exiting a sharp curve are likely to be driving slower and with more awareness as they approach the next horizontal curve. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hosseinpour, Mehdi; Pour, Mehdi Hossein; Prasetijo, Joewono; Yahaya, Ahmad Shukri; Ghadiri, Seyed Mohammad Reza
2013-01-01
The objective of this study was to examine the effects of various roadway characteristics on the incidence of pedestrian-vehicle crashes by developing a set of crash prediction models on 543 km of Malaysia federal roads over a 4-year time span between 2007 and 2010. Four count models including the Poisson, negative binomial (NB), hurdle Poisson (HP), and hurdle negative binomial (HNB) models were developed and compared to model the number of pedestrian crashes. The results indicated the presence of overdispersion in the pedestrian crashes (PCs) and showed that it is due to excess zero rather than variability in the crash data. To handle the issue, the hurdle Poisson model was found to be the best model among the considered models in terms of comparative measures. Moreover, the variables average daily traffic, heavy vehicle traffic, speed limit, land use, and area type were significantly associated with PCs.
Savino, Giovanni; Mackenzie, Jamie; Allen, Trevor; Baldock, Matthew; Brown, Julie; Fitzharris, Michael
2016-09-01
Autonomous emergency braking (AEB) is a safety system that detects imminent forward collisions and reacts by slowing down the host vehicle without any action from the driver. AEB effectiveness in avoiding and mitigating real-world crashes has recently been demonstrated. Research suggests that a translation of AEB to powered 2-wheelers could also be beneficial. Previous studies have estimated the effects of a motorcycle AEB system (MAEB) via computer simulations. Though effects of MAEB were computed for motorcycle crashes derived from in-depth crash investigation, there may be some inaccuracies due to limitations of postcrash investigation (e.g., inaccuracies in preimpact velocity of the motorcycle). Furthermore, ideal MAEB technology was assumed, which may lead to overestimation of the benefits. This study sought to evaluate the sensitivity of the simulations to variations in reconstructed crash cases and the capacity of the MAEB system in order to provide a more robust estimation of MAEB effects. First, a comprehensive classification of accidents was used to identify scenarios in which MAEB was likely to apply, and representative crash cases from those available for this study were populated for each crash scenario. Second, 100 variant cases were generated by randomly varying a set of simulation parameters with given normal distributions around the baseline values. Variants reflected uncertainties in the original data. Third, the effects of MAEB were estimated in terms of the difference in the impact speed of the host motorcycle with and without the system via computer simulations of each variant case. Simulations were repeated assuming both an idealized and a realistic MAEB system. For each crash case, the results in the baseline case and in the variants were compared. A total of 36 crash cases representing 11 common crash scenarios were selected from 3 Australian in-depth data sets: 12 cases from New South Wales, 13 cases from Victoria, and 11 cases from South Australia. The reduction in impact speed elicited by MAEB in the baseline cases ranged from 2.8 to 10.0 km/h. The baseline cases over- or underestimated the mean impact speed reduction of the variant cases by up to 20%. Constraints imposed by simulating more realistic capabilities for an MAEB system produced a decrease in the estimated impact speed reduction of up to 14% (mean 5%) compared to an idealized system. The small difference between the baseline and variant case results demonstrates that the potential effects of MAEB computed from the cases described in in-depth crash reports are typically a good approximation, despite limitations of postcrash investigation. Furthermore, given that MAEB intervenes very close to the point of impact, limitations of the currently available technologies were not found to have a dramatic influence on the effects of the system.
A new method to evaluate future impact of vehicle safety technology in Sweden.
Strandroth, Johan; Sternlund, Simon; Tingvall, Claes; Johansson, Roger; Rizzi, Matteo; Kullgren, Anders
2012-10-01
In the design of a safe road transport system there is a need to better understand the safety challenges lying ahead. One way of doing that is to evaluate safety technology with retrospective analysis of crashes. However, by using retros- pective data there is the risk of adapting safety innovations to scenarios irrelevant in the future. Also, challenges arise as safety interventions do not act alone but are rather interacting components in a complex road transport system. The objective of this study was therefore to facilitate the prioritizing of road safety measures by developing and applying a new method to consider possible impact of future vehicle safety technology. The key point was to project the chain of events leading to a crash today into the crashes for a given time in the future. Assumptions on implementation on safety technologies were made and these assump- tions were applied on the crashes of today. It was estimated which crashes would be prevented and the residual was analyzed to identify the characteristics of future crashes. The Swedish Transport Administration's in-depth studies of fatal crashes from 2010 involving car passengers (n=156) were used. This study estimated that the number of killed car occupant would be reduced with 53 percent from the year 2010 to 2020. Through this new method, valuable information regarding the characteristic of the future crashes was found. The results of this study showed that it was possible to evaluate future impact of vehicle safety technology if detailed and representative crash data is available.
Injury severity data for front and second row passengers in frontal crashes.
Atkinson, Theresa; Leszek Gawarecki; Tavakoli, Massoud
2016-06-01
The data contained here were obtained from the National Highway Transportation Safety Administration׳s National Automotive Sampling System - Crashworthiness Data System (NASS-CDS) for the years 2008-2014. This publically available data set monitors motor vehicle crashes in the United States, using a stratified random sample frame, resulting in information on approximately 5000 crashes each year that can be utilized to create national estimates for crashes. The NASS-CDS data sets document vehicle, crash, and occupant factors. These data can be utilized to examine public health, law enforcement, roadway planning, and vehicle design issues. The data provided in this brief are a subset of crash events and occupants. The crashes provided are exclusively frontal crashes. Within these crashes, only restrained occupants who were seated in the right front seat position or the second row outboard seat positions were included. The front row and second row data sets were utilized to construct occupant pairs crashes where both a right front seat occupant and a second row occupant were available. Both unpaired and paired data sets are provided in this brief.
Injury severity data for front and second row passengers in frontal crashes
Atkinson, Theresa; Leszek Gawarecki; Tavakoli, Massoud
2016-01-01
The data contained here were obtained from the National Highway Transportation Safety Administration׳s National Automotive Sampling System – Crashworthiness Data System (NASS-CDS) for the years 2008–2014. This publically available data set monitors motor vehicle crashes in the United States, using a stratified random sample frame, resulting in information on approximately 5000 crashes each year that can be utilized to create national estimates for crashes. The NASS-CDS data sets document vehicle, crash, and occupant factors. These data can be utilized to examine public health, law enforcement, roadway planning, and vehicle design issues. The data provided in this brief are a subset of crash events and occupants. The crashes provided are exclusively frontal crashes. Within these crashes, only restrained occupants who were seated in the right front seat position or the second row outboard seat positions were included. The front row and second row data sets were utilized to construct occupant pairs crashes where both a right front seat occupant and a second row occupant were available. Both unpaired and paired data sets are provided in this brief. PMID:27077084
The shift to and from daylight savings time and motor vehicle crashes.
Lambe, M; Cummings, P
2000-07-01
The objective of the study was to examine whether the shifts to and from daylight savings time in Sweden have short-term effects on the incidence of traffic crashes. A database maintained by the Swedish National Road Administration was used to examine crashes from 1984 through 1995, that occurred on state roads the Monday preceding, the Monday immediately after (index Monday), and the Monday 1 week after the change to daylight savings time in the spring and for the corresponding three Mondays in the autumn. The Mondays 1 week before and after the time changes were taken as representing the expected incidence of crashes. Crash incidence was calculated per 1000 person-years using population estimates for each year of the study. The association between 1 h of possible sleep loss and crash incidence was estimated by the incidence rate ratio from negative binomial regression. The incidence rate ratio was 1.04 (95% CI, 0.92-1.16) for a Monday on which drivers were expected to have had 1 h less sleep, compared with other Mondays. In the spring, the incidence rate ratio for crashes was 1.11 (95% CI, 0.93-1.31) for Mondays after the time change compared to other spring Mondays. The corresponding rate ratio for the fall was 0.98 (95% CI, 0.84-1.15) It was concluded that the shift to and from daylight savings time did not have measurable important immediate effects on crash incidence in Sweden.
Depression, antidepressants and driving safety.
Hill, Linda L; Lauzon, Vanessa L; Winbrock, Elise L; Li, Guohua; Chihuri, Stanford; Lee, Kelly C
2017-12-01
The purpose of this study was to review to review the reported associations of depression and antidepressants with motor vehicle crashes. A literature search for material published in the English language between January, 1995, and October, 2015, in bibliographic databases was combined with a search for other relevant material referenced in the retrieved articles. Retrieved articles were systematically reviewed for inclusion criteria: 19 epidemiological studies (17 case-control and 2 cohort studies) fulfilled the inclusion criteria by estimating the crash risk associated with depression and/or psychotropic medications in naturalistic settings. The estimates of the odds ratio (OR) of crash involvement associated with depression ranged from 1.78 to 3.99. All classes of antidepressants were reported to have side effects with the potential to affect driving safety. The majority of studies of antidepressant effects on driving reported an elevated crash risk, and ORs ranged from 1.19 to 2.03 for all crashes, and 3.19 for fatal crashes. In meta-analysis, depression was associated with approximately 2-fold increased crash risk (summary OR = 1.90; 95% CI, 1.06 to 3.39), and antidepressants were associated with approximately 40% increased crash risk (summary OR = 1.40; 95%CI, 1.18 to 1.66). Based on the findings of the studies reviewed, depression, antidepressants or the combination of depression and antidepressants may pose a potential hazard to driving safety. More research is needed to understand the individual contributions of depression and the medications used to treat depression.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wenzel, Thomas P.
This report analyzes the relationship between vehicle weight, size (wheelbase, track width, and their product, footprint), and safety, for individual vehicle makes and models. Vehicle weight and footprint are correlated with a correlation coefficient (R{sup 2}) of about 0.62. The relationship is stronger for cars (0.69) than for light trucks (0.42); light trucks include minivans, fullsize vans, truck-based SUVs, crossover SUVs, and pickup trucks. The correlation between wheelbase and track width, the components of footprint, is about 0.61 for all light vehicles, 0.62 for cars and 0.48 for light trucks. However, the footprint data used in this analysis does notmore » vary for different versions of the same vehicle model, as curb weight does; the analysis could be improved with more precise data on footprint for different versions of the same vehicle model. Although US fatality risk to drivers (driver fatalities per million registered vehicles) decreases as vehicle footprint increases, there is very little correlation either for all light vehicles (0.01), or cars (0.07) or trucks (0.11). The correlation between footprint and fatality risks cars impose on drivers of other vehicles is also very low (0.01); for trucks the correlation is higher (0.30), with risk to others increasing as truck footprint increases. Fatality risks reported here do not account for differences in annual miles driven, driver age or gender, or crash location by vehicle type or model. It is difficult to account for these factors using data on national fatal crashes because the number of vehicles registered to, for instance, young males in urban areas is not readily available by vehicle type or model. State data on all police-reported crashes can be used to estimate casualty risks that account for miles driven, driver age and gender, and crash location. The number of vehicles involved in a crash can act as a proxy of the number of miles a given vehicle type, or model, is driven per year, and is a preferable unit of exposure to a serious crash than the number of registered vehicles. However, because there are relatively few fatalities in the states providing crash data, we calculate casualty risks, which are the sum of fatalities and serious or incapacitating injuries, per vehicle involved in a crash reported to the police. We can account for driver age/gender and driving location effects by excluding from analysis crashes (and casualties) involving young males and the elderly, and occurring in very rural or very urban counties. Using state data on all police-reported crashes in five states, we find that excluding crashes involving young male and elderly drivers has little effect on casualty risk; however, excluding crashes that occurred in the most rural and most urban counties (based on population density) increases casualty risk for all vehicle types except pickups. This suggests that risks for pickups are overstated unless they account for the population density of the county in which the crashes occur. After removing crashes involving young males and elderly drivers, and those occurring in the most rural and most urban counties, we find that casualty risk in all light-duty vehicles tends to increase with increasing weight or footprint; however, the correlation (R{sup 2}) between casualty risk and vehicle weight is 0.31, while the correlation with footprint is 0.23. These relationships are stronger for cars than for light trucks. The correlation between casualty risk in frontal crashes and light-duty vehicle wheelbase is 0.12, while the correlation between casualty risk in left side crashes and track width is 0.36. We calculated separately the casualty risks vehicles impose on drivers of the other vehicles with which they crash. The correlation between casualty risk imposed by light trucks on drivers of other vehicles and light truck footprint is 0.15, while the correlation with light truck footprint is 0.33; risk imposed on others increases as light truck weight or footprint increases. Our analysis indicates that, after excluding crashes involving young male and elderly drivers, and crashes in very rural and very urban counties, and accounting for vehicle weight and footprint, sports cars, pickup trucks and truck-based SUVs have higher risk to their drivers than cars, while import luxury cars and crossover SUVs have lower risk to their drivers than cars. Similarly, pickups and sports cars impose a large casualty risk on drivers of other vehicles, after accounting for vehicle weight and footprint. Our analysis suggests that excluding young male and elderly drivers, and crashes in very rural and urban counties, accounting for vehicle weight, footprint, and type explains only about half of the variability in casualty risk to drivers, and to drivers of other vehicles, by vehicle model.« less
Vehicle crashworthiness ratings in Australia.
Cameron, M; Mach, T; Neiger, D; Graham, A; Ramsay, R; Pappas, M; Haley, J
1994-08-01
The paper reviews the published vehicle safety ratings based on mass crash data from the United States, Sweden, and Great Britain. It then describes the development of vehicle crashworthiness ratings based on injury compensation claims and police accident reports from Victoria and New South Wales, the two most populous states in Australia. Crashworthiness was measured by a combination of injury severity (of injured drivers) and injury risk (of drivers involved in crashes). Injury severity was based on 22,600 drivers injured in crashes in the two states. Injury risk was based on 70,900 drivers in New South Wales involved in crashes after which a vehicle was towed away. Injury risk measured in this way was compared with the "relative injury risk" of particular model cars involved in two car crashes in Victoria (where essentially only casualty crashes are reported), which was based on the method developed by Folksam Insurance in Sweden from Evans' double-pair comparison method. The results include crashworthiness ratings for the makes and models crashing in Australia in sufficient numbers to measure their crash performance adequately. The ratings were normalised for the driver sex and speed limit at the crash location, the two factors found to be strongly related to injury risk and/or severity and to vary substantially across makes and models of Australian crash-involved cars. This allows differences in crashworthiness of individual models to be seen, uncontaminated by major crash exposure differences.
Exploring the safety in numbers effect for vulnerable road users on a macroscopic scale.
Tasic, Ivana; Elvik, Rune; Brewer, Simon
2017-12-01
A "Safety in Numbers" effect for a certain group of road users is present if the number of crashes increases at a lower rate than the number of road users. The existence of this effect has been invoked to justify investments in multimodal transportation improvements in order to create more sustainable urban transportation systems by encouraging walking, biking, and transit ridership. The goal of this paper is to explore safety in numbers effect for cyclists and pedestrians in areas with different levels of access to multimodal infrastructure. Data from Chicago served to estimate the expected number of crashes on the census tract level by applying Generalized Additive Models (GAM) to capture spatial dependence in crash data. Measures of trip generation, multimodal infrastructure, network connectivity and completeness, and accessibility were used to model travel exposure in terms of activity, number of trips, trip length, travel opportunities, and conflicts. The results show that a safety in numbers effect exists on a macroscopic level for motor vehicles, pedestrians, and bicyclists. Copyright © 2017 Elsevier Ltd. All rights reserved.
The impact of Michigan's text messaging restriction on motor vehicle crashes.
Ehsani, Johnathon P; Bingham, C Raymond; Ionides, Edward; Childers, David
2014-05-01
The purpose of this study was to determine the effects of Michigan's universal text messaging restriction (effective July 2010) across different age groups of drivers and crash severities. Changes in monthly crash rates and crash trends per 10,000 licensed drivers aged 16, 17, 18, 19, 20-24, and 25-50 years were estimated using time series analysis for three levels of crash severity: (1) fatal/disabling injury; (2) nondisabling injury; and (3) possible injury/property damage only (PDO) crashes for the period 2005-2012. Analyses were adjusted for crash rates of drivers' aged 65-99 years, Michigan's unemployment rate, and gasoline prices. After the introduction of the texting restriction, significant increases were observed in crash rates and monthly trends in fatal/disabling injury crashes and nondisabling injury crashes, and significant decreases in possible injury/PDO crashes. The magnitude of the effects where significant changes were observed was small. The introduction of the texting restriction was not associated with a reduction in crash rates or trends in severe crash types. On the contrary, small increases in the most severe crash types (fatal/disabling and nondisabling injury) and small decreases in the least severe crash types (possible injury/PDO) were observed. These findings extend the literature on the effects of cell phone restrictions by examining the effects of the restriction on newly licensed adolescent drivers and adult drivers separately by crash severity. Published by Elsevier Inc.
Ponte, G; Ryan, G A; Anderson, R W G
2016-01-01
The aim of this study was to estimate the potential effectiveness of an in-vehicle automatic collision notification (ACN) system in reducing all road crash fatalities in South Australia (SA). For the years 2008 to 2009, traffic accident reporting system (TARS) data, emergency medical services (EMS) road crash dispatch data, and coroner's reports were matched and examined. This was done to initially determine the extent to which there were differences between the reported time of a fatal road crash in the mass crash data and the time EMS were notified and dispatched. In the subset of fatal crashes where there was a delay, injuries detailed by a forensic pathologist in individual coroner's reports were examined to determine the likelihood of survival had there not been a delay in emergency medical assistance. In 25% (N = 53) of fatalities in SA in the period 2008 to 2009, there was a delay in the notification of the crash event, and hence dispatch of EMS, that exceeded 10 min. In the 2-year crash period, 5 people were likely to have survived through more prompt crash notification enabling quicker emergency medical assistance. Additionally, 3 people potentially would have survived if surgical intervention (or emergency medical assistance to sustain life until surgery) occurred more promptly. The minimum effectiveness rate of an ACN system in SA with full deployment is likely to be in the range of 2.4 to 3.8% of all road crash fatalities involving all vehicle types and all vulnerable road users (pedestrians, cyclists, and motorcyclists) from 2008 to 2009. Considering only passenger vehicle occupants, the benefit is likely to be 2.6 to 4.6%. These fatality reductions could only have been achieved through earlier notification of each crash and their location to enable a quicker medical response. This might be achievable through a fully deployed in-vehicle ACN system.
A preliminary investigation of the relationships between historical crash and naturalistic driving.
Pande, Anurag; Chand, Sai; Saxena, Neeraj; Dixit, Vinayak; Loy, James; Wolshon, Brian; Kent, Joshua D
2017-04-01
This paper describes a project that was undertaken using naturalistic driving data collected via Global Positioning System (GPS) devices to demonstrate a proof-of-concept for proactive safety assessments of crash-prone locations. The main hypothesis for the study is that the segments where drivers have to apply hard braking (higher jerks) more frequently might be the "unsafe" segments with more crashes over a long-term. The linear referencing methodology in ArcMap was used to link the GPS data with roadway characteristic data of US Highway 101 northbound (NB) and southbound (SB) in San Luis Obispo, California. The process used to merge GPS data with quarter-mile freeway segments for traditional crash frequency analysis is also discussed in the paper. A negative binomial regression analyses showed that proportion of high magnitude jerks while decelerating on freeway segments (from the driving data) was significantly related with the long-term crash frequency of those segments. A random parameter negative binomial model with uniformly distributed parameter for ADT and a fixed parameter for jerk provided a statistically significant estimate for quarter-mile segments. The results also indicated that roadway curvature and the presence of auxiliary lane are not significantly related with crash frequency for the highway segments under consideration. The results from this exploration are promising since the data used to derive the explanatory variable(s) can be collected using most off-the-shelf GPS devices, including many smartphones. Copyright © 2017 Elsevier Ltd. All rights reserved.
Alcohol involvement in fatal traffic crashes 1996
DOT National Transportation Integrated Search
1998-01-01
This report presents estimates of alcohol involvement in fatal traffic crashes that occurred during 1996. The data represent a combination of actual blood alcohol concentration (BAC) test results recorded in the Fatal Accident Reporting System (FARS)...
Rizzi, Matteo; Strandroth, Johan; Tingvall, Claes
2009-10-01
This study set out to evaluate the effectiveness of antilock brake system (ABS) technology on motorcycles in reducing real-life injury crashes and to mitigate injury severity. The study comprised an analysis of in-depth fatal crash data in Sweden during 2005-2008 to investigate the potential of ABS as well an estimate of the effectiveness of ABS in crash reduction in Sweden between 2003 and 2008 using induced exposure methods. Findings show that head-on collisions were the least ABS-affected crash types and collisions at intersections the most influenced. Induced exposure analysis showed that the overall effectiveness of ABS was 38 percent on all crashes with injuries and 48 percent on all severe and fatal crashes, with a minimum effectiveness of 11 and 17 percent, respectively. The study recommends the fitment of ABS on all new motorcycles as soon as possible and that customers only purchase motorcycles with ABS.
Analyses of rear-end crashes based on classification tree models.
Yan, Xuedong; Radwan, Essam
2006-09-01
Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.
Stitzel, Joel D; Weaver, Ashley A; Talton, Jennifer W; Barnard, Ryan T; Schoell, Samantha L; Doud, Andrea N; Martin, R Shayn; Meredith, J Wayne
2016-06-01
Advanced Automatic Crash Notification algorithms use vehicle telemetry measurements to predict risk of serious motor vehicle crash injury. The objective of the study was to develop an Advanced Automatic Crash Notification algorithm to reduce response time, increase triage efficiency, and improve patient outcomes by minimizing undertriage (<5%) and overtriage (<50%), as recommended by the American College of Surgeons. A list of injuries associated with a patient's need for Level I/II trauma center treatment known as the Target Injury List was determined using an approach based on 3 facets of injury: severity, time sensitivity, and predictability. Multivariable logistic regression was used to predict an occupant's risk of sustaining an injury on the Target Injury List based on crash severity and restraint factors for occupants in the National Automotive Sampling System - Crashworthiness Data System 2000-2011. The Advanced Automatic Crash Notification algorithm was optimized and evaluated to minimize triage rates, per American College of Surgeons recommendations. The following rates were achieved: <50% overtriage and <5% undertriage in side impacts and 6% to 16% undertriage in other crash modes. Nationwide implementation of our algorithm is estimated to improve triage decisions for 44% of undertriaged and 38% of overtriaged occupants. Annually, this translates to more appropriate care for >2,700 seriously injured occupants and reduces unnecessary use of trauma center resources for >162,000 minimally injured occupants. The algorithm could be incorporated into vehicles to inform emergency personnel of recommended motor vehicle crash triage decisions. Lower under- and overtriage was achieved, and nationwide implementation of the algorithm would yield improved triage decision making for an estimated 165,000 occupants annually. Copyright © 2016. Published by Elsevier Inc.
Kusano, Kristofer D; Gabler, Hampton C
2010-01-01
To mitigate the severity of rear-end and other collisions, Pre-Crash Systems (PCS) are being developed. These active safety systems utilize radar and/or video cameras to determine when a frontal crash, such as a front-to-back rear-end collisions, is imminent and can brake autonomously, even with no driver input. Of these PCS features, the effects of autonomous pre-crash braking are estimated. To estimate the maximum potential for injury reduction due to autonomous pre-crash braking in the striking vehicle of rear-end crashes, a methodology is presented for determining 1) the reduction in vehicle crash change in velocity (ΔV) due to PCS braking and 2) the number of injuries that could be prevented due to the reduction in collision severity. Injury reduction was only performed for belted drivers, as unbelted drivers have an unknown risk of being thrown out of position. The study was based on 1,406 rear-end striking vehicles from NASS / CDS years 1993 to 2008. PCS parameters were selected from realistic values and varied to examine the effect on system performance. PCS braking authority was varied from 0.5 G's to 0.8 G's while time to collision (TTC) was held at 0.45 seconds. TTC was then varied from 0.3 second to 0.6 seconds while braking authority was held constant at 0.6 G's. A constant braking pulse (step function) and ramp-up braking pulse were used. The study found that automated PCS braking could reduce the crash ΔV in rear-end striking vehicles by an average of 12% - 50% and avoid 0% - 14% of collisions, depending on PCS parameters. Autonomous PCS braking could potentially reduce the number of injured drivers who are belted by 19% to 57%.
Crash Frequency Analysis Using Hurdle Models with Random Effects Considering Short-Term Panel Data
Chen, Feng; Ma, Xiaoxiang; Chen, Suren; Yang, Lin
2016-01-01
Random effect panel data hurdle models are established to research the daily crash frequency on a mountainous section of highway I-70 in Colorado. Road Weather Information System (RWIS) real-time traffic and weather and road surface conditions are merged into the models incorporating road characteristics. The random effect hurdle negative binomial (REHNB) model is developed to study the daily crash frequency along with three other competing models. The proposed model considers the serial correlation of observations, the unbalanced panel-data structure, and dominating zeroes. Based on several statistical tests, the REHNB model is identified as the most appropriate one among four candidate models for a typical mountainous highway. The results show that: (1) the presence of over-dispersion in the short-term crash frequency data is due to both excess zeros and unobserved heterogeneity in the crash data; and (2) the REHNB model is suitable for this type of data. Moreover, time-varying variables including weather conditions, road surface conditions and traffic conditions are found to play importation roles in crash frequency. Besides the methodological advancements, the proposed technology bears great potential for engineering applications to develop short-term crash frequency models by utilizing detailed data from field monitoring data such as RWIS, which is becoming more accessible around the world. PMID:27792209
Romano, Eduardo; Scherer, Michael; Fell, James; Taylor, Eileen
2015-12-01
To effectively address concerns associated with alcohol-related traffic laws, communities must apply comprehensive and well-coordinated interventions that account for as many factors as possible. The goal of the current research article is to examine and evaluate the simultaneous contribution of 20 underage drinking laws and 3 general driving safety laws, while accounting for demographic, economic, and environmental variables. Annual fatal crash data (1982 to 2010), policies, and demographic, economic, and environmental information were collected and applied to each of the 51 jurisdictions (50 states and the District of Columbia). A structural equation model was fit to estimate the relative contribution of the variables of interest to alcohol-related crashes. As expected, economic factors (e.g., unemployment rate, cost of alcohol) and alcohol outlet density were found highly relevant to the amount of alcohol teens consume and therefore to teens' impaired driving. Policies such as those regulating the age of bartenders, sellers, or servers; social host civil liability laws; dram shop laws; internal possession of alcohol laws; and fake identification laws do not appear to have the same impact on teens' alcohol-related crash ratios as other types of policies such as those regulating alcohol consumption or alcohol outlet density. This effort illustrates the need for comprehensive models of teens' impaired driving. After simultaneously accounting for as many factors as possible, we found that in general (for most communities) further reductions in alcohol-related crashes among teens might be more rapidly achieved from efforts focused on reducing teens' drinking rather than on reducing teens' driving. Future efforts should be made to develop models that represent specific communities. Based on this and community-specific models, simulation programs can be developed to help communities understand and visualize the impact of various policy alternatives. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.
Buckis, Samantha; Lenné, Mike G; Fitzharris, Michael
2015-01-01
The elevated crash involvement rate of young drivers is well documented. Given the higher crash risk of young drivers and the need for innovative policy and programs, it remains important to fully understand the type of crashes young drivers are involved in, and knowledge of the lifetime care cost of crashes can support effective policy development. The aim of this article is to document the number and type of young driver crashes, as well as the associated lifetime care cost over a 9-year period (2005-2013) in Victoria, Australia. In Victoria, Australia, the Transport Accident Commission (TAC) has legislated responsibility for road safety and the care of persons injured in road crashes, irrespective of fault. TAC claims data for the period 2005-2013 were used to document the number and type of young driver crashes. Lifetime care costs (past and future payment liabilities) were calculated by Taylor Fry actuarial consultancy. License and population data were used to define the crash involvement rate of young drivers. Over the 9-year period, 16,817 claims were lodged to the TAC by drivers 18-25 years of age following a crash. There were 646 fewer drivers aged 18-25 killed and injured in 2013, compared to 2005, representing an unadjusted change of -28.7% (-29.8% males; -28.4% females). The total lifetime care cost of young drivers killed and injured in Victoria for the period 2005-2013 was estimated to be AU$634 million (US$493 million). Differences between males and females, single- and multivehicle crashes, and fatalities and injuries were found to be statistically significant. Run-off-road crashes and crashes from opposing direction were overrepresented in the lifetime care costs for young driver claimants. Twenty-eight injured drivers were classified as high-severity claims. These 28 claimants require additional long-term care, which was estimated to be AU$219 million; of these 28, 24 were male (85.7%). The long-term care costs for these 28 drivers (0.16%) accounts for 34.5% of the total lifetime care cost of all 18- to 25-year-old injured drivers. By using no-fault lifetime care costs that account for medical and like expenses, rehabilitation, and social reintegration costs, a more accurate understanding of the cost of young driver crashes can be determined. Application of these costs to specific crash types highlights new priorities and opportunities for developing programs to reduce young driver crashes.
Toolbox of countermeasures for rural two-lane curves.
DOT National Transportation Integrated Search
2013-10-01
The Federal Highway Administration (FHWA) estimates that 58 percent of roadway fatalities are lane departures, while 40 : percent of fatalities are single-vehicle run-off-road (SVROR) crashes. Addressing lane-departure crashes is therefore a : priori...
Toolbox of countermeasures for rural two-lane curves.
DOT National Transportation Integrated Search
2012-06-01
The Federal Highway Administration (FHWA) estimates that 58 percent of roadway fatalities are lane departures, while 40 percent of fatalities are single-vehicle run-off-road (SVROR) crashes. Addressing lane-departure crashes is therefore a priority f...
Establishing crash modification factors and their use.
DOT National Transportation Integrated Search
2014-08-01
A critical component in the Association of State Highway and Transportation Officials (AASHTO) Highway Safety Manual : (HSM) safety management process is the Crash Modification Factor (CMF). It is used to estimate the change in the : expected (ave...
Alcohol involvement in fatal traffic crashes 1998
DOT National Transportation Integrated Search
2001-03-01
This report presents estimates of alcohol involvement in fatal traffic crashes that occurred during 1998. Several comparisons of alcohol involvement for the period 1982-1998 are presented to illustrate changes and trends. The data are abstracted from...
Alcohol involvement in fatal traffic crashes 1999
DOT National Transportation Integrated Search
2001-05-01
This report presents estimates of alcohol invoelement in fatal traffic crashes that occured during 1999. Several comparisons of alcohol involvement for the period 1982-1999 are presented to illustrate changes and trends. The data are abstracted from ...
Alcohol involvement in fatal traffic crashes 1997
DOT National Transportation Integrated Search
2000-08-01
This report presents estimates of alcohol involvement in fatal traffic crashes that occurred during 1997. Several comparisons of alcohol involvement for the period 1982-1997 are presented to illustrate changes and trends. The data are abstracted from...
Zhang, Guangnan; Li, Yanyan; King, Mark J; Zhong, Qiaoting
2018-03-21
Motor vehicle overloading is correlated with the possibility of road crash occurrence and severity. Although overloading of motor vehicles is pervasive in developing nations, few empirical analyses have been performed on factors that might influence the occurrence of overloading. This study aims to address this shortcoming by seeking evidence from several years of crash data from Guangdong province, China. Data on overloading and other factors are extracted for crash-involved vehicles from traffic crash records for 2006-2010 provided by the Traffic Management Bureau in Guangdong province. Logistic regression is applied to identify risk factors for overloading in crash-involved vehicles and within these crashes to identify factors contributing to greater crash severity. Driver, vehicle, road and environmental characteristics and violation types are considered in the regression models. In addition to the basic logistic models, association analysis is employed to identify the potential interactions among different risk factors during fitting the logistic models of overloading and severity. Crash-involved vehicles driven by males from rural households and in an unsafe condition are more likely to be overloaded and to be involved in higher severity overloaded vehicle crashes. If overloaded vehicles speed, the risk of severe traffic crash casualties increases. Young drivers (aged under 25 years) in mountainous areas are more likely to be involved in higher severity overloaded vehicle crashes. This study identifies several factors associated with overloading in crash-involved vehicles and with higher severity overloading crashes and provides an important reference for future research on those specific risk factors. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Roque, Carlos; Cardoso, João Lourenço
2014-02-01
Crash prediction models play a major role in highway safety analysis. These models can be used for various purposes, such as predicting the number of road crashes or establishing relationships between these crashes and different covariates. However, the appropriate choice for the functional form of these models is generally not discussed in research literature on road safety. In case of run-off-the-road crashes, empirical evidence and logical considerations lead to conclusion that the relationship between expected frequency and traffic flow is not monotonously increasing. Copyright © 2013 Elsevier Ltd. All rights reserved.
Work zone safety analysis and modeling: a state-of-the-art review.
Yang, Hong; Ozbay, Kaan; Ozturk, Ozgur; Xie, Kun
2015-01-01
Work zone safety is one of the top priorities for transportation agencies. In recent years, a considerable volume of research has sought to determine work zone crash characteristics and causal factors. Unlike other non-work zone-related safety studies (on both crash frequency and severity), there has not yet been a comprehensive review and assessment of methodological approaches for work zone safety. To address this deficit, this article aims to provide a comprehensive review of the existing extensive research efforts focused on work zone crash-related analysis and modeling, in the hopes of providing researchers and practitioners with a complete overview. Relevant literature published in the last 5 decades was retrieved from the National Work Zone Crash Information Clearinghouse and the Transport Research International Documentation database and other public digital libraries and search engines. Both peer-reviewed publications and research reports were obtained. Each study was carefully reviewed, and those that focused on either work zone crash data analysis or work zone safety modeling were identified. The most relevant studies are specifically examined and discussed in the article. The identified studies were carefully synthesized to understand the state of knowledge on work zone safety. Agreement and inconsistency regarding the characteristics of the work zone crashes discussed in the descriptive studies were summarized. Progress and issues about the current practices on work zone crash frequency and severity modeling are also explored and discussed. The challenges facing work zone safety research are then presented. The synthesis of the literature suggests that the presence of a work zone is likely to increase the crash rate. Crashes are not uniformly distributed within work zones and rear-end crashes are the most prevalent type of crashes in work zones. There was no across-the-board agreement among numerous papers reviewed on the relationship between work zone crashes and other factors such as time, weather, victim severity, traffic control devices, and facility types. Moreover, both work zone crash frequency and severity models still rely on relatively simple modeling techniques and approaches. In addition, work zone data limitations have caused a number of challenges in analyzing and modeling work zone safety. Additional efforts on data collection, developing a systematic data analysis framework, and using more advanced modeling approaches are suggested as future research tasks.
Conscientious personality and young drivers’ crash risk
Ehsani, Johnathon P.; Li, Kaigang; Simons-Morton, Bruce; Tree-McGrath, Cheyenne Fox; Perlus, Jessamyn; O’Brien, Fearghal; Klauer, Sheila G.
2015-01-01
Introduction Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior and crashes and near-crashes, using naturalistic driving research methods. Method Participants’ driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes and near-crashes (CNC) were assessed over the first 18 months of licensure using naturalistic driving methods. A personality survey (NEO-Five Factor Inventory) was administered at baseline. The association between personality characteristics, KRD rate, secondary task engagement rate and CNC rate was estimated using a linear regression model. Mediation analysis was conducted to examine if participants’ KRD rate or secondary task engagement rate mediated the relationship between personality and CNC. Data were collected as part of the Naturalistic Teen Driving Study. Results Conscientiousness was marginally negatively associated with CNC (path c = −0.034, p = .09) and both potential mediators KRD (path a = −0.040, p = .09) and secondary task engagement while driving (path a = −0.053, p = .03). KRD, but not secondary task engagement, was found to mediate (path b = 0.376, p = .02) the relationship between conscientiousness and CNC (path c’ = −0.025, p = .20). Conclusions Using objective measures of driving behavior and a widely used personality construct, these findings present a causal pathway through which personality and risky driving are associated with CNC. Specifically, more conscientious teenage drivers engaged in fewer risky driving maneuvers, suffered fewer CNC. Practical Applications Part of the variability in crash-risk observed among newly licensed teenage drivers can be explained by personality. Parents and driving instructors may take teenage drivers’ personality into account when providing guidance, and establishing norms and expectations about driving. PMID:26403906
Conscientious personality and young drivers' crash risk.
Ehsani, Johnathon P; Li, Kaigang; Simons-Morton, Bruce G; Fox Tree-McGrath, Cheyenne; Perlus, Jessamyn G; O'Brien, Fearghal; Klauer, Sheila G
2015-09-01
Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior, and crashes and near-crashes, using naturalistic driving research methods. Participants' driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes and near-crashes (CNC) were assessed over the first 18months of licensure using naturalistic driving methods. A personality survey (NEO-Five Factor Inventory) was administered at baseline. The association between personality characteristics, KRD rate, secondary task engagement rate, and CNC rate was estimated using a linear regression model. Mediation analysis was conducted to examine if participants' KRD rate or secondary task engagement rate mediated the relationship between personality and CNC. Data were collected as part of the Naturalistic Teen Driving Study. Conscientiousness was marginally negatively associated with CNC (path c=-0.034, p=.09) and both potential mediators KRD (path a=-0.040, p=.09) and secondary task engagement while driving (path a=-0.053, p=.03). KRD, but not secondary task engagement, was found to mediate (path b=0.376, p=.02) the relationship between conscientiousness and CNC (path c'=-0.025, p=.20). Using objective measures of driving behavior and a widely used personality construct, these findings present a causal pathway through which personality and risky driving are associated with CNC. Specifically, more conscientious teenage drivers engaged in fewer risky driving maneuvers, and suffered fewer CNC. Part of the variability in crash risk observed among newly licensed teenage drivers can be explained by personality. Parents and driving instructors may take teenage drivers' personality into account when providing guidance, and establishing norms and expectations about driving. Published by Elsevier Ltd.
Alcohol-related predictors of adolescent driving: gender differences in crashes and offenses.
Shope, J T; Waller, P F; Lang, S W
1996-11-01
Demographic and alcohol-related data collected from eight-grade students (age 13 years) were used in logistic regression to predict subsequent first-year driving crashes and offenses (age 17 years). For young men's crashes and offenses, good-fitting models used living situation (both parents or not), parents' attitude about teen drinking (negative or neutral), and the interaction term. Young men who lived with both parents and reported negative parental attitudes regarding teen drinking were less likely to have crashes and offenses. For young women's crashes, a good-fitting model included friends' involvement with alcohol. Young women who reported that their friends were not involved with alcohol were least likely to have crashes. No model predicting young women's offenses emerged.
Anarkooli, Alireza Jafari; Hosseinpour, Mehdi; Kardar, Adele
2017-09-01
Rollover crashes are responsible for a notable number of serious injuries and fatalities; hence, they are of great concern to transportation officials and safety researchers. However, only few published studies have analyzed the factors associated with severity outcomes of rollover crashes. This research has two objectives. The first objective is to investigate the effects of various factors, of which some have been rarely reported in the existing studies, on the injury severities of single-vehicle (SV) rollover crashes based on six-year crash data collected on the Malaysian federal roads. A random-effects generalized ordered probit (REGOP) model is employed in this study to analyze injury severity patterns caused by rollover crashes. The second objective is to examine the performance of the proposed approach, REGOP, for modeling rollover injury severity outcomes. To this end, a mixed logit (MXL) model is also fitted in this study because of its popularity in injury severity modeling. Regarding the effects of the explanatory variables on the injury severity of rollover crashes, the results reveal that factors including dark without supplemental lighting, rainy weather condition, light truck vehicles (e.g., sport utility vehicles, vans), heavy vehicles (e.g., bus, truck), improper overtaking, vehicle age, traffic volume and composition, number of travel lanes, speed limit, undulating terrain, presence of central median, and unsafe roadside conditions are positively associated with more severe SV rollover crashes. On the other hand, unpaved shoulder width, area type, driver occupation, and number of access points are found as the significant variables decreasing the probability of being killed or severely injured (i.e., KSI) in rollover crashes. Land use and side friction are significant and positively associated only with slight injury category. These findings provide valuable insights into the causes and factors affecting the injury severity patterns of rollover crashes, and thus can help develop effective countermeasures to reduce the severity of rollover crashes. The model comparison results show that the REGOP model is found to outperform the MXL model in terms of goodness-of-fit measures, and also is significantly superior to other extensions of ordered probit models, including generalized ordered probit and random-effects ordered probit (REOP) models. As a result, this research introduces REGOP as a promising tool for future research focusing on crash injury severity. Copyright © 2017 Elsevier Ltd. All rights reserved.
Delamination Modeling of Composites for Improved Crash Analysis
NASA Technical Reports Server (NTRS)
Fleming, David C.
1999-01-01
Finite element crash modeling of composite structures is limited by the inability of current commercial crash codes to accurately model delamination growth. Efforts are made to implement and assess delamination modeling techniques using a current finite element crash code, MSC/DYTRAN. Three methods are evaluated, including a straightforward method based on monitoring forces in elements or constraints representing an interface; a cohesive fracture model proposed in the literature; and the virtual crack closure technique commonly used in fracture mechanics. Results are compared with dynamic double cantilever beam test data from the literature. Examples show that it is possible to accurately model delamination propagation in this case. However, the computational demands required for accurate solution are great and reliable property data may not be available to support general crash modeling efforts. Additional examples are modeled including an impact-loaded beam, damage initiation in laminated crushing specimens, and a scaled aircraft subfloor structures in which composite sandwich structures are used as energy-absorbing elements. These examples illustrate some of the difficulties in modeling delamination as part of a finite element crash analysis.
Chen, Chen; Xie, Yuanchang
2016-06-01
Annual Average Daily Traffic (AADT) is often considered as a main covariate for predicting crash frequencies at urban and suburban intersections. A linear functional form is typically assumed for the Safety Performance Function (SPF) to describe the relationship between the natural logarithm of expected crash frequency and covariates derived from AADTs. Such a linearity assumption has been questioned by many researchers. This study applies Generalized Additive Models (GAMs) and Piecewise Linear Negative Binomial (PLNB) regression models to fit intersection crash data. Various covariates derived from minor-and major-approach AADTs are considered. Three different dependent variables are modeled, which are total multiple-vehicle crashes, rear-end crashes, and angle crashes. The modeling results suggest that a nonlinear functional form may be more appropriate. Also, the results show that it is important to take into consideration the joint safety effects of multiple covariates. Additionally, it is found that the ratio of minor to major-approach AADT has a varying impact on intersection safety and deserves further investigations. Copyright © 2016 Elsevier Ltd. All rights reserved.
Powered two-wheeler riders' risk of crashes associated with filtering on urban roads.
Clabaux, Nicolas; Fournier, Jean-Yves; Michel, Jean-Emmanuel
2017-02-17
The objective of this study is to estimate the crash risk per kilometer traveled by powered two-wheeler (PTW) riders filtering through traffic on urban roads. Using the traffic injury crashes recorded by the police over a period of 3 years on 14 sections of urban roads in the city of Marseille, France, and a campaign of observations of PTWs, the crash risk per kilometer traveled by PTWs filtering was estimated and compared to the risk of PTWs that did not filter. The results show that the risk of PTW riders being involved in injury crashes while filtering is significantly higher than the risk for riders who do not filter. For the 14 sections studied, it is 3.94 times greater (95% confidence interval [CI], 2.63, 5.89). This excess risk occurred for all PTW categories. Furthermore, no space appears to be safer than the others for filtering. Riders filtering forward along the axis of the carriageway, along bus lanes, or between traffic lanes (lane-splitting) all have a crash risk greater than the risk of those who do not filter. All measures limiting the practice of filtering by PTWs on urban roads would probably contribute to improving the safety of their users.
"Crashing the gates" - selection criteria for television news reporting of traffic crashes.
De Ceunynck, Tim; De Smedt, Julie; Daniels, Stijn; Wouters, Ruud; Baets, Michèle
2015-07-01
This study investigates which crash characteristics influence the probability that the crash is reported in the television news. To this purpose, all news items from the period 2006-2012 about traffic crashes from the prime time news of two Belgian television channels are linked to the official injury crash database. Logistic regression models are built for the database of all injury crashes and for the subset of fatal crashes to identify crash characteristics that correlate with a lower or higher probability of being reported in the news. A number of significant biases in terms of crash severity, time, place, types of involved road users and victims' personal characteristics are found in the media reporting of crashes. More severe crashes are reported in the media more easily than less severe crashes. Significant fluctuations in media reporting probability through time are found in terms of the year and month in which the crash took place. Crashes during week days are generally less reported in the news. The geographical area (province) in which the crash takes place also has a significant impact on the probability of being reported in the news. Crashes on motorways are significantly more represented in the news. Regarding the age of the involved victims, a clear trend of higher media reporting rates of crashes involving young victims or young fatalities is observed. Crashes involving female fatalities are also more frequently reported in the news. Furthermore, crashes involving a bus have a significantly higher probability of being reported in the news, while crashes involving a motorcycle have a significantly lower probability. Some models also indicate a lower reporting rate of crashes involving a moped, and a higher reporting rate of crashes involving heavy goods vehicles. These biases in media reporting can create skewed perceptions in the general public about the prevalence of traffic crashes and eventually may influence people's behaviour. Copyright © 2015 Elsevier Ltd. All rights reserved.
Chung, Younshik
2018-02-01
In-vehicle recording devices have enabled recent changes in methodological paradigms for traffic safety research. Such devices include event data recorders (EDRs), vehicle black boxes (VBBs), and various sensors used in naturalistic driving studies (NDSs). These technologies may help improve the validity of models used to assess impacts on traffic safety. The objective of this study is to analyze the injury severity in taxi-pedestrian crashes using the accurate crash data from VBBs, such as the time-to-collision (TTC), speed, angle, and region of the crash. VBB data from a two-year period (2010-2011) were collected from taxis operating in Incheon, South Korea. An ordered probit model was then applied to analyze the injury severity in crashes. Five variables were found to have a greater effect on injury severity: crash speed, crashes in no-median sections, crashes where the secondary impact object of pedestrians was the crash vehicle, crashes where the third impact object of pedestrians was another moving vehicle, and crashes where the third impact region of pedestrians was their head. However, injuries were less severe in crashes where the first impact region on the pedestrian was their leg, crashes with the car moving in a straight line, and crashes involving junior high school students. Copyright © 2017 Elsevier Ltd. All rights reserved.
Development of a speeding-related crash typology
DOT National Transportation Integrated Search
2010-04-01
Speeding, the driver behavior of exceeding the posted speed limit or driving too fast for conditions, has consistently been estimated to be a contributing factor to a significant percentage of fatal and nonfatal crashes. The U.S. Department of Transp...
Truck crash severity in New York city: An investigation of the spatial and the time of day effects.
Zou, Wei; Wang, Xiaokun; Zhang, Dapeng
2017-02-01
This paper investigates the differences between single-vehicle and multi-vehicle truck crashes in New York City. The random parameter models take into account the time of day effect, the heterogeneous truck weight effect and other influencing factors such as crash characteristics, driver and vehicle characteristics, built environment factors and traffic volume attributes. Based on the results from the co-location quotient analysis, a spatial generalized ordered probit model is further developed to investigate the potential spatial dependency among single-vehicle truck crashes. The sample is drawn from the state maintained incident data, the publicly available Smart Location Data, and the BEST Practices Model (BPM) data from 2008 to 2012. The result shows that there exists a substantial difference between factors influencing single-vehicle and multi-vehicle truck crash severity. It also suggests that heterogeneity does exist in the truck weight, and it behaves differently in single-vehicle and multi-vehicle truck crashes. Furthermore, individual truck crashes are proved to be spatially dependent events for both single and multi-vehicle crashes. Last but not least, significant time of day effects were found for PM and night time slots, crashes that occurred in the afternoons and at nights were less severe in single-vehicle crashes, but more severe in multi-vehicle crashes. Copyright © 2016. Published by Elsevier Ltd.
Fitzpatrick, Cole D; Rakasi, Saritha; Knodler, Michael A
2017-01-01
Speed is one of the most important factors in traffic safety as higher speeds are linked to increased crash risk and higher injury severities. Nearly a third of fatal crashes in the United States are designated as "speeding-related", which is defined as either "the driver behavior of exceeding the posted speed limit or driving too fast for conditions." While many studies have utilized the speeding-related designation in safety analyses, no studies have examined the underlying accuracy of this designation. Herein, we investigate the speeding-related crash designation through the development of a series of logistic regression models that were derived from the established speeding-related crash typologies and validated using a blind review, by multiple researchers, of 604 crash narratives. The developed logistic regression model accurately identified crashes which were not originally designated as speeding-related but had crash narratives that suggested speeding as a causative factor. Only 53.4% of crashes designated as speeding-related contained narratives which described speeding as a causative factor. Further investigation of these crashes revealed that the driver contributing code (DCC) of "driving too fast for conditions" was being used in three separate situations. Additionally, this DCC was also incorrectly used when "exceeding the posted speed limit" would likely have been a more appropriate designation. Finally, it was determined that the responding officer only utilized one DCC in 82% of crashes not designated as speeding-related but contained a narrative indicating speed as a contributing causal factor. The use of logistic regression models based upon speeding-related crash typologies offers a promising method by which all possible speeding-related crashes could be identified. Published by Elsevier Ltd.
Linear regression crash prediction models : issues and proposed solutions.
DOT National Transportation Integrated Search
2010-05-01
The paper develops a linear regression model approach that can be applied to : crash data to predict vehicle crashes. The proposed approach involves novice data aggregation : to satisfy linear regression assumptions; namely error structure normality ...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wenzel, Tom P.
In its 2012 report NHTSA simulated the effect four fleetwide mass reduction scenarios would have on the change in annual fatalities. NHTSA estimated that the most aggressive of these scenarios (reducing mass 5.2% in heavier light trucks and 2.6% in all other vehicles types except lighter cars) would result in a small reduction in societal fatalities. LBNL replicated the methodology NHTSA used to simulate six mass reduction scenarios, including the mass reductions recommended in the 2015 NRC committee report, and estimated in 2021 and 2025 by EPA in the TAR, using the updated data through 2012. The analysis indicates thatmore » the estimated x change in fatalities under each scenario based on the updated analysis is comparable to that in the 2012 analysis, but less beneficial or more detrimental than that in the 2016 analysis. For example, an across the board 100-lb reduction in mass would result in an estimated 157 additional annual fatalities based on the 2012 analysis, but would result in only an estimated 91 additional annual fatalities based on the 2016 analysis, and an additional 87 fatalities based on the current analysis. The mass reductions recommended by the 2015 NRC committee report6 would result in a 224 increase in annual fatalities in the 2012 analysis, a 344 decrease in annual fatalities in the 2016 analysis, and a 141 increase in fatalities in the current analysis. The mass reductions EPA estimated for 2025 in the TAR7 would result in a 203 decrease in fatalities based on the 2016 analysis, but an increase of 39 fatalities based on the current analysis. These results support NHTSA’s conclusion from its 2012 study that, when footprint is held fixed, “no judicious combination of mass reductions in the various classes of vehicles results in a statistically significant fatality increase and many potential combinations are safety-neutral as point estimates.”Like the previous NHTSA studies, this updated report concludes that the estimated effect of mass reduction while maintaining footprint on societal U.S. fatality risk is small, and not statistically significant at the 95% or 90% confidence level for all vehicle types based on the jack-knife method NHTSA used. This report also finds that the estimated effects of other control variables, such as vehicle type, specific safety technologies, and crash conditions such as whether the crash occurred at night, in a rural county, or on a high-speed road, on risk are much larger, in some cases two orders of magnitude larger, than the estimated effect of mass or footprint reduction on risk. Finally, this report shows that after accounting for the many vehicle, driver, and crash variables NHTSA used in its regression analyses, there remains a wide variation in risk by vehicle make and model, and this variation is unrelated to vehicle mass. Although the purpose of the NHTSA and LBNL reports is to estimate the effect of vehicle mass reduction on societal risk, this is not exactly what the regression models are estimating. Rather, they are estimating the recent historical relationship between mass and risk, after accounting for most measurable differences between vehicles, drivers, and crash times and locations. In essence, the regression models are comparing the risk of a 2600-lb Dodge Neon with that of a 2500-lb Honda Civic, after attempting to account for all other differences between the two vehicles. The models are not estimating the effect of literally removing 100 pounds from the Neon, leaving everything else unchanged. In addition, the analyses are based on the relationship of vehicle mass and footprint on risk for recent vehicle designs (model year 2004 to 2011). These relationships may or may not continue into the future as manufacturers utilize new vehicle designs and incorporate new technologies, such as more extensive use of strong lightweight materials and specific safety technologies. Therefore, throughout this report we use the phrase “the estimated effect of mass (or footprint) reduction on risk” as shorthand for “the estimated change in risk as a function of its relationship to mass (or footprint) for vehicle models of recent design.”« less
Crash Certification by Analysis - Are We There Yet?
NASA Technical Reports Server (NTRS)
Jackson, Karen E.; Fasanella, Edwin L.; Lyle, Karen H.
2006-01-01
This paper addresses the issue of crash certification by analysis. This broad topic encompasses many ancillary issues including model validation procedures, uncertainty in test data and analysis models, probabilistic techniques for test-analysis correlation, verification of the mathematical formulation, and establishment of appropriate qualification requirements. This paper will focus on certification requirements for crashworthiness of military helicopters; capabilities of the current analysis codes used for crash modeling and simulation, including some examples of simulations from the literature to illustrate the current approach to model validation; and future directions needed to achieve "crash certification by analysis."
DOT National Transportation Integrated Search
2001-01-01
The National Highway Traffic Safety Administration (NHTSA), the federal agency responsible for reducing accidents, deaths, and injuries resulting from motor vehicle crashes on the nation's highways, estimates that over 6 million automobile accidents ...
DOT National Transportation Integrated Search
2014-04-01
The National Highway Traffic Safety Administration estimates : 10% of fatal crashes (3,328) and 18% of injury crashes (421,000) : were attributable to distracted driving in 2012. Previous : research indicates dedicated law enforcement over a specifie...
Accuracy of AHOF400 with a moment-measuring load cell barrier.
DOT National Transportation Integrated Search
2011-06-13
Several performance measures derived from rigid : barrier crash testing have been proposed to assess : vehicle-to-vehicle crash compatibility. One such : measure, the Average Height of Force 400 (AHOF400) : [1], has been proposed to estimate the heig...
Visual demand of curves and fog-limited sight distance and its relationship to brake response time.
DOT National Transportation Integrated Search
2006-05-01
Driver distraction is a major contributing factor to automobile crashes. National Highway Traffic Safety Administration (NHTSA) has estimated that approximately 25% of crashes are attributed to driver distraction and inattention (Wang, Knipling, & Go...
Modeling Intersection Crash Counts and Traffic Volume
DOT National Transportation Integrated Search
1998-07-01
This research explored the feasibility of modeling crash counts at intersections with use of available exposure measures. The basic purpose of "exposure" is to serve as a size factor to allow comparison of crash counts among populations of different ...
Torres, Pedro; Romano, Eduardo; Voas, Robert B.; de la Rosa, Mario; Lacey, John H.
2014-01-01
Introduction The literature presents a puzzling picture of Latinos being overrepresented in alcohol-related crashes, but not in noncrash drinking and driving. This report examines if, like other demographic variables in which some groups are at a higher crash risk than others (e.g., young drivers), different racial/ethnic groups face different crash risks Method This study compares blood-alcohol information from the 2006–2007 U.S. Fatality Analysis Reporting System (FARS) with control data from the 2007 U.S. National Roadside Survey. Logistic regression, including a dual interaction between BAC and race/ethnicity, was used to estimate crash risk at different BAC levels. Results It was found that, although Hispanic and African-American drivers were less likely to be involved in single-vehicle crashes than their White counterparts, all drivers face similar BAC relative crash risk regardless of their group membership. The overrepresentation of Latino drivers in alcohol-related crashes could be explained by differences in patterns of consumption, driving exposure, lack of awareness of driving rules, and/or socioeconomics. PMID:24529097
Wagenaar, Alexander C; Maldonado-Molina, Mildred M; Erickson, Darin J; Ma, Linan; Tobler, Amy L; Komro, Kelli A
2007-09-01
We examined effects of state statutory changes in DUI fine or jail penalties for firsttime offenders from 1976 to 2002. A quasi-experimental time-series design was used (n=324 monthly observations). Four outcome measures of drivers involved in alcohol-related fatal crashes are: single-vehicle nighttime, low BAC (0.01-0.07g/dl), medium BAC (0.08-0.14g/dl), high BAC (>/=0.15g/dl). All analyses of BAC outcomes included multiple imputation procedures for cases with missing data. Comparison series of non-alcohol-related crashes were included to efficiently control for effects of other factors. Statistical models include state-specific Box-Jenkins ARIMA models, and pooled general linear mixed models. Twenty-six states implemented mandatory minimum fine policies and 18 states implemented mandatory minimum jail penalties. Estimated effects varied widely from state to state. Using variance weighted meta-analysis methods to aggregate results across states, mandatory fine policies are associated with an average reduction in fatal crash involvement by drivers with BAC>/=0.08g/dl of 8% (averaging 13 per state per year). Mandatory minimum jail policies are associated with a decline in single-vehicle nighttime fatal crash involvement of 6% (averaging 5 per state per year), and a decline in low-BAC cases of 9% (averaging 3 per state per year). No significant effects were observed for the other outcome measures. The overall pattern of results suggests a possible effect of mandatory fine policies in some states, but little effect of mandatory jail policies.
Bicycle Guidelines and Crash Rates on Cycle Tracks in the United States
Morency, Patrick; Miranda-Moreno, Luis F.; Willett, Walter C.; Dennerlein, Jack T.
2013-01-01
Objectives. We studied state-adopted bicycle guidelines to determine whether cycle tracks (physically separated, bicycle-exclusive paths adjacent to sidewalks) were recommended, whether they were built, and their crash rate. Methods. We analyzed and compared US bicycle facility guidelines published between 1972 and 1999. We identified 19 cycle tracks in the United States and collected extensive data on cycle track design, usage, and crash history from local communities. We used bicycle counts and crash data to estimate crash rates. Results. A bicycle facility guideline written in 1972 endorsed cycle tracks but American Association of State Highway and Transportation Officials (AASHTO) guidelines (1974–1999) discouraged or did not include cycle tracks and did not cite research about crash rates on cycle tracks. For the 19 US cycle tracks we examined, the overall crash rate was 2.3 (95% confidence interval = 1.7, 3.0) per 1 million bicycle kilometers. Conclusions. AASHTO bicycle guidelines are not explicitly based on rigorous or up-to-date research. Our results show that the risk of bicycle–vehicle crashes is lower on US cycle tracks than published crashes rates on roadways. This study and previous investigations support building cycle tracks. PMID:23678920
How to determine an optimal threshold to classify real-time crash-prone traffic conditions?
Yang, Kui; Yu, Rongjie; Wang, Xuesong; Quddus, Mohammed; Xue, Lifang
2018-08-01
One of the proactive approaches in reducing traffic crashes is to identify hazardous traffic conditions that may lead to a traffic crash, known as real-time crash prediction. Threshold selection is one of the essential steps of real-time crash prediction. And it provides the cut-off point for the posterior probability which is used to separate potential crash warnings against normal traffic conditions, after the outcome of the probability of a crash occurring given a specific traffic condition on the basis of crash risk evaluation models. There is however a dearth of research that focuses on how to effectively determine an optimal threshold. And only when discussing the predictive performance of the models, a few studies utilized subjective methods to choose the threshold. The subjective methods cannot automatically identify the optimal thresholds in different traffic and weather conditions in real application. Thus, a theoretical method to select the threshold value is necessary for the sake of avoiding subjective judgments. The purpose of this study is to provide a theoretical method for automatically identifying the optimal threshold. Considering the random effects of variable factors across all roadway segments, the mixed logit model was utilized to develop the crash risk evaluation model and further evaluate the crash risk. Cross-entropy, between-class variance and other theories were employed and investigated to empirically identify the optimal threshold. And K-fold cross-validation was used to validate the performance of proposed threshold selection methods with the help of several evaluation criteria. The results indicate that (i) the mixed logit model can obtain a good performance; (ii) the classification performance of the threshold selected by the minimum cross-entropy method outperforms the other methods according to the criteria. This method can be well-behaved to automatically identify thresholds in crash prediction, by minimizing the cross entropy between the original dataset with continuous probability of a crash occurring and the binarized dataset after using the thresholds to separate potential crash warnings against normal traffic conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.
Computer simulations and experimental study on crash box of automobile in low speed collision
NASA Astrophysics Data System (ADS)
Liu, Yanjie; Ding, Lin; Yan, Shengyuan; Yang, Yongsheng
2008-11-01
Based on the problems of energy-absorbing components in the automobile low speed collision process, according to crash box frontal crash test in low speed as the example, the simulation analysis of crash box impact process was carried out by Hyper Mesh and LS-DYNA. Each parameter on the influence modeling was analyzed by mathematics analytical solution and test comparison, which guaranteed that the model was accurate. Combination of experiment and simulation result had determined the weakness part of crash box structure crashworthiness aspect, and improvement method of crash box crashworthiness was discussed. Through numerical simulation of the impact process of automobile crash box, the obtained analysis result was used to optimize the design of crash box. It was helpful to improve the vehicles structure and decrease the collision accident loss at most. And it was also provided a useful method for the further research on the automobile collision.
Tay, Richard; Rifaat, Shakil Mohammad; Chin, Hoong Chor
2008-07-01
Leaving the scene of a crash without reporting it is an offence in most countries and many studies have been devoted to improving ways to identify hit-and-run vehicles and the drivers involved. However, relatively few studies have been conducted on identifying factors that contribute to the decision to run after the crash. This study identifies the factors that are associated with the likelihood of hit-and-run crashes including driver characteristics, vehicle types, crash characteristics, roadway features and environmental characteristics. Using a logistic regression model to delineate hit-and-run crashes from nonhit-and-run crashes, this study found that drivers were more likely to run when crashes occurred at night, on a bridge and flyover, bend, straight road and near shop houses; involved two vehicles, two-wheel vehicles and vehicles from neighboring countries; and when the driver was a male, minority, and aged between 45 and 69. On the other hand, collisions involving right turn and U-turn maneuvers, and occurring on undivided roads were less likely to be hit-and-run crashes.
Understanding the bursty electron cyclotron emission during a sawtooth crash in the HT-7 tokamak
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Erzhong, E-mail: rzhonglee@ipp.ac.cn; Hu, Liqun; Chen, Kaiyun
2014-01-15
Bursts in electron cyclotron emission (ECE) were observed during sawtooth crashes in HT-7 in discharges with ion cyclotron resonance heating injected near the q = 1 rational surface (q is the safety factor). The local ECE measurement indicated that the bursty radiation is only observed on channels near but a little away outward from the q = 1 magnetic surface. In conjunction with the soft x-ray tomography analysis, it was determined that, for the first time, only a compression process survives in the later stage of fast magnetic reconnection but before prompt heat transport. The compression enhanced the electron radiation temperature, the increased amplitudemore » of which agreed well with the estimation according to a kinetic compression theory model [R. J. Hastie and T. C. Hender, Nucl. Fusion 28, 585 (1988)]. This paper presents the experimental evidence that there indeed exists a transient compression phase which results in the bursty ECE radiation during a sawtooth crash.« less
A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis.
Zeng, Ziqiang; Zhu, Wenbo; Ke, Ruimin; Ash, John; Wang, Yinhai; Xu, Jiuping; Xu, Xinxin
2017-02-01
The mixed multinomial logit (MNL) approach, which can account for unobserved heterogeneity, is a promising unordered model that has been employed in analyzing the effect of factors contributing to crash severity. However, its basic assumption of using a linear function to explore the relationship between the probability of crash severity and its contributing factors can be violated in reality. This paper develops a generalized nonlinear model-based mixed MNL approach which is capable of capturing non-monotonic relationships by developing nonlinear predictors for the contributing factors in the context of unobserved heterogeneity. The crash data on seven Interstate freeways in Washington between January 2011 and December 2014 are collected to develop the nonlinear predictors in the model. Thirteen contributing factors in terms of traffic characteristics, roadway geometric characteristics, and weather conditions are identified to have significant mixed (fixed or random) effects on the crash density in three crash severity levels: fatal, injury, and property damage only. The proposed model is compared with the standard mixed MNL model. The comparison results suggest a slight superiority of the new approach in terms of model fit measured by the Akaike Information Criterion (12.06 percent decrease) and Bayesian Information Criterion (9.11 percent decrease). The predicted crash densities for all three levels of crash severities of the new approach are also closer (on average) to the observations than the ones predicted by the standard mixed MNL model. Finally, the significance and impacts of the contributing factors are analyzed. Copyright © 2016 Elsevier Ltd. All rights reserved.
Zou, Yaotian; Tarko, Andrew P
2018-02-01
The objective of this study was to develop crash modification factors (CMFs) and estimate the average crash costs applicable to a wide range of road-barrier scenarios that involved three types of road barriers (concrete barriers, W-beam guardrails, and high-tension cable barriers) to produce a suitable basis for comparing barrier-oriented design alternatives and road improvements. The intention was to perform the most comprehensive and in-depth analysis allowed by the cross-sectional method and the crash data available in Indiana. To accomplish this objective and to use the available data efficiently, the effects of barrier were estimated on the frequency of barrier-relevant (BR) crashes, the types of harmful events and their occurrence during a BR crash, and the severity of BR crash outcomes. The harmful events component added depth to the analysis by connecting the crash onset with its outcome. Further improvement of the analysis was accomplished by considering the crash outcome severity of all the individuals involved in a crash and not just drivers, utilizing hospital data, and pairing the observations with and without road barriers along same or similar road segments to better control the unobserved heterogeneity. This study confirmed that the total number of BR crashes tended to be higher where medians had installed barriers, mainly due to collisions with barriers and, in some cases, with other vehicles after redirecting vehicles back to traffic. These undesirable effects of barriers were surpassed by the positive results of reducing cross-median crashes, rollover events, and collisions with roadside hazards. The average cost of a crash (unit cost) was reduced by 50% with cable barriers installed in medians wider than 50ft. A similar effect was concluded for concrete barriers and guardrails installed in medians narrower than 50ft. The studied roadside guardrails also reduced the unit cost by 20%-30%. Median cable barriers were found to be the most effective among all the studied barriers due to the smaller increase in the crash frequency caused by these barriers and the less severe injury outcomes. More specifically, the occupants of vehicles colliding with near-side cable barriers tended to have less severe injuries than occupants of vehicles entering the median from median's farther side. The near-side cable barriers provided protection against rollover inside the median and against a potentially dangerous collision with or running over the median drain; therefore, the greatest safety benefit can be expected where cable barriers are installed at both edges of the median. The CMFs and unit crash costs for 48 road-barrier scenarios produced in this study are included in this paper. Copyright © 2017 Elsevier Ltd. All rights reserved.
Safety effects of exclusive and concurrent signal phasing for pedestrian crossing.
Zhang, Yaohua; Mamun, Sha A; Ivan, John N; Ravishanker, Nalini; Haque, Khademul
2015-10-01
This paper describes the estimation of pedestrian crash count and vehicle interaction severity prediction models for a sample of signalized intersections in Connecticut with either concurrent or exclusive pedestrian phasing. With concurrent phasing, pedestrians cross at the same time as motor vehicle traffic in the same direction receives a green phase, while with exclusive phasing, pedestrians cross during their own phase when all motor vehicle traffic on all approaches is stopped. Pedestrians crossing at each intersection were observed and classified according to the severity of interactions with motor vehicles. Observation intersections were selected to represent both types of signal phasing while controlling for other physical characteristics. In the nonlinear mixed models for interaction severity, pedestrians crossing on the walk signal at an exclusive signal experienced lower interaction severity compared to those crossing on the green light with concurrent phasing; however, pedestrians crossing on a green light where an exclusive phase was available experienced higher interaction severity. Intersections with concurrent phasing have fewer total pedestrian crashes than those with exclusive phasing but more crashes at higher severity levels. It is recommended that exclusive pedestrian phasing only be used at locations where pedestrians are more likely to comply. Copyright © 2015. Published by Elsevier Ltd.
Association of rear seat safety belt use with death in a traffic crash: a matched cohort study.
Zhu, Motao; Cummings, Peter; Chu, Haitao; Cook, Lawrence J
2007-06-01
To estimate the association of rear seat safety belt use with death in a traffic crash. Matched cohort study. The US during 2000 through 2004. Drivers (10,427) and rear seat passengers (15,922) in passenger vehicles that crashed and had at least one driver or rear passenger death. Data from the Fatality Analysis Reporting System. The adjusted relative risk (aRR) of death for a belted rear seat passenger compared with an otherwise similar unbelted rear passenger. Safety belt use was associated with a reduced risk of death for rear car occupants: outboard rear seat aRR 0.42 (95% CI 0.38 to 0.46), and center rear seat aRR 0.30 (95% CI 0.20 to 0.44). For rear occupants of light trucks, vans, and utility vehicles, the estimates were: outboard aRR 0.25 (95% CI 0.21 to 0.29), center aRR 0.34 (95% CI 0.24 to 0.48). If the authors' estimates are causal, traffic crash mortality can be reduced for rear occupants by approximately 55-75% if they use safety belts.
Fell, James C.; Todd, Michael; Voas, Robert B.
2011-01-01
Introduction The high crash rate of youthful novice drivers has been recognized for half a century. Over the last decade, graduated driver licensing (GDL) systems, which extend the period of supervised driving and limit the novice’s exposure to higher-risk conditions (such as nighttime driving) has effectively reduced crash involvements of novice drivers. Method This study used data from the Fatality Analysis Reporting System (FARS) and the implementation dates of GDL laws in a state-by-year panel study to evaluate the effectiveness of two key elements of GDL laws: nighttime restrictions and passenger limitations. Results Nighttime restrictions were found to reduce 16- and 17-year-old driver involvements in nighttime fatal crashes by an estimated 10% and 16- and 17-year-old drinking drivers in nighttime fatal crashes by 13%. Passenger restrictions were found to reduce 16- and 17-year-old driver involvements in fatal crashes with teen passengers by an estimated 9%. Conclusions These results confirm the effectiveness of these provisions in GDL systems. Impact on Public Health The results of this study indicate that nighttime restrictions and passenger limitations are very important components of any GDL law. PMID:22017831
Stigson, Helena; Krafft, Maria; Tingvall, Claes
2008-10-01
To evaluate if the Swedish Road Administration (SRA) model for a safe road transport system, which includes the interaction between the road user, the vehicle, and the road, could be used to classify fatal car crashes according to some safety indicators. Also, to present a development of the model to better identify system weakness. Real-life crashes with a fatal outcome were classified according to the vehicle's safety rating by Euro NCAP (European Road Assessment Programme) and fitment of ESC (Electronic Stability Control). For each crash, the road was also classified according to EuroRAP (European Road Assessment Programme) criteria, and human behavior in terms of speeding, seat belt use, and driving under the influence of alcohol. Each crash was compared with the model criteria, to identify components that might have contributed to fatal outcome. All fatal crashes where a car occupant was killed that occurred in Sweden during 2004 were included: in all, 215 crashes with 248 fatalities. The data were collected from the in-depth fatal crash data of the Swedish Road Administration (SRA). It was possible to classify 93% of the fatal car crashes according to the SRA model. A number of shortcomings in the criteria were identified since the model did not address rear-end or animal collisions or collisions with stationary/parked vehicles or trailers (18 out of 248 cases). Using the further developed model, it was possible to identify that most of the crashes occurred when two or all three components interacted (in 85 of the total 230 cases). Noncompliance with safety criteria for the road user, the vehicle, and the road led to fatal outcome in 43, 27, and 75 cases, respectively. The SRA model was found to be useful for classifying fatal crashes but needs to be further developed to identify how the components interact and thereby identify weaknesses in the road traffic system. This developed model might be a tool to systematically identify which of the components are linked to fatal outcome. In the presented study, fatal outcomes were mostly related to an interaction between the three components: the road, the vehicle, and the road user. Of the three components, the road was the one that was most often linked to a fatal outcome.
Injury Risk Functions in Frontal Impacts Using Data from Crash Pulse Recorders
Stigson, Helena; Kullgren, Anders; Rosén, Erik
2012-01-01
Knowledge of how crash severity influences injury risk in car crashes is essential in order to create a safe road transport system. Analyses of real-world crashes increase the ability to obtain such knowledge. The aim of this study was to present injury risk functions based on real-world frontal crashes where crash severity was measured with on-board crash pulse recorders. Results from 489 frontal car crashes (26 models of four car makes) with recorded acceleration-time history were analysed. Injury risk functions for restrained front seat occupants were generated for maximum AIS value of two or greater (MAIS2+) using multiple logistic regression. Analytical as well as empirical injury risk was plotted for several crash severity parameters; change of velocity, mean acceleration and peak acceleration. In addition to crash severity, the influence of occupant age and gender was investigated. A strong dependence between injury risk and crash severity was found. The risk curves reflect that small changes in crash severity may have a considerable influence on the risk of injury. Mean acceleration, followed by change of velocity, was found to be the single variable that best explained the risk of being injured (MAIS2+) in a crash. Furthermore, all three crash severity parameters were found to predict injury better than age and gender. However, age was an important factor. The very best model describing MAIS2+ injury risk included delta V supplemented by an interaction term of peak acceleration and age. PMID:23169136
A Front-End Analysis Of Rear-End Crashes
DOT National Transportation Integrated Search
1992-05-17
THIS PAPER DESCRIBES THE APPLICATION OF A SEVEN-STEP CRASH PROBLEM ANALYSIS METHODOLOGY, AS DESCRIBED IN THE PRECEDING PAPER BY LEASURE (1), TO REAR-END CRASHES. THE PAPER SHOWS HOW MODELING OF REAR-END CRASH SCENARIOS AND CANDIDATE COUNTERMEASURE AC...
Kusano, Kristofer D.; Gabler, Hampton C.
2010-01-01
To mitigate the severity of rear-end and other collisions, Pre-Crash Systems (PCS) are being developed. These active safety systems utilize radar and/or video cameras to determine when a frontal crash, such as a front-to-back rear-end collisions, is imminent and can brake autonomously, even with no driver input. Of these PCS features, the effects of autonomous pre-crash braking are estimated. To estimate the maximum potential for injury reduction due to autonomous pre-crash braking in the striking vehicle of rear-end crashes, a methodology is presented for determining 1) the reduction in vehicle crash change in velocity (ΔV) due to PCS braking and 2) the number of injuries that could be prevented due to the reduction in collision severity. Injury reduction was only performed for belted drivers, as unbelted drivers have an unknown risk of being thrown out of position. The study was based on 1,406 rear-end striking vehicles from NASS / CDS years 1993 to 2008. PCS parameters were selected from realistic values and varied to examine the effect on system performance. PCS braking authority was varied from 0.5 G’s to 0.8 G’s while time to collision (TTC) was held at 0.45 seconds. TTC was then varied from 0.3 second to 0.6 seconds while braking authority was held constant at 0.6 G’s. A constant braking pulse (step function) and ramp-up braking pulse were used. The study found that automated PCS braking could reduce the crash ΔV in rear-end striking vehicles by an average of 12% – 50% and avoid 0% – 14% of collisions, depending on PCS parameters. Autonomous PCS braking could potentially reduce the number of injured drivers who are belted by 19% to 57%. PMID:21050603
DOT National Transportation Integrated Search
2002-01-01
One of the primary objectives of the National Highway Traffic Safety Administration (NHTSA) is to reduce : the staggering human toll and property damage that motor vehicle traffic crashes impose on our society. : Crashes each year result in thousands...
DOT National Transportation Integrated Search
2001-07-01
One of the primary objectives of the National Highway Traffic Safety Administration (NHTSA) is to reduce the staggering human toll and property damage that motor vehicle traffic crashes impose on our society. Crashes each year result in thousands of ...
DOT National Transportation Integrated Search
2000-01-01
One of the primary objectives of the National Highway Traffic Safety Administration (NHTSA) is : to reduce the staggering human toll and property damage that motor vehicle traffic crashes impose : on our society. Crashes each year result in thousands...
Application of Poisson random effect models for highway network screening.
Jiang, Ximiao; Abdel-Aty, Mohamed; Alamili, Samer
2014-02-01
In recent years, Bayesian random effect models that account for the temporal and spatial correlations of crash data became popular in traffic safety research. This study employs random effect Poisson Log-Normal models for crash risk hotspot identification. Both the temporal and spatial correlations of crash data were considered. Potential for Safety Improvement (PSI) were adopted as a measure of the crash risk. Using the fatal and injury crashes that occurred on urban 4-lane divided arterials from 2006 to 2009 in the Central Florida area, the random effect approaches were compared to the traditional Empirical Bayesian (EB) method and the conventional Bayesian Poisson Log-Normal model. A series of method examination tests were conducted to evaluate the performance of different approaches. These tests include the previously developed site consistence test, method consistence test, total rank difference test, and the modified total score test, as well as the newly proposed total safety performance measure difference test. Results show that the Bayesian Poisson model accounting for both temporal and spatial random effects (PTSRE) outperforms the model that with only temporal random effect, and both are superior to the conventional Poisson Log-Normal model (PLN) and the EB model in the fitting of crash data. Additionally, the method evaluation tests indicate that the PTSRE model is significantly superior to the PLN model and the EB model in consistently identifying hotspots during successive time periods. The results suggest that the PTSRE model is a superior alternative for road site crash risk hotspot identification. Copyright © 2013 Elsevier Ltd. All rights reserved.
IIHS side crash test ratings and occupant death risk in real-world crashes.
Teoh, Eric R; Lund, Adrian K
2011-10-01
To evaluate how well the Insurance Institute for Highway Safety (IIHS) side crash test ratings predict real-world occupant death risk in side-impact crashes. The IIHS has been evaluating passenger vehicle side crashworthiness since 2003. In the IIHS side crash test, a vehicle is impacted perpendicularly on the driver's side by a moving deformable barrier simulating a typical sport utility vehicle (SUV) or pickup. Injury ratings are computed for the head/neck, torso, and pelvis/leg, and vehicles are rated based on their ability to protect occupants' heads and resist occupant compartment intrusion. Component ratings are combined into an overall rating of good, acceptable, marginal, or poor. A driver-only rating was recalculated by omitting rear passenger dummy data. Data were extracted from the Fatality Analysis Reporting System (FARS) and National Automotive Sampling System/General Estimates System (NASS/GES) for the years 2000-2009. Analyses were restricted to vehicles with driver side air bags with head and torso protection as standard features. The risk of driver death was computed as the number of drivers killed (FARS) divided by the number involved (NASS/GES) in left-side impacts and was modeled using logistic regression to control for the effects of driver age and gender and vehicle type and curb weight. Death rates per million registered vehicle years were computed for all outboard occupants and compared by overall rating. Based on the driver-only rating, drivers of vehicles rated good were 70 percent less likely to die when involved in left-side crashes than drivers of vehicles rated poor, after controlling for driver and vehicle factors. Compared with vehicles rated poor, driver death risk was 64 percent lower for vehicles rated acceptable and 49 percent lower for vehicles rated marginal. All 3 results were statistically significant. Among components, vehicle structure rating exhibited the strongest relationship with driver death risk. The vehicle registration-based results for drivers were similar, suggesting that the benefit was not due to differences in crash risk. The same pattern of results held for outboard occupants in nearside crashes per million registered vehicle years and, with the exception of marginally rated vehicles, also held for other crash types. Results show that IIHS side crash test ratings encourage designs that improve crash protection in meaningful ways beyond encouraging head protection side air bags, particularly by promoting vehicle structures that limit occupant compartment intrusion. Results further highlight the need for a strong occupant compartment and its influence in all types of crashes.
Cicchino, Jessica B
2017-02-01
The objective of this study was to evaluate the effectiveness of forward collision warning (FCW) alone, a low-speed autonomous emergency braking (AEB) system operational at speeds up to 19mph that does not warn the driver prior to braking, and FCW with AEB that operates at higher speeds in reducing front-to-rear crashes and injuries. Poisson regression was used to compare rates of police-reported crash involvements per insured vehicle year in 22 U.S. states during 2010-2014 between passenger vehicle models with FCW alone or with AEB and the same models where the optional systems were not purchased, controlling for other factors affecting crash risk. Similar analyses compared rates between Volvo 2011-2012 model S60 and 2010-2012 model XC60 vehicles with a standard low-speed AEB system to those of other luxury midsize cars and SUVs, respectively, without the system. FCW alone, low-speed AEB, and FCW with AEB reduced rear-end striking crash involvement rates by 27%, 43%, and 50%, respectively. Rates of rear-end striking crash involvements with injuries were reduced by 20%, 45%, and 56%, respectively, by FCW alone, low-speed AEB, and FCW with AEB, and rates of rear-end striking crash involvements with third-party injuries were reduced by 18%, 44%, and 59%, respectively. Reductions in rear-end striking crashes with third-party injuries were marginally significant for FCW alone, and all other reductions were statistically significant. FCW alone and low-speed AEB reduced rates of being rear struck in rear-end crashes by 13% and 12%, respectively, but FCW with AEB increased rates of rear-end struck crash involvements by 20%. Almost 1 million U.S. police-reported rear-end crashes in 2014 and more than 400,000 injuries in such crashes could have been prevented if all vehicles were equipped with FCW and AEB that perform similarly as systems did for study vehicles. Copyright © 2016 Elsevier Ltd. All rights reserved.
Laituri, Tony R; Sullivan, Donald; Sullivan, Kaye; Prasad, Priya
2004-11-01
A theoretical math model was created to assess the net effect of aging populations versus evolving system designs from the standpoint of thoracic injury potential. The model was used to project the next twenty-five years of thoracic injuries in Canada. The choice of Canada was topical because rulemaking for CMVSS 208 has been proposed recently. The study was limited to properly-belted, front-outboard, adult occupants in 11-1 o'clock frontal crashes. Moreover, only AIS3+ thoracic injury potential was considered. The research consisted of four steps. First, sub-models were developed and integrated. The sub-models were made for numerous real-world effects including population growth, crash involvement, fleet penetration of various systems (via system introduction, vehicle production, and vehicle attrition), and attendant injury risk estimation. Second, existing NASS data were used to estimate the number of AIS3+ chest-injured drivers in Canada in 2001. This served as data for model validation. Third, the projection model was correlated favorably with the 2001 field estimate. Finally, for the scenario that 2004-2030 model-year systems would perform like 2000-2003 model-year systems, a projection was made to estimate the long-term effect of eliminating designs that would not comply with the proposed CMVSS 208. The 2006-2030-projection result for this scenario: 764 occupants would benefit from the proposed regulation. This projection was considered to be conservative because future innovation was not considered, and, to date, the fleet's average chest deflections have been decreasing. The model also predicted that, through 2016, the effect of improving system performance would be more influential than the population-aging effect; thereafter, the population-aging effect would somewhat counteract the effect of improving system performance. This theoretical math model can provide insights for both designers and rule makers.
Prevalence of teen driver errors leading to serious motor vehicle crashes.
Curry, Allison E; Hafetz, Jessica; Kallan, Michael J; Winston, Flaura K; Durbin, Dennis R
2011-07-01
Motor vehicle crashes are the leading cause of adolescent deaths. Programs and policies should target the most common and modifiable reasons for crashes. We estimated the frequency of critical reasons for crashes involving teen drivers, and examined in more depth specific teen driver errors. The National Highway Traffic Safety Administration's (NHTSA) National Motor Vehicle Crash Causation Survey collected data at the scene of a nationally representative sample of 5470 serious crashes between 7/05 and 12/07. NHTSA researchers assigned a single driver, vehicle, or environmental factor as the critical reason for the event immediately leading to each crash. We analyzed crashes involving 15-18 year old drivers. 822 teen drivers were involved in 795 serious crashes, representing 335,667 teens in 325,291 crashes. Driver error was by far the most common reason for crashes (95.6%), as opposed to vehicle or environmental factors. Among crashes with a driver error, a teen made the error 79.3% of the time (75.8% of all teen-involved crashes). Recognition errors (e.g., inadequate surveillance, distraction) accounted for 46.3% of all teen errors, followed by decision errors (e.g., following too closely, too fast for conditions) (40.1%) and performance errors (e.g., loss of control) (8.0%). Inadequate surveillance, driving too fast for conditions, and distracted driving together accounted for almost half of all crashes. Aggressive driving behavior, drowsy driving, and physical impairments were less commonly cited as critical reasons. Males and females had similar proportions of broadly classified errors, although females were specifically more likely to make inadequate surveillance errors. Our findings support prioritization of interventions targeting driver distraction and surveillance and hazard awareness training. Copyright © 2010 Elsevier Ltd. All rights reserved.
Effectiveness of antilock braking systems in reducing motorcycle fatal crash rates.
Teoh, Eric R
2011-04-01
Overbraking and underbraking have been shown to be common factors in motorcycle crashes. Antilock braking systems (ABS) prevent wheels from locking during braking and may make riders less reluctant to apply full braking force. The objective of this study was to evaluate the effect of ABS in fatal motorcycle crashes. Motorcycle drivers involved in fatal crashes per 10,000 registered vehicle years were compared for 13 motorcycle models with optional ABS and those same models without the option during 2003-2008. Motorcycles with optional ABS were included only if the presence of the option could be identified from the vehicle identification number. The rate of fatal motorcycle crashes per 10,000 registered vehicle years was 37 percent lower for ABS models than for their non-ABS versions. ABS appears to be highly effective in preventing fatal motorcycle crashes based on some early adopters of motorcycle ABS technology.
Stigson, Helena; Hill, Julian
2009-10-01
The objective of this study was to evaluate a model for a safe road transport system, based on some safety performance indicators regarding the road user, the vehicle, and the road, by using crashes with fatally and seriously injured car occupants. The study also aimed to evaluate whether the model could be used to identify system weaknesses and components (road user, vehicles, and road) where improvements would yield the highest potential for further reductions in serious injuries. Real-life car crashes with serious injury outcomes (Maximum Abbreviated Injury Scale 2+) were classified according to the vehicle's safety rating by Euro NCAP (European New Car Assessment Programme) and whether the vehicle was fitted with ESC (Electronic Stability Control). For each crash, the road was also classified according to EuroRAP (European Road Assessment Programme) criteria, and human behavior in terms of speeding, seat belt use, and driving under the influence of alcohol/drugs. Each crash was compared and classified according to the model criteria. Crashes where the safety criteria were not met in more than one of the 3 components were reclassified to identify whether all the components were correlated to the injury outcome. In-depth crash injury data collected by the UK On The Spot (OTS) accident investigation project was used in this study. All crashes in the OTS database occurring between 2000 and 2005 with a car occupant with injury rated MAIS2+ were included, for a total of 101 crashes with 120 occupants. It was possible to classify 90 percent of the crashes according to the model. Eighty-six percent of the occupants were injured when more than one of the 3 components were noncompliant with the safety criteria. These cases were reclassified to identify whether all of the components were correlated to the injury outcome. In 39 of the total 108 cases, at least two components were still seen to interact. The remaining cases were only related to one of the safety criteria, namely, the road user (26), the vehicle (19), and the road (24). The criteria for the road and the vehicle did not address multiple event crashes, rear-end crashes, hitting stationary/parked vehicles, or trailers. The model for a safe road transport system was found useful to classify fatal and serious road vehicle crashes. It was possible to classify 90 percent of the crashes according to the safety road transport model. For all these cases it was possible to identify weaknesses and parts of the road transport system with the highest potential to prevent fatal and serious injuries. Injury outcomes were mostly related to an interaction between the 3 components: the road, the vehicle, and the road user.
Kononen, Douglas W; Flannagan, Carol A C; Wang, Stewart C
2011-01-01
A multivariate logistic regression model, based upon National Automotive Sampling System Crashworthiness Data System (NASS-CDS) data for calendar years 1999-2008, was developed to predict the probability that a crash-involved vehicle will contain one or more occupants with serious or incapacitating injuries. These vehicles were defined as containing at least one occupant coded with an Injury Severity Score (ISS) of greater than or equal to 15, in planar, non-rollover crash events involving Model Year 2000 and newer cars, light trucks, and vans. The target injury outcome measure was developed by the Centers for Disease Control and Prevention (CDC)-led National Expert Panel on Field Triage in their recent revision of the Field Triage Decision Scheme (American College of Surgeons, 2006). The parameters to be used for crash injury prediction were subsequently specified by the National Expert Panel. Model input parameters included: crash direction (front, left, right, and rear), change in velocity (delta-V), multiple vs. single impacts, belt use, presence of at least one older occupant (≥ 55 years old), presence of at least one female in the vehicle, and vehicle type (car, pickup truck, van, and sport utility). The model was developed using predictor variables that may be readily available, post-crash, from OnStar-like telematics systems. Model sensitivity and specificity were 40% and 98%, respectively, using a probability cutpoint of 0.20. The area under the receiver operator characteristic (ROC) curve for the final model was 0.84. Delta-V (mph), seat belt use and crash direction were the most important predictors of serious injury. Due to the complexity of factors associated with rollover-related injuries, a separate screening algorithm is needed to model injuries associated with this crash mode. Copyright © 2010 Elsevier Ltd. All rights reserved.
Crash-resistant fuel system effectiveness in civil helicopter crashes.
Hayden, Mark S; Shanahan, Dennis F; Chen, Li-Hui; Baker, Susan P
2005-08-01
Crash-resistant fuel systems (CRFS) have demonstrated close to 100% effectiveness in survivable crashes of Army helicopters, but the technology has been slow to transfer into the civil helicopter arena. Federal standards for civil helicopter CRFS are less stringent than those for military helicopters. A reduction in standards for CRFS in military helicopters is being considered. The goal of this study was to determine whether crashes of civil helicopters with CRFS are less likely to result in post-crash fire than crashes of those without. Crashes of civil helicopters during 1982-2004 were analyzed, comparing Bell 206 helicopters manufactured with CRFS with Aerospatial 350 helicopters manufactured during the same period (post-1981), but lacking CRFS. Bell 206 helicopters with CRFS were also compared with earlier models without CRFS. The highest proportion of crashes with post-crash fires (11.3%) was in AS-350s manufactured after 1981 (non-CRFS), and the lowest (3.7%) was in Bell 206s (with CRFS) [unadjusted risk ratio (RR) = 3.3, 95% confidence interval (CI) = 1.04, 10.50; adjusted for light and weather, RR = 2.81, Cl = 0.82, 9.69]. Earlier models of Bell 206s without CRFS had higher risk of post-crash fire than post-1981 models with CRFS (7.4% vs. 3.7%; adjusted RR = 2.11, Cl = 0.82, 5.45). The results of this study suggest a better performance, in terms of post-crash fire prevention, of CRFS-equipped civil helicopters as compared with those without CRFS. It is possible that CRFS in civil helicopters have not achieved the same degree of effectiveness as CRFS in military helicopters. CRFS should be used more widely in civil helicopters. The more stringent CRFS requirements for military helicopters should not be reduced without further research.
Comparing Driver Frontal Mortality in Vehicles with Redesigned and Older-Design Front Airbags
Braver, Elisa R.; Kyrychenko, Sergey Y.; Ferguson, Susan A.
2004-01-01
In 1997, the National Highway Traffic Safety Administration amended its requirements for frontal crash performance under Federal Motor Vehicle Safety Standard 208 to temporarily allow 30 mph (48 kph) sled tests with unbelted dummies as an alternative to 30 mph head-on rigid-barrier vehicle tests. This change permitted automakers to reduce airbag inflation forces so that they would be less likely to injure occupants who are close to airbags when they first deploy. Most vehicle models were sled-certified starting in model year 1998. Airbag-related deaths have decreased since 1997; however, controversy persists about whether reduced inflation forces might be decreasing protection for some occupants in high-severity frontal crashes. To examine the effects of the regulatory changes, this study computed rate ratios (RR) and 95 percent confidence intervals (95% CI) for passenger vehicle driver deaths per vehicle registration during 2000–02 at principal impact points of 12 o’clock for 1998–99 model year vehicles relative to 1997 models. Passenger vehicles included in the study had both driver and passenger front airbags, had the same essential designs during the 1997–99 model years, and had been sled-certified for drivers throughout model years 1998 and 1999. An adjustment was made for the higher annual mileage of newer vehicles. Findings were that the effect of the regulatory change varied by vehicle type. For cars, sport utility vehicles, and minivans combined, there was an 11 percent decrease in fatality risk in frontal crashes after changing to sled certification (RR=0.89; 95% CI=0.82–0.96). Among pickups, however, estimated frontal fatality risk increased 35 percent (RR=1.35; 95% CI=1.12–1.62). For a broad range of frontal crashes (11, 12, and 1 o’clock combined), the results indicated a modest net benefit of the regulatory change across all vehicle types and driver characteristics. However, the contrary finding for pickups needs to be researched further. PMID:15319114
Comparing driver frontal mortality in vehicles with redesigned and older-design front airbags.
Braver, Elisa R; Kyrychenko, Sergey Y; Ferguson, Susan A
2004-01-01
In 1997, the National Highway Traffic Safety Administration amended its requirements for frontal crash performance under Federal Motor Vehicle Safety Standard 208 to temporarily allow 30 mph (48 kph) sled tests with unbelted dummies as an alternative to 30 mph head-on rigid-barrier vehicle tests. This change permitted automakers to reduce airbag inflation forces so that they would be less likely to injure occupants who are close to airbags when they first deploy. Most vehicle models were sled-certified starting in model year 1998. Airbag-related deaths have decreased since 1997; however, controversy persists about whether reduced inflation forces might be decreasing protection for some occupants in high-severity frontal crashes. To examine the effects of the regulatory changes, this study computed rate ratios (RR) and 95 percent confidence intervals (95% CI) for passenger vehicle driver deaths per vehicle registration during 2000-02 at principal impact points of 12 o'clock for 1998-99 model year vehicles relative to 1997 models. Passenger vehicles included in the study had both driver and passenger front airbags, had the same essential designs during the 1997-99 model years, and had been sled-certified for drivers throughout model years 1998 and 1999. An adjustment was made for the higher annual mileage of newer vehicles. Findings were that the effect of the regulatory change varied by vehicle type. For cars, sport utility vehicles, and minivans combined, there was an 11 percent decrease in fatality risk in frontal crashes after changing to sled certification (RR=0.89; 95% CI=0.82-0.96). Among pickups, however, estimated frontal fatality risk increased 35 percent (RR=1.35; 95% CI=1.12-1.62). For a broad range of frontal crashes (11, 12, and 1 o'clock combined), the results indicated a modest net benefit of the regulatory change across all vehicle types and driver characteristics. However, the contrary finding for pickups needs to be researched further.
Regression discontinuity was a valid design for dichotomous outcomes in three randomized trials.
van Leeuwen, Nikki; Lingsma, Hester F; Mooijaart, Simon P; Nieboer, Daan; Trompet, Stella; Steyerberg, Ewout W
2018-06-01
Regression discontinuity (RD) is a quasi-experimental design that may provide valid estimates of treatment effects in case of continuous outcomes. We aimed to evaluate validity and precision in the RD design for dichotomous outcomes. We performed validation studies in three large randomized controlled trials (RCTs) (Corticosteroid Randomization After Significant Head injury [CRASH], the Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries [GUSTO], and PROspective Study of Pravastatin in elderly individuals at risk of vascular disease [PROSPER]). To mimic the RD design, we selected patients above and below a cutoff (e.g., age 75 years) randomized to treatment and control, respectively. Adjusted logistic regression models using restricted cubic splines (RCS) and polynomials and local logistic regression models estimated the odds ratio (OR) for treatment, with 95% confidence intervals (CIs) to indicate precision. In CRASH, treatment increased mortality with OR 1.22 [95% CI 1.06-1.40] in the RCT. The RD estimates were 1.42 (0.94-2.16) and 1.13 (0.90-1.40) with RCS adjustment and local regression, respectively. In GUSTO, treatment reduced mortality (OR 0.83 [0.72-0.95]), with more extreme estimates in the RD analysis (OR 0.57 [0.35; 0.92] and 0.67 [0.51; 0.86]). In PROSPER, similar RCT and RD estimates were found, again with less precision in RD designs. We conclude that the RD design provides similar but substantially less precise treatment effect estimates compared with an RCT, with local regression being the preferred method of analysis. Copyright © 2018 Elsevier Inc. All rights reserved.
The effect of decreases in vehicle weight on injury crash rates
DOT National Transportation Integrated Search
1997-01-01
This study presents the results of an analysis to estimate the effect of a one hundred (1 00) pound reduction in the : average weight of passenger vehicles on the crash rates of driver incapacitating injury. The analysis was conducted : as a part of ...
Relative risk of fatal crash involvement by BAC, age, and gender
DOT National Transportation Integrated Search
2000-04-01
The objective of this study was to re-examine and refine estimates for alcohol-related relative risk of driver involvement in fatal crashes by age and gender as a function of blood alcohol concentration (BAC) using recent data. The method of study wa...
Pedestrian fatality and impact speed squared: Cloglog modeling from French national data.
Martin, Jean-Louis; Wu, Dan
2018-01-02
The present study estimates pedestrians' risk of death according to impact speed when hit by a passenger car in a frontal collision. Data were coded for all fatal crashes in France in 2011 and for a random sample of 1/20th of all road injuries for the same year and weighted to take into account police underreporting of mild injury. A cloglog model was used to optimize risk adjustment for high collision speeds. The fit of the model on the data was also improved by using the square of the impact speed, which best matches the energy dissipated in the collision. Modeling clearly demonstrated that the risk of death was very close to 1 when impact speeds exceeded 80 km/h. For speeds less than 40 km/h, because data representative of all crashes resulting in injury were used, the estimated risk of death was fairly low. However, although the curve seemed deceptively flat below 50 km/h, the risk of death in fact rose 2-fold between 30 and 40 km/h and 6-fold between 30 and 50 km/h. For any given speed, the risk of death was much higher for more elderly subjects, especially those over 75 years of age. These results concern frontal crashes involving a passenger car. Collisions involving trucks are far less frequent, but half result in the pedestrian being run over, incurring greater mortality. For impact speeds below 60 km/h, the shape of the curve relating probability of death to impact speed was very similar to those reported in recent rigorous studies. For higher impact speeds, the present model allows the curve to rise ever more steeply, giving a much better fit to observed data. The present results confirm that, when a pedestrian is struck by a car, impact speed is a major risk factor, thus providing a supplementary argument for strict speed limits in areas where pedestrians are highly exposed.
Cost and benefit estimates of partially-automated vehicle collision avoidance technologies.
Harper, Corey D; Hendrickson, Chris T; Samaras, Constantine
2016-10-01
Many light-duty vehicle crashes occur due to human error and distracted driving. Partially-automated crash avoidance features offer the potential to reduce the frequency and severity of vehicle crashes that occur due to distracted driving and/or human error by assisting in maintaining control of the vehicle or issuing alerts if a potentially dangerous situation is detected. This paper evaluates the benefits and costs of fleet-wide deployment of blind spot monitoring, lane departure warning, and forward collision warning crash avoidance systems within the US light-duty vehicle fleet. The three crash avoidance technologies could collectively prevent or reduce the severity of as many as 1.3 million U.S. crashes a year including 133,000 injury crashes and 10,100 fatal crashes. For this paper we made two estimates of potential benefits in the United States: (1) the upper bound fleet-wide technology diffusion benefits by assuming all relevant crashes are avoided and (2) the lower bound fleet-wide benefits of the three technologies based on observed insurance data. The latter represents a lower bound as technology is improved over time and cost reduced with scale economies and technology improvement. All three technologies could collectively provide a lower bound annual benefit of about $18 billion if equipped on all light-duty vehicles. With 2015 pricing of safety options, the total annual costs to equip all light-duty vehicles with the three technologies would be about $13 billion, resulting in an annual net benefit of about $4 billion or a $20 per vehicle net benefit. By assuming all relevant crashes are avoided, the total upper bound annual net benefit from all three technologies combined is about $202 billion or an $861 per vehicle net benefit, at current technology costs. The technologies we are exploring in this paper represent an early form of vehicle automation and a positive net benefit suggests the fleet-wide adoption of these technologies would be beneficial from an economic and social perspective. Copyright © 2016 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wenzel, Tom P.
The Department of Energy’s (DOE) Vehicle Technologies Office funds research on development of technologies to improve the fuel economy of both light- and heavy-duty vehicles, including advanced combustion systems, improved batteries and electric drive systems, and new lightweight materials. Of these approaches to increase fuel economy and reduce fuel consumption, reducing vehicle mass through more extensive use of strong lightweight materials is perhaps the easiest and least expensive method; however, there is a concern that reducing vehicle mass may lead to more fatalities. Lawrence Berkeley National Laboratory (LBNL) has conducted several analyses to better understand the relationship between vehicle mass,more » size and safety, in order to ameliorate concerns that down-weighting vehicles will inherently lead to more fatalities. These analyses include recreating the regression analyses conducted by the National Highway Traffic Safety Administration (NHTSA) that estimate the relationship between mass reduction and U.S. societal fatality risk per vehicle mile of travel (VMT), while holding vehicle size (i.e. footprint, wheelbase times track width) constant; these analyses are referred to as LBNL Phase 1 analysis. In addition, LBNL has conducted additional analysis of the relationship between mass and the two components of risk per VMT, crash frequency (crashes per VMT) and risk once a crash has occurred (risk per crash); these analyses are referred to as LBNL Phase 2 analysis.« less
Helicopter crashes into water: warning time, final position, and other factors affecting survival.
Brooks, Christopher J; MacDonald, Conor V; Baker, Susan P; Shanahan, Dennis F; Haaland, Wren L
2014-04-01
According to 40 yr of data, the fatality rate for a helicopter crash into water is approximately 25%. Does warning time and the final position of the helicopter in the water influence the survival rate? The National Transportation Safety Board (NTSB) database was queried to identify helicopter crashes into water between 1981 and 2011 in the Gulf of Mexico and Hawaii. Fatality rate, amount of warning time prior to the crash, and final position of the helicopter were identified. There were 133 helicopters that crashed into water with 456 crew and passengers. Of these, 119 occupants (26%) did not survive; of those who did survive, 38% were injured. Twelve died after making a successful escape from the helicopter. Crashes with < 15 s warning had a fatality rate of 22%, compared to 12% for 16-60 s warning and 5% for > 1 min. However, more than half of fatalities (57%) came from crashes for which the warning time could not be determined. Lack of warning time and how to survive in the water after the crash should be a topic for study in all marine survival/aircraft ditching courses. Investigators should be trained to provide estimates of warning time when investigating helicopter crashes into water.
NASA Astrophysics Data System (ADS)
Sornette, D.
2003-04-01
This review presents a general theory of financial crashes and of stock market instabilities that his co-workers and the author have developed over the past seven years. We start by discussing the limitation of standard analyses for characterizing how crashes are special. The study of the frequency distribution of drawdowns, or runs of successive losses shows that large financial crashes are “outliers”: they form a class of their own as can be seen from their statistical signatures. If large financial crashes are “outliers”, they are special and thus require a special explanation, a specific model, a theory of their own. In addition, their special properties may perhaps be used for their prediction. The main mechanisms leading to positive feedbacks, i.e., self-reinforcement, such as imitative behavior and herding between investors are reviewed with many references provided to the relevant literature outside the narrow confine of Physics. Positive feedbacks provide the fuel for the development of speculative bubbles, preparing the instability for a major crash. We demonstrate several detailed mathematical models of speculative bubbles and crashes. A first model posits that the crash hazard drives the market price. The crash hazard may sky-rocket at some times due to the collective behavior of “noise traders”, those who act on little information, even if they think they “know”. A second version inverses the logic and posits that prices drive the crash hazard. Prices may skyrocket at some times again due to the speculative or imitative behavior of investors. According the rational expectation model, this entails automatically a corresponding increase of the probability for a crash. We also review two other models including the competition between imitation and contrarian behavior and between value investors and technical analysts. The most important message is the discovery of robust and universal signatures of the approach to crashes. These precursory patterns have been documented for essentially all crashes on developed as well as emergent stock markets, on currency markets, on company stocks, and so on. We review this discovery at length and demonstrate how to use this insight and the detailed predictions obtained from these models to forecast crashes. For this, we review the major crashes of the past that occurred on the major stock markets of the planet and describe the empirical evidence of the universal nature of the critical log-periodic precursory signature of crashes. The concept of an “anti-bubble” is also summarized, with the Japanese collapse from the beginning of 1991 to present, taken as a prominent example. A prediction issued and advertised in January 1999 has been until recently born out with remarkable precision, predicting correctly several changes of trends, a feat notoriously difficult using standard techniques of economic forecasting. We also summarize a very recent analysis the behavior of the U.S. S&P500 index from 1996 to August 2002 and the forecast for the two following years. We conclude by presenting our view of the organization of financial markets.
Sagberg, Fridulv
2018-08-01
Drivers or riders without a valid license are involved in 10% of fatal road crashes in Norway. This was shown by an analysis of data from all fatal crashes in the period 2005-2014. A literature review shows that unlicensed drivers have a considerably increased crash risk. Such crashes could be prevented by electronic driver authentication, i.e., a technical system for checking that a driver or rider has legal access to a vehicle before driving is permitted. This can be done by requiring the driver/rider to identify themselves with a national identity number and a unique code or biometric information before driving may commence. The vehicle thereafter verifies license availability and vehicle access by communication with a central register. In more than 80% of fatal crashes with unlicensed drivers/riders, speeding and/or drug influence contributed to the crash. This means that a majority of crashes with unlicensed drivers alternatively could be prevented by already available systems, such as alcolock and speed limit dependent speed adapters. These systems will have a wider influence, by preventing crashes also among licensed drivers. Mandatory implementation of alcolock, speed limiter, and electronic driver authentication in all motorized vehicles is estimated to prevent up to 28% of fatal road crashes, depending on effectiveness of the systems. Copyright © 2018 Elsevier Ltd. All rights reserved.
Driver air bag effectiveness by severity of the crash.
Segui-Gomez, M
2000-01-01
OBJECTIVES: This analysis provided effectiveness estimates of the driver-side air bag while controlling for severity of the crash and other potential confounders. METHODS: Data were from the National Automotive Sampling System (1993-1996). Injury severity was described on the basis of the Abbreviated Injury Scale, Injury Severity Score, Functional Capacity Index, and survival. Ordinal, linear, and logistic multivariate regression methods were used. RESULTS: Air bag deployment in frontal or near-frontal crashes decreases the probability of having severe and fatal injuries (e.g., Abbreviated Injury Scale score of 4-6), including those causing a long-lasting high degree of functional limitation. However, air bag deployment in low-severity crashes increases the probability that a driver (particularly a woman) will sustain injuries of Abbreviated Injury Scale level 1 to 3. Air bag deployment exerts a net injurious effect in low-severity crashes and a net protective effect in high-severity crashes. The level of crash severity at which air bags are protective is higher for female than for male drivers. CONCLUSIONS: Air bag improvement should minimize the injuries induced by their deployment. One possibility is to raise their deployment level so that they deploy only in more severe crashes. PMID:11029991
Hotspot Identification for Shanghai Expressways Using the Quantitative Risk Assessment Method
Chen, Can; Li, Tienan; Sun, Jian; Chen, Feng
2016-01-01
Hotspot identification (HSID) is the first and key step of the expressway safety management process. This study presents a new HSID method using the quantitative risk assessment (QRA) technique. Crashes that are likely to happen for a specific site are treated as the risk. The aggregation of the crash occurrence probability for all exposure vehicles is estimated based on the empirical Bayesian method. As for the consequences of crashes, crashes may not only cause direct losses (e.g., occupant injuries and property damages) but also result in indirect losses. The indirect losses are expressed by the extra delays calculated using the deterministic queuing diagram method. The direct losses and indirect losses are uniformly monetized to be considered as the consequences of this risk. The potential costs of crashes, as a criterion to rank high-risk sites, can be explicitly expressed as the sum of the crash probability for all passing vehicles and the corresponding consequences of crashes. A case study on the urban expressways of Shanghai is presented. The results show that the new QRA method for HSID enables the identification of a set of high-risk sites that truly reveal the potential crash costs to society. PMID:28036009
Naznin, Farhana; Currie, Graham; Sarvi, Majid; Logan, David
2016-01-01
Streetcars/tram systems are growing worldwide, and many are given priority to increase speed and reliability performance in mixed traffic conditions. Research related to the road safety impact of tram priority is limited. This study explores the road safety impacts of tram priority measures including lane and intersection/signal priority measures. A before-after crash study was conducted using the empirical Bayes (EB) method to provide more accurate crash impact estimates by accounting for wider crash trends and regression to the mean effects. Before-after crash data for 29 intersections with tram signal priority and 23 arterials with tram lane priority in Melbourne, Australia, were analyzed to evaluate the road safety impact of tram priority. The EB before-after analysis results indicated a statistically significant adjusted crash reduction rate of 16.4% after implementation of tram priority measures. Signal priority measures were found to reduce crashes by 13.9% and lane priority by 19.4%. A disaggregate level simple before-after analysis indicated reductions in total and serious crashes as well as vehicle-, pedestrian-, and motorcycle-involved crashes. In addition, reductions in on-path crashes, pedestrian-involved crashes, and collisions among vehicles moving in the same and opposite directions and all other specific crash types were found after tram priority implementation. Results suggest that streetcar/tram priority measures result in safety benefits for all road users, including vehicles, pedestrians, and cyclists. Policy implications and areas for future research are discussed.
Wainiqolo, Iris; Kafoa, Berlin; Kool, Bridget; Robinson, Elizabeth; Herman, Josephine; McCaig, Eddie; Ameratunga, Shanthi
2016-01-01
Objective To investigate the association between kava use and the risk of four-wheeled motor vehicle crashes in Fiji. Kava is a traditional beverage commonly consumed in many Pacific Island Countries. Herbal anxiolytics containing smaller doses of kava are more widely available. Methods Data for this population-based case-control study were collected from drivers of ‘case’ vehicles involved in serious injury-involved crashes (where at least one road user was killed or admitted to hospital for 12 hours or more) and ‘control’ vehicles representative of ‘driving time’ in the study base. Structured interviewer administered questionnaires collected self-reported participant data on demographic characteristics and a range of risk factors including kava use and potential confounders. Unconditional logistic regression models estimated odds ratios relating to the association between kava use and injury-involved crash risk. Findings Overall, 23% and 4% of drivers of case and control vehicles, respectively, reported consuming kava in the 12 hours prior to the crash or road survey. After controlling for assessed confounders, driving following kava use was associated with a four-fold increase in the odds of crash involvement (Odds ratio: 4.70; 95% CI: 1.90–11.63). The related population attributable risk was 18.37% (95% CI: 13.77–22.72). Acknowledging limited statistical power, we did not find a significant interaction in this association with concurrent alcohol use. Conclusion In this study conducted in a setting where recreational kava consumption is common, driving following the use of kava was associated with a significant excess of serious-injury involved road crashes. The precautionary principle would suggest road safety strategies should explicitly recommend avoiding driving following kava use, particularly in communities where recreational use is common. PMID:26930404
Wainiqolo, Iris; Kafoa, Berlin; Kool, Bridget; Robinson, Elizabeth; Herman, Josephine; McCaig, Eddie; Ameratunga, Shanthi
2016-01-01
To investigate the association between kava use and the risk of four-wheeled motor vehicle crashes in Fiji. Kava is a traditional beverage commonly consumed in many Pacific Island Countries. Herbal anxiolytics containing smaller doses of kava are more widely available. Data for this population-based case-control study were collected from drivers of 'case' vehicles involved in serious injury-involved crashes (where at least one road user was killed or admitted to hospital for 12 hours or more) and 'control' vehicles representative of 'driving time' in the study base. Structured interviewer administered questionnaires collected self-reported participant data on demographic characteristics and a range of risk factors including kava use and potential confounders. Unconditional logistic regression models estimated odds ratios relating to the association between kava use and injury-involved crash risk. Overall, 23% and 4% of drivers of case and control vehicles, respectively, reported consuming kava in the 12 hours prior to the crash or road survey. After controlling for assessed confounders, driving following kava use was associated with a four-fold increase in the odds of crash involvement (Odds ratio: 4.70; 95% CI: 1.90-11.63). The related population attributable risk was 18.37% (95% CI: 13.77-22.72). Acknowledging limited statistical power, we did not find a significant interaction in this association with concurrent alcohol use. In this study conducted in a setting where recreational kava consumption is common, driving following the use of kava was associated with a significant excess of serious-injury involved road crashes. The precautionary principle would suggest road safety strategies should explicitly recommend avoiding driving following kava use, particularly in communities where recreational use is common.
Risk of injury to restrained children from passenger air bags.
Durbin, Dennis R; Kallan, Michael; Elliott, Michael; Cornejo, Rebecca A; Arbogast, Kristy B; Winston, Flaura K
2003-03-01
The objectives of this study were to estimate the prevalence of children's exposure to passenger air bag (PAB) deployments and to determine the relative risk of both minor and more serious nonfatal injuries to restrained children exposed to PABs in frontal impact collisions. Data were collected from 1 December 1998 to 30 November 2001 from a large-scale, child-specific crash surveillance system based on insurance claims, a telephone survey, and on-site crash investigations. Vehicles qualifying for inclusion were State Farm-insured, model year 1990 or newer, and involved in a crash with at least one child occupant < or =15 years of age. Qualifying crashes were limited to those that occurred in 15 states and the District of Columbia. A stratified cluster sample was designed in order to select vehicles (the unit of sampling) for the conduction of a telephone survey with the driver. For cases in which child occupants were seriously injured or killed, in-depth crash investigations were performed. The prevalence of exposure to PABs was calculated as the number of children occupying the right front seat in a PAB deployment crash among all children occupying the right front seat in vehicles equipped with PABs. Complete interview data were obtained on 9,779 vehicles involving 15,341 children. Among PAB-exposed children, 175 (14%) suffered serious injuries versus 41 (7.5%) of those in the comparison group (OR 2.0; 95% CI, 1.1-3.7). The overall risk of any injury (both minor and serious) was 86% among children exposed to PABs, compared to 55% among the comparison group (OR 5.3; 95% CI, 2.1-13.4). Exposure to PABs increased the risk of both minor injuries, including facial and chest abrasions, and more serious injuries, particularly upper extremity fractures.
Influence of pedestrian age and gender on spatial and temporal distribution of pedestrian crashes.
Toran Pour, Alireza; Moridpour, Sara; Tay, Richard; Rajabifard, Abbas
2018-01-02
Every year, about 1.24 million people are killed in traffic crashes worldwide and more than 22% of these deaths are pedestrians. Therefore, pedestrian safety has become a significant traffic safety issue worldwide. In order to develop effective and targeted safety programs, the location- and time-specific influences on vehicle-pedestrian crashes must be assessed. The main purpose of this research is to explore the influence of pedestrian age and gender on the temporal and spatial distribution of vehicle-pedestrian crashes to identify the hotspots and hot times. Data for all vehicle-pedestrian crashes on public roadways in the Melbourne metropolitan area from 2004 to 2013 are used in this research. Spatial autocorrelation is applied in examining the vehicle-pedestrian crashes in geographic information systems (GIS) to identify any dependency between time and location of these crashes. Spider plots and kernel density estimation (KDE) are then used to determine the temporal and spatial patterns of vehicle-pedestrian crashes for different age groups and genders. Temporal analysis shows that pedestrian age has a significant influence on the temporal distribution of vehicle-pedestrian crashes. Furthermore, men and women have different crash patterns. In addition, results of the spatial analysis shows that areas with high risk of vehicle-pedestrian crashes can vary during different times of the day for different age groups and genders. For example, for those between ages 18 and 65, most vehicle-pedestrian crashes occur in the central business district (CBD) during the day, but between 7:00 p.m. and 6:00 a.m., crashes among this age group occur mostly around hotels, clubs, and bars. This research reveals that temporal and spatial distributions of vehicle-pedestrian crashes vary for different pedestrian age groups and genders. Therefore, specific safety measures should be in place during high crash times at different locations for different age groups and genders to increase the effectiveness of the countermeasures in preventing and reducing vehicle-pedestrian crashes.
Optimization of vehicle deceleration to reduce occupant injury risks in frontal impact.
Mizuno, Koji; Itakura, Takuya; Hirabayashi, Satoko; Tanaka, Eiichi; Ito, Daisuke
2014-01-01
In vehicle frontal impacts, vehicle acceleration has a large effect on occupant loadings and injury risks. In this research, an optimal vehicle crash pulse was determined systematically to reduce injury measures of rear seat occupants by using mathematical simulations. The vehicle crash pulse was optimized based on a vehicle deceleration-deformation diagram under the conditions that the initial velocity and the maximum vehicle deformation were constant. Initially, a spring-mass model was used to understand the fundamental parameters for optimization. In order to investigate the optimization under a more realistic situation, the vehicle crash pulse was also optimized using a multibody model of a Hybrid III dummy seated in the rear seat for the objective functions of chest acceleration and chest deflection. A sled test using a Hybrid III dummy was carried out to confirm the simulation results. Finally, the optimal crash pulses determined from the multibody simulation were applied to a human finite element (FE) model. The optimized crash pulse to minimize the occupant deceleration had a concave shape: a high deceleration in the initial phase, low in the middle phase, and high again in the final phase. This crash pulse shape depended on the occupant restraint stiffness. The optimized crash pulse determined from the multibody simulation was comparable to that from the spring-mass model. From the sled test, it was demonstrated that the optimized crash pulse was effective for the reduction of chest acceleration. The crash pulse was also optimized for the objective function of chest deflection. The optimized crash pulse in the final phase was lower than that obtained for the minimization of chest acceleration. In the FE analysis of the human FE model, the optimized pulse for the objective function of the Hybrid III chest deflection was effective in reducing rib fracture risks. The optimized crash pulse has a concave shape and is dependent on the occupant restraint stiffness and maximum vehicle deformation. The shapes of the optimized crash pulse in the final phase were different for the objective functions of chest acceleration and chest deflection due to the inertial forces of the head and upper extremities. From the human FE model analysis it was found that the optimized crash pulse for the Hybrid III chest deflection can substantially reduce the risk of rib cage fractures. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.
Application of the Hyper-Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes.
Khazraee, S Hadi; Sáez-Castillo, Antonio Jose; Geedipally, Srinivas Reddy; Lord, Dominique
2015-05-01
The hyper-Poisson distribution can handle both over- and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation-specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper-Poisson distribution in analyzing motor vehicle crash count data. The hyper-Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway-highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness-of-fit measures indicated that the hyper-Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper-Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway-Maxwell-Poisson model previously developed for the same data set. The advantages of the hyper-Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper-Poisson model can handle both over- and underdispersed crash data. Although not a major issue for the Conway-Maxwell-Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model. © 2014 Society for Risk Analysis.
McDonald, Catherine C; Curry, Allison E; Kandadai, Venk; Sommers, Marilyn S; Winston, Flaura K
2014-11-01
Motor vehicle crashes are the leading cause of death and acquired disability during the first four decades of life. While teen drivers have the highest crash risk, few studies examine the similarities and differences in teen and adult driver crashes. We aimed to: (1) identify and compare the most frequent crash scenarios-integrated information on a vehicle's movement prior to crash, immediate pre-crash event, and crash configuration-for teen and adult drivers involved in serious crashes, and (2) for the most frequent scenarios, explore whether the distribution of driver critical errors differed for teens and adult drivers. We analyzed data from the National Motor Vehicle Crash Causation Survey, a nationally representative study of serious crashes conducted by the U.S. National Highway Traffic Safety Administration from 2005 to 2007. Our sample included 642 16- to 19-year-old and 1167 35- to 54-year-old crash-involved drivers (weighted n=296,482 and 439,356, respectively) who made a critical error that led to their crash's critical pre-crash event (i.e., event that made the crash inevitable). We estimated prevalence ratios (PR) and 95% confidence intervals (CI) to compare the relative frequency of crash scenarios and driver critical errors. The top five crash scenarios among teen drivers, accounting for 37.3% of their crashes, included: (1) going straight, other vehicle stopped, rear end; (2) stopped in traffic lane, turning left at intersection, turn into path of other vehicle; (3) negotiating curve, off right edge of road, right roadside departure; (4) going straight, off right edge of road, right roadside departure; and (5) stopped in lane, turning left at intersection, turn across path of other vehicle. The top five crash scenarios among adult drivers, accounting for 33.9% of their crashes, included the same scenarios as the teen drivers with the exception of scenario (3) and the addition of going straight, crossing over an intersection, and continuing on a straight path. For two scenarios ((1) and (3) above), teens were more likely than adults to make a critical decision error (e.g., traveling too fast for conditions). Our findings indicate that among those who make a driver critical error in a serious crash, there are few differences in the scenarios or critical driver errors for teen and adult drivers. Copyright © 2014 Elsevier Ltd. All rights reserved.
Social costs of road crashes: An international analysis.
Wijnen, Wim; Stipdonk, Henk
2016-09-01
This paper provides an international overview of the most recent estimates of the social costs of road crashes: total costs, value per casualty and breakdown in cost components. The analysis is based on publications about the national costs of road crashes of 17 countries, of which ten high income countries (HICs) and seven low and middle income countries (LMICs). Costs are expressed as a proportion of the gross domestic product (GDP). Differences between countries are described and explained. These are partly a consequence of differences in the road safety level, but there are also methodological explanations. Countries may or may not correct for underreporting of road crashes, they may or may not use the internationally recommended willingness to pay (WTP)-method for estimating human costs, and there are methodological differences regarding the calculation of some other cost components. The analysis shows that the social costs of road crashes in HICs range from 0.5% to 6.0% of the GDP with an average of 2.7%. Excluding countries that do not use a WTP- method for estimating human costs and countries that do not correct for underreporting, results in average costs of 3.3% of GDP. For LMICs that do correct for underreporting the share in GDP ranges from 1.1% to 2.9%. However, none of the LMICs included has performed a WTP study of the human costs. A major part of the costs is related to injuries: an average share of 50% for both HICs and LMICs. The average share of fatalities in the costs is 23% and 30% respectively. Prevention of injuries is thus important to bring down the socio-economic burden of road crashes. The paper shows that there are methodological differences between countries regarding cost components that are taken into account and regarding the methods used to estimate specific cost components. In order to be able to make sound comparisons of the costs of road crashes across countries, (further) harmonization of cost studies is recommended. This can be achieved by updating and improving international guidelines and applying them in future cost studies. The information regarding some cost components, particularly human costs and property damage, is poor and more research into these cost components is recommended. Copyright © 2016 Elsevier Ltd. All rights reserved.
DOT National Transportation Integrated Search
2015-07-01
This study developed methods for estimating the expected crash frequency of urban freeway segments : with HOV or HOT lanes. The safety impacts of the type of separation between the managed lanes and : general purpose lanes were examined. Separate mod...
DOT National Transportation Integrated Search
2008-05-06
The present study used commercial motor vehicle (CMV) crash data from NCDOTs Traffic Engineering Accident : Analysis System (TEAAS) to infer the presence and relative extent of STAA dimensioned vehicles operating : beyond the 3-mile buffer of the ...
Studying the effect of weather conditions on daily crash counts using a discrete time-series model.
Brijs, Tom; Karlis, Dimitris; Wets, Geert
2008-05-01
In previous research, significant effects of weather conditions on car crashes have been found. However, most studies use monthly or yearly data and only few studies are available analyzing the impact of weather conditions on daily car crash counts. Furthermore, the studies that are available on a daily level do not explicitly model the data in a time-series context, hereby ignoring the temporal serial correlation that may be present in the data. In this paper, we introduce an integer autoregressive model for modelling count data with time interdependencies. The model is applied to daily car crash data, metereological data and traffic exposure data from the Netherlands aiming at examining the risk impact of weather conditions on the observed counts. The results show that several assumptions related to the effect of weather conditions on crash counts are found to be significant in the data and that if serial temporal correlation is not accounted for in the model, this may produce biased results.
Assessing the Impact of Twenty Underage Drinking Laws.
Fell, James C; Scherer, Michael; Thomas, Sue; Voas, Robert B
2016-03-01
Over the last two decades, many states have adopted several of the 20 laws that aim to control youth access to and possession of alcohol and prevent underage drinking in the United States. However, many of these laws have not been evaluated since their adoption. The objective of this study was to determine which minimum legal drinking age 21 (MLDA-21) laws currently have an effect on underage drinking-and-driving fatal crashes. We updated the effective dates of the 20 MLDA-21 laws examined in this study and used scores of each law's strengths and weaknesses. Our structural equation model included the 20 MLDA-21 laws, impaired driving laws, seat belt safety laws, economic strength, driving exposure, beer consumption, and fatal crash ratios of drinking-to-nondrinking drivers under age 21. Nine MLDA-21 laws were associated with significant decreases in fatal crash ratios of underage drinking drivers: possession of alcohol (-7.7%), purchase of alcohol (-4.2%), use alcohol and lose your license (-7.9%), zero tolerance .02 blood alcohol concentration limit for underage drivers (-2.9%), age of bartender ≥21 (-4.1%), state responsible beverage service program (-3.8%), fake identification support provisions for retailers (-11.9%), dram shop liability (-2.5%), and social host civil liability (-1.7%). Two laws were associated with significant increases in the fatal crash ratios of underage drinking drivers: prohibition of furnishing alcohol to minors (+7.2%) and registration of beer kegs (+9.6%). The nine effective MLDA-21 laws are estimated to be currently saving approximately 1,135 lives annually, yet only five states have enacted all nine laws. If all states adopted these nine effective MLDA-21 laws, it is estimated that an additional 210 lives could be saved every year.
The exposure of children to deploying side air bags: an initial field assessment.
Arbogast, Kristy B; Kallan, Michael J
2007-01-01
Tremendous effort has been invested in the laboratory to ensure side air bag (SAB) deployments minimize injury metrics in pediatric anthropometric test devices (ATDs). Little is known, however, about the experience of children exposed to this technology in real world crashes. Therefore, the objective of this study was to determine the prevalence of SAB exposure in children and provide estimates of injury risk among those exposed. This study utilized data from the Partners for Child Passenger Safety study, a large-scale child-focused crash surveillance system, to identify a probability sample of 348 child occupants, age 0-15 years, weighted to represent 6,600 children, in vehicles of model year 1998 and newer, equipped with SABs, in side impact crashes from three large U.S. regions between 1/1/05 and 12/31/06. In the study sample, 27 children per 1000 children in crashes were exposed to a deployed side air bag. Over 75% of these children were seated in the rear seat and 83% were exposed to a head curtain SAB. 65% of those exposed were less than 9 years of age. Of those exposed, 10.6% sustained an AIS2+ injury; all injuries were of the AIS 2 level and limited to the head or upper extremity. This paper provides the first population-based estimates of the exposure of children to SABs. Initial experience suggests that the risk of injury is fairly low with only one in ten sustaining injury - none of which were serious or life threatening. These findings offer assurance that efforts by regulators and the automotive industry to minimize negative consequences from SABs to vulnerable occupants appear to be effective and cause no change in the current recommendation of safe seating for children next to SABs.
The Exposure of Children to Deploying Side Air Bags: An Initial Field Assessment
Arbogast, Kristy B.; Kallan, Michael J.
2007-01-01
Tremendous effort has been invested in the laboratory to ensure side air bag (SAB) deployments minimize injury metrics in pediatric anthropometric test devices (ATDs). Little is known, however, about the experience of children exposed to this technology in real world crashes. Therefore, the objective of this study was to determine the prevalence of SAB exposure in children and provide estimates of injury risk among those exposed. This study utilized data from the Partners for Child Passenger Safety study, a large-scale child-focused crash surveillance system, to identify a probability sample of 348 child occupants, age 0–15 years, weighted to represent 6,600 children, in vehicles of model year 1998 and newer, equipped with SABs, in side impact crashes from three large U.S. regions between 1/1/05 and 12/31/06. In the study sample, 27 children per 1000 children in crashes were exposed to a deployed side airbag. Over 75% of these children were seated in the rear seat and 83% were exposed to a head curtain SAB. 65% of those exposed were less than 9 years of age. Of those exposed, 10.6% sustained an AIS2+ injury; all injuries were of the AIS 2 level and limited to the head or upper extremity. This paper provides the first population-based estimates of the exposure of children to SABs. Initial experience suggests that the risk of injury is fairly low with only one in ten sustaining injury – none of which were serious or life threatening. These findings offer assurance that efforts by regulators and the automotive industry to minimize negative consequences from SABs to vulnerable occupants appear to be effective and cause no change in the current recommendation of safe seating for children next to SABs. PMID:18184496
Assessing the Impact of Twenty Underage Drinking Laws
Fell, James C.; Scherer, Michael; Thomas, Sue; Voas, Robert B.
2016-01-01
Objective: Over the last two decades, many states have adopted several of the 20 laws that aim to control youth access to and possession of alcohol and prevent underage drinking in the United States. However, many of these laws have not been evaluated since their adoption. The objective of this study was to determine which minimum legal drinking age 21 (MLDA-21) laws currently have an effect on underage drinking-and-driving fatal crashes. Method: We updated the effective dates of the 20 MLDA-21 laws examined in this study and used scores of each law’s strengths and weaknesses. Our structural equation model included the 20 MLDA-21 laws, impaired driving laws, seat belt safety laws, economic strength, driving exposure, beer consumption, and fatal crash ratios of drinking-to-nondrinking drivers under age 21. Results: Nine MLDA-21 laws were associated with significant decreases in fatal crash ratios of underage drinking drivers: possession of alcohol (-7.7%), purchase of alcohol (-4.2%), use alcohol and lose your license (-7.9%), zero tolerance .02 blood alcohol concentration limit for under-age drivers (-2.9%), age of bartender ≥21 (-4.1%), state responsible beverage service program (-3.8%), fake identification support provisions for retailers (-11.9%), dram shop liability (-2.5%), and social host civil liability (-1.7%). Two laws were associated with significant increases in the fatal crash ratios of underage drinking drivers: prohibition of furnishing alcohol to minors (+7.2%) and registration of beer kegs (+9.6%). Conclusions: The nine effective MLDA-21 laws are estimated to be currently saving approximately 1,135 lives annually, yet only five states have enacted all nine laws. If all states adopted these nine effective MLDA-21 laws, it is estimated that an additional 210 lives could be saved every year. PMID:26997183
Sternlund, Simon
2017-05-29
Lane departure crashes account for a significant proportion of passenger car occupant fatalities and serious injuries. Utilizing real-world data involving fatal passenger car crashes in Sweden, the characteristics of lane departure crashes were identified and the safety potential of lane departure warning (LDW) systems was quantified. The material consisted of 104 in-depth studies of fatal passenger car crashes in 2010. The crashes were classified as single-vehicle (n = 48), head-on (n = 52), and overtaking (n = 4) crashes. These crash types were identified as crashes that could have potentially involved lane departure. A case-by-case analysis was carried out and lane departure crashes were identified and characterized using police reports and information collected by crash investigators at the Swedish Transport Administration; for example, inspections and photographs of the crash sites and of the involved vehicles. Lane departure crashes were separated from crashes where loss of control occurred pre-lane departure. Furthermore, loss of control post-lane departures were identified. When studying the pre-stage of lane departure without prior loss of control, crashes were categorized as unintentional drifting, intentional lane change, or evasive maneuver. Using previously published effectiveness information, the potential for LDW systems to prevent crashes was estimated. Of all crashes with passenger car occupant fatalities in Sweden in 2010, 46% (63/138) were found to relate to lane departure without prior loss of control. These crashes accounted for 61% (63/104) of all single-vehicle, head-on, and overtaking crashes. The remaining 41 crashes were due to loss of control pre-lane departure. Unintentional drifting accounted for 81% (51/63) of all lane departure crashes without prior loss of control, which corresponded to 37% (51/138) of all fatal passenger car occupant crashes. LDW systems were found to potentially prevent 33-38 of the 100 fatal head-on and single vehicle crashes. These crashes involved drifting and occurred on roads with visible lane markings, signed posted speed limits ≥70 km/h, and without rumble strips on the corresponding lane departure side. The range of potentially prevented crashes (33-38) is due to the inclusion or exclusion of crashes involving excessive speeding. In this study, approximately half (51/100) of all head-on and single-vehicle crashes were identified as being a consequence of drifting, where LDW systems had the potential to prevent the majority (33-38) of these crashes. The typical lane departure crash without prior loss of control occurred on undivided roads in rural areas with signed posted speed limits ≥70 km/h, where the center and side road markings were visible.
Washington, Simon; Haque, Md Mazharul; Oh, Jutaek; Lee, Dongmin
2014-05-01
Hot spot identification (HSID) aims to identify potential sites-roadway segments, intersections, crosswalks, interchanges, ramps, etc.-with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset. Copyright © 2014 Elsevier Ltd. All rights reserved.
Gasoline prices and their relationship to drunk-driving crashes.
Chi, Guangqing; Zhou, Xuan; McClure, Timothy E; Gilbert, Paul A; Cosby, Arthur G; Zhang, Li; Robertson, Angela A; Levinson, David
2011-01-01
This study investigates the relationship between changing gasoline prices and drunk-driving crashes. Specifically, we examine the effects of gasoline prices on drunk-driving crashes in Mississippi by several crash types and demographic groups at the monthly level from 2004 to 2008, a period experiencing great fluctuation in gasoline prices. An exploratory visualization by graphs shows that higher gasoline prices are generally associated with fewer drunk-driving crashes. Higher gasoline prices depress drunk-driving crashes among young and adult drivers, among male and female drivers, and among white and black drivers. Results from negative binomial regression models show that when gas prices are higher, there are fewer drunk-driving crashes, particularly among property-damage-only crashes. When alcohol consumption levels are higher, there are more drunk-driving crashes, particularly fatal and injury crashes. The effects of gasoline prices and alcohol consumption are stronger on drunk-driving crashes than on all crashes. The findings do not vary much across different demographic groups. Overall, gasoline prices have greater effects on less severe crashes and alcohol consumption has greater effects on more severe crashes. Copyright © 2010 Elsevier Ltd. All rights reserved.
Avoidable Burden of Risk Factors for Serious Road Traffic Crashes in Iran: A Modeling Study.
Khosravi Shadmani, Fatemeh; Mansori, Kamyar; Karami, Manoochehr; Zayeri, Farid; Shadman, Reza Khosravi; Hanis, Shiva Mansouri; Soori, Hamid
2017-03-01
The aim of this study was to model the avoidable burden of the risk factors of road traffic crashes in Iran and to prioritize interventions to reduce that burden. The prevalence and the effect size of the risk factors were obtained from data documented by the traffic police of Iran in 2013. The effect size was estimated using an ordinal regression model. The potential impact fraction index was applied to calculate the avoidable burden in order to prioritize interventions. This index was calculated for theoretical, plausible, and feasible minimum risk level scenarios. The joint effects of the risk factors were then estimated for all the scenarios. The highest avoidable burdens in the theoretical, plausible, and feasible minimum risk level scenarios for the non-use of child restraints on urban roads were 52.25, 28.63, and 46.67, respectively. In contrast, the value of this index for speeding was 76.24, 37.00, and 62.23, respectively, for rural roads. On the basis of the different scenarios considered in this research, we suggest focusing on future interventions to decrease the prevalence of speeding, the non-use of child restraints, the use of cell phones while driving, and helmet disuse, and the laws related to these items should be considered seriously.
Data-driven train set crash dynamics simulation
NASA Astrophysics Data System (ADS)
Tang, Zhao; Zhu, Yunrui; Nie, Yinyu; Guo, Shihui; Liu, Fengjia; Chang, Jian; Zhang, Jianjun
2017-02-01
Traditional finite element (FE) methods are arguably expensive in computation/simulation of the train crash. High computational cost limits their direct applications in investigating dynamic behaviours of an entire train set for crashworthiness design and structural optimisation. On the contrary, multi-body modelling is widely used because of its low computational cost with the trade-off in accuracy. In this study, a data-driven train crash modelling method is proposed to improve the performance of a multi-body dynamics simulation of train set crash without increasing the computational burden. This is achieved by the parallel random forest algorithm, which is a machine learning approach that extracts useful patterns of force-displacement curves and predicts a force-displacement relation in a given collision condition from a collection of offline FE simulation data on various collision conditions, namely different crash velocities in our analysis. Using the FE simulation results as a benchmark, we compared our method with traditional multi-body modelling methods and the result shows that our data-driven method improves the accuracy over traditional multi-body models in train crash simulation and runs at the same level of efficiency.
Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie
2016-03-01
In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.
Jafari Anarkooli, A; Hadji Hosseinlou, M
2016-02-01
Many studies have examined different factors contributing to the injury severity of crashes; however, relatively few studies have focused on the crashes by considering the specific effects of lighting conditions. This research investigates lighting condition differences in the injury severity of crashes using 3-year (2009-2011) crash data of two-lane rural roads of the state of Washington. Separate ordered-probit models were developed to predict the effects of a set of factors expected to influence injury severity in three lighting conditions; daylight, dark, and dark with street lights. A series of likelihood ratio tests were conducted to determine if these lighting condition models were justified. The modeling results suggest that injury severity in specific lighting conditions are associated with contributing factors in different ways, and that such differences cannot be uncovered by focusing merely on one aggregate model. Key differences include crash location, speed limit, shoulder width, driver action, and three collision types (head-on, rear-end, and right-side impact collisions). This paper highlights the importance of deploying street lights at and near intersections (or access points) on two-lane rural roads because injury severity highly increases when crashes occur at these points in dark conditions. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.
NASA Astrophysics Data System (ADS)
Bae, Gihyun; Huh, Hoon; Park, Sungho
This paper deals with a regression model for light weight and crashworthiness enhancement design of automotive parts in frontal car crash. The ULSAB-AVC model is employed for the crash analysis and effective parts are selected based on the amount of energy absorption during the crash behavior. Finite element analyses are carried out for designated design cases in order to investigate the crashworthiness and weight according to the material and thickness of main energy absorption parts. Based on simulations results, a regression analysis is performed to construct a regression model utilized for light weight and crashworthiness enhancement design of automotive parts. An example for weight reduction of main energy absorption parts demonstrates the validity of a regression model constructed.
A model to identify high crash road segments with the dynamic segmentation method.
Boroujerdian, Amin Mirza; Saffarzadeh, Mahmoud; Yousefi, Hassan; Ghassemian, Hassan
2014-12-01
Currently, high social and economic costs in addition to physical and mental consequences put road safety among most important issues. This paper aims at presenting a novel approach, capable of identifying the location as well as the length of high crash road segments. It focuses on the location of accidents occurred along the road and their effective regions. In other words, due to applicability and budget limitations in improving safety of road segments, it is not possible to recognize all high crash road segments. Therefore, it is of utmost importance to identify high crash road segments and their real length to be able to prioritize the safety improvement in roads. In this paper, after evaluating deficiencies of the current road segmentation models, different kinds of errors caused by these methods are addressed. One of the main deficiencies of these models is that they can not identify the length of high crash road segments. In this paper, identifying the length of high crash road segments (corresponding to the arrangement of accidents along the road) is achieved by converting accident data to the road response signal of through traffic with a dynamic model based on the wavelet theory. The significant advantage of the presented method is multi-scale segmentation. In other words, this model identifies high crash road segments with different lengths and also it can recognize small segments within long segments. Applying the presented model into a real case for identifying 10-20 percent of high crash road segment showed an improvement of 25-38 percent in relative to the existing methods. Copyright © 2014 Elsevier Ltd. All rights reserved.
The interactive effect on injury severity of driver-vehicle units in two-vehicle crashes.
Zeng, Qiang; Wen, Huiying; Huang, Helai
2016-12-01
This study sets out to investigate the interactive effect on injury severity of driver-vehicle units in two-vehicle crashes. A Bayesian hierarchical ordered logit model is proposed to relate the variation and correlation of injury severity of drivers involved in two-vehicle crashes to the factors of both driver-vehicle units and the crash configurations. A total of 6417 crash records with 12,834 vehicles involved in Florida are used for model calibration. The results show that older, female and not-at-fault drivers and those without use of safety equipment are more likely to be injured but less likely to injure the drivers in the other vehicles. New vehicles and lower speed ratios are associated with lower injury degree of both drivers involved. Compared with automobiles, vans, pick-ups, light trucks, median trucks, and heavy trucks possess better self-protection and stronger aggressivity. The points of impact closer to the driver's seat in general indicate a higher risk to the own drivers while engine cover and vehicle rear are the least hazardous to other drivers. Head-on crashes are significantly more severe than angle and rear-end crashes. We found that more severe crashes occurred on roadways than on shoulders or safety zones. Based on these results, some suggestions for traffic safety education, enforcement and engineering are made. Moreover, significant within-crash correlation is found in the crash data, which demonstrates the applicability of the proposed model. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.
Ahmed, Mohamed M; Franke, Rebecca; Ksaibati, Khaled; Shinstine, Debbie S
2018-08-01
Roadway safety is an integral part of a functioning infrastructure. A major use of the highway system is the transport of goods. The United States has experienced constant growth in the amount of freight transported by truck in the last few years. Wyoming is experiencing a large increase in truck traffic on its local and county roads due to an increase in oil and gas production. This study explores the involvement of heavy trucks in crashes and their significance as a predictor of crash severity and addresses the effect that large truck traffic is having on the safety of roadways for various road classifications. Studies have been done on the factors involved in and the causation of heavy truck crashes, but none address the causation and effect of roadway classifications on truck crashes. Binary Logit Models (BLM) with Bayesian inferences were utilized to classify heavy truck involvement in severe and non-severe crashes using ten years (2002-2011) of historical crash data in the State of Wyoming. From the final main effects model, various interactions proved to be significant in predicting the severity of crashes and varied depending on the roadway classification. The results indicated the odds of a severe crash increase to 2.3 and 4.5 times when a heavy truck is involved on state and interstate highways respectively. The severity of crashes is significantly increased when road conditions were not clear, icy, and during snowy weather conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.
Best Practices for Crash Modeling and Simulation
NASA Technical Reports Server (NTRS)
Fasanella, Edwin L.; Jackson, Karen E.
2002-01-01
Aviation safety can be greatly enhanced by the expeditious use of computer simulations of crash impact. Unlike automotive impact testing, which is now routine, experimental crash tests of even small aircraft are expensive and complex due to the high cost of the aircraft and the myriad of crash impact conditions that must be considered. Ultimately, the goal is to utilize full-scale crash simulations of aircraft for design evaluation and certification. The objective of this publication is to describe "best practices" for modeling aircraft impact using explicit nonlinear dynamic finite element codes such as LS-DYNA, DYNA3D, and MSC.Dytran. Although "best practices" is somewhat relative, it is hoped that the authors' experience will help others to avoid some of the common pitfalls in modeling that are not documented in one single publication. In addition, a discussion of experimental data analysis, digital filtering, and test-analysis correlation is provided. Finally, some examples of aircraft crash simulations are described in several appendices following the main report.
Curry, Allison E; Metzger, Kristina B; Williams, Allan F; Tefft, Brian C
2017-11-01
Few previous studies have directly compared crash rates of older and younger novice drivers. To inform discussion about whether Graduated Driver Licensing (GDL) policies that are applied in the US for younger novice drivers should be applied to older novice drivers, we conducted a longitudinal study to examine overall, nighttime, and multiple passenger crash rates over the initial four years of licensure differ for novice drivers licensed at different ages. Using data from the New Jersey Traffic Safety Outcomes (NJ-TSO) data warehouse, we selected all NJ drivers who obtained their initial intermediate driver's license from 2006 through 2014 and had at least one month of follow-up from the date of licensure to study end or death (n=1,034,835). Novice drivers were grouped based on age at licensure: age 17; 18-20; 21-24; and 25 or older. We estimated monthly rates for overall crashes (per 10,000 licensed drivers) as well as: late night crashes (11:01 p.m.-4:59 a.m.); early night crashes (9:00 p.m.-11:00 p.m.); and multiple passenger crashes (two or more passengers). Average monthly rates were calculated for specific relevant time periods and Poisson regression models were used to compare rates: (1) between novice driver groups with the same time since licensure; (2) over the first 48 months of licensure within each novice driver group; and (3) between same-aged 21-year-old drivers with varying lengths of licensure. Although initial (three months post-licensure) overall crash rates of novice NJ drivers age 21 and older were higher than rates of same-aged experienced drivers, they were substantially lower than initial rates for 17- to 20-year-old novice drivers, who are licensed under GDL policies. Moreover, older novice drivers experience much less steep crash reductions over the first year of licensure than younger novice drivers. Nighttime crash rates among the 21- to 24-year old and aged 25 and older novice driver groups were stable over the first year of licensure. For novice drivers under age 21, early night crash rates declined rapidly over the course of licensure, while changes in late night crashes were much smaller. First-year multiple passenger crash rates were highest for drivers licensed at age 18-20, and novice driver groups experienced varying amounts of reduction in multiple passenger crashes over time. Study findings support NJ's current GDL policies for 17- to 20-year-old novice drivers and the potential for added benefits from beginning the nighttime restriction at 9:00 p.m. Conversely, there was a lack of compelling evidence for additional policies for drivers licensed at age 21-24 and no evidence to indicate a need for additional GDL policies for NJ novices aged 25 years and older. Copyright © 2017 Elsevier Ltd. All rights reserved.
Seacrist, Thomas; Belwadi, Aditya; Prabahar, Abhiti; Chamberlain, Samuel; Megariotis, James; Loeb, Helen
2016-09-01
Motor vehicle crashes are the leading cause of death for teens. Previous teen and adult crash rates have been based upon fatal crashes, police-reported crashes, and estimated miles driven. Large-scale naturalistic driving studies offer the opportunity to compute crash rates using a reliable methodology to capture crashes and driving exposure. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study contains extensive real-world data on teen and adult driving. This article presents findings on the crash rates of novice teen and experienced adult drivers in naturalistic crashes. A subset from the SHRP2 database consisting of 539 crash events for novice teens (16-19 years, n = 549) and experienced adults (35-54 years, n = 591) was used. Onboard instrumentation such as scene cameras, accelerometers, and Global Positioning System logged time series data at 10 Hz. Scene videos were reviewed for all events to identify rear-end striking crashes. Dynamic variables such as acceleration and velocity were analyzed for rear-end striking events. Number of crashes, crash rates, rear-end striking crash severity, and rear-end striking impact velocity were compared between novice teens and experienced adults. Video review of the SHRP2 crashes identified significantly more crashes (P < 0.01) and rear-end striking crashes (P < 0.01) among the teen group than among the adult group. This yielded crash rates of 30.0 crashes per million miles driven for novice teens compared to 5.3 crashes per million miles driven for experienced adults. The crash rate ratio for teens vs. adults was 5.7. The rear-end striking crash rate was 13.5 and 1.8 per million miles driven for novice teens and experienced adults, respectively. The rear-end striking crash rate ratio for teens vs. adults was 7.5. The rear-end striking crash severity measured by the accelerometers was greater (P < 0.05) for the teen group (1.8 ± 0.9 g; median = 1.6 g) than for the adult group (1.1 ± 0.4 g; median = 1.0 g), suggesting that teen crashes tend to be more serious than adult crashes. Increased rear-end striking impact velocity (P < 0.01) was also observed for novice teens (18.8 ± 13.2 mph; median = 18.9 mph) compared to experienced adults (3.3 ± 1.2 mph; median = 2.8 mph). To our knowledge, this is the first study to compare crash rates between teens and adults using a large-scale naturalistic driving database. Unlike previous crash rates, the reported rates reliably control for crash type and driving exposure. These results conform to previous findings that novice teens exhibit increased crash rates compared to experienced adults.
Area-wide traffic calming for preventing traffic related injuries.
Bunn, F; Collier, T; Frost, C; Ker, K; Roberts, I; Wentz, R
2003-01-01
It is estimated that by 2020 road traffic crashes will have moved from ninth to third in the world disease burden ranking, as measured in disability adjusted life years, and second in developing countries. The identification of effective strategies for the prevention of traffic related injuries is of global health importance. Area-wide traffic calming schemes that discourage through traffic on residential roads is one such strategy. To evaluate the effectiveness of area-wide traffic calming in preventing traffic related crashes, injuries, and deaths. We searched the following electronic databases: Cochrane Injuries Group's Specialised Register, Cochrane Controlled Trials Register, MEDLINE, EMBASE and TRANSPORT (NTIS, TRIS, TRANSDOC). We searched the web sites of road safety organisations, handsearched conference proceedings, checked reference lists of relevant papers and contacted experts in the area. The search was not restricted by language or publication status. Randomised controlled trials, and controlled before-after studies of area-wide traffic calming schemes. Two reviewers independently extracted data on type of study, characteristics of intervention and control areas, and length of data collection periods. Before and after data were collected on the total number of road traffic crashes, all road user deaths and injuries, pedestrian-motor vehicle collisions and road user deaths. The statistical package STATA was used to calculate rate ratios for each study, which were then pooled to give an overall estimate using a random effects model. We found no randomised controlled trials, but 16 controlled before-after trials met our inclusion criteria. Seven studies were done in Germany, six in the UK, two in Australia and one in the Netherlands. There were no studies in low or middle income countries. Eight trials reported the number of road traffic crashes resulting in deaths. The pooled rate ratio was 0.63 (0.14, 2.59 95% CI). Sixteen studies reported the number of road traffic crashes resulting in injuries (fatal and non fatal). The pooled rate ratio was 0.89 (0.80, 1.00 95% CI). Nine studies reported the total number of road traffic crashes. The pooled rate ratio was 0.95 (0.81, 1.11 95% CI). Thirteen trials reported the number of pedestrian-motor vehicle collisions. The pooled rate ratio was 1.00 (0.84, 1.18). There was significant heterogeneity for the total number of crashes and deaths and injuries. The results from this review suggest that area-wide traffic calming in towns and cities may be a promising intervention for reducing the number of road traffic injuries, and deaths. However, further rigorous evaluations of this intervention are needed.
Ivers, Rebecca; Senserrick, Teresa; Boufous, Soufiane; Stevenson, Mark; Chen, Huei-Yang; Woodward, Mark; Norton, Robyn
2009-09-01
We explored the risky driving behaviors and risk perceptions of a cohort of young novice drivers and sought to determine their associations with crash risk. Provisional drivers aged 17 to 24 (n = 20 822) completed a detailed questionnaire that included measures of risk perception and behaviors; 2 years following recruitment, survey data were linked to licensing and police-reported crash data. Poisson regression models that adjusted for multiple confounders were created to explore crash risk. High scores on questionnaire items for risky driving were associated with a 50% increased crash risk (adjusted relative risk = 1.51; 95% confidence interval = 1.25, 1.81). High scores for risk perception (poorer perceptions of safety) were also associated with increased crash risk in univariate and multivariate models; however, significance was not sustained after adjustment for risky driving. The overrepresentation of youths in crashes involving casualties is a significant public health issue. Risky driving behavior is strongly linked to crash risk among young drivers and overrides the importance of risk perceptions. Systemwide intervention, including licensing reform, is warranted.
Ebel, B E; Mack, C; Diehr, P; Rivara, F P
2004-10-01
In 2001, 6.3 million passengers were involved in motor vehicle crashes. This study aimed to determine the number of work days lost as a result of motor vehicle crashes and factors that influenced people's return to work. This was a retrospective, population based cohort study of occupants in motor vehicles involved in crashes from the 1993-2001 Crashworthiness Data System produced by the National Highway Traffic Safety Administration. The sample population of people aged 18-65 years included two groups: occupants who survived and were working before the crash and occupants who were injured fatally and were estimated to have been working before the crash. Multivariate linear regression was used to analyze the impact of restraint use and injury type on return to work. Overall, 30.1% of occupants of vehicles that crashed missed one or more days of work. A crash resulted in a mean 28.0 (95% confidence interval 15.8 to 40.1) days lost from work, including losses associated with fatalities. The 2.1 million working occupants of vehicles that crashed in 2001 lost a total of 60 million days of work, resulting in annual productivity losses of over $7.5 billion (2964 to 12 075). Unrestrained vehicle occupants accounted for $5.6 billion in lost productivity. Motor vehicle crashes result in large and potentially preventable productive losses that are mostly attributable to fatal injuries.
Analyzing crash frequency in freeway tunnels: A correlated random parameters approach.
Hou, Qinzhong; Tarko, Andrew P; Meng, Xianghai
2018-02-01
The majority of past road safety studies focused on open road segments while only a few focused on tunnels. Moreover, the past tunnel studies produced some inconsistent results about the safety effects of the traffic patterns, the tunnel design, and the pavement conditions. The effects of these conditions therefore remain unknown, especially for freeway tunnels in China. The study presented in this paper investigated the safety effects of these various factors utilizing a four-year period (2009-2012) of data as well as three models: 1) a random effects negative binomial model (RENB), 2) an uncorrelated random parameters negative binomial model (URPNB), and 3) a correlated random parameters negative binomial model (CRPNB). Of these three, the results showed that the CRPNB model provided better goodness-of-fit and offered more insights into the factors that contribute to tunnel safety. The CRPNB was not only able to allocate the part of the otherwise unobserved heterogeneity to the individual model parameters but also was able to estimate the cross-correlations between these parameters. Furthermore, the study results showed that traffic volume, tunnel length, proportion of heavy trucks, curvature, and pavement rutting were associated with higher frequencies of traffic crashes, while the distance to the tunnel wall, distance to the adjacent tunnel, distress ratio, International Roughness Index (IRI), and friction coefficient were associated with lower crash frequencies. In addition, the effects of the heterogeneity of the proportion of heavy trucks, the curvature, the rutting depth, and the friction coefficient were identified and their inter-correlations were analyzed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Association Between NCAP Ratings and Real-World Rear Seat Occupant Risk of Injury.
Metzger, Kristina B; Gruschow, Siobhan; Durbin, Dennis R; Curry, Allison E
2015-01-01
Several studies have evaluated the correlation between U.S. or Euro New Car Assessment Program (NCAP) ratings and injury risk to front seat occupants, in particular driver injuries. Conversely, little is known about whether NCAP 5-star ratings predict real-world risk of injury to restrained rear seat occupants. The NHTSA has identified rear seat occupant protection as a specific area under consideration for improvements to its NCAP. In order to inform NHTSA's efforts, we examined how NCAP's current 5-star rating system predicts risk of moderate or greater injury among restrained rear seat occupants in real-world crashes. We identified crash-involved vehicles, model year 2004-2013, in NASS-CDS (2003-2012) with known make and model and nonmissing occupant information. We manually matched these vehicles to their NCAP star ratings using data on make, model, model year, body type, and other identifying information. The resultant linked NASS-CDS and NCAP database was analyzed to examine associations between vehicle ratings and rear seat occupant injury risk; risk to front seat occupants was also estimated for comparison. Data were limited to restrained occupants and occupant injuries were defined as any injury with a maximum Abbreviated Injury Scale (AIS) score of 2 or greater. We linked 95% of vehicles in NASS-CDS to a specific vehicle in NCAP. The 18,218 vehicles represented an estimated 6 million vehicles with over 9 million occupants. Rear seat passengers accounted for 12.4% of restrained occupants. The risk of injury in all crashes for restrained rear seat occupants was lower in vehicles with a 5-star driver rating in frontal impact tests (1.4%) than with 4 or fewer stars (2.6%, P =.015); results were similar for the frontal impact passenger rating (1.3% vs. 2.4%, P =.024). Conversely, side impact driver and passenger crash tests were not associated with rear seat occupant injury risk (driver test: 1.7% for 5-star vs. 1.8% for 1-4 stars; passenger test: 1.6% for 5 stars vs 1.8% for 1-4 stars). Current frontal impact test procedures provide some degree of discrimination in real-world rear seat injury risk among vehicles with 5 compared to fewer than 5 stars. However, there is no evidence that vehicles with a 5-star side impact passenger rating, which is the only crash test procedure to include an anthropomorphic test dummy (ATD) in the rear, demonstrate lower risks of injury in the rear than vehicles with fewer than 5 stars. These results support prioritizing modifications to the NCAP program that specifically evaluate rear seat injury risk to restrained occupants of all ages.
Road traffic accidents prediction modelling: An analysis of Anambra State, Nigeria.
Ihueze, Chukwutoo C; Onwurah, Uchendu O
2018-03-01
One of the major problems in the world today is the rate of road traffic crashes and deaths on our roads. Majority of these deaths occur in low-and-middle income countries including Nigeria. This study analyzed road traffic crashes in Anambra State, Nigeria with the intention of developing accurate predictive models for forecasting crash frequency in the State using autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average with explanatory variables (ARIMAX) modelling techniques. The result showed that ARIMAX model outperformed the ARIMA (1,1,1) model generated when their performances were compared using the lower Bayesian information criterion, mean absolute percentage error, root mean square error; and higher coefficient of determination (R-Squared) as accuracy measures. The findings of this study reveal that incorporating human, vehicle and environmental related factors in time series analysis of crash dataset produces a more robust predictive model than solely using aggregated crash count. This study contributes to the body of knowledge on road traffic safety and provides an approach to forecasting using many human, vehicle and environmental factors. The recommendations made in this study if applied will help in reducing the number of road traffic crashes in Nigeria. Copyright © 2017 Elsevier Ltd. All rights reserved.
Lord, Dominique; Guikema, Seth D; Geedipally, Srinivas Reddy
2008-05-01
This paper documents the application of the Conway-Maxwell-Poisson (COM-Poisson) generalized linear model (GLM) for modeling motor vehicle crashes. The COM-Poisson distribution, originally developed in 1962, has recently been re-introduced by statisticians for analyzing count data subjected to over- and under-dispersion. This innovative distribution is an extension of the Poisson distribution. The objectives of this study were to evaluate the application of the COM-Poisson GLM for analyzing motor vehicle crashes and compare the results with the traditional negative binomial (NB) model. The comparison analysis was carried out using the most common functional forms employed by transportation safety analysts, which link crashes to the entering flows at intersections or on segments. To accomplish the objectives of the study, several NB and COM-Poisson GLMs were developed and compared using two datasets. The first dataset contained crash data collected at signalized four-legged intersections in Toronto, Ont. The second dataset included data collected for rural four-lane divided and undivided highways in Texas. Several methods were used to assess the statistical fit and predictive performance of the models. The results of this study show that COM-Poisson GLMs perform as well as NB models in terms of GOF statistics and predictive performance. Given the fact the COM-Poisson distribution can also handle under-dispersed data (while the NB distribution cannot or has difficulties converging), which have sometimes been observed in crash databases, the COM-Poisson GLM offers a better alternative over the NB model for modeling motor vehicle crashes, especially given the important limitations recently documented in the safety literature about the latter type of model.
DOT National Transportation Integrated Search
1997-12-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
DOT National Transportation Integrated Search
2006-01-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
DOT National Transportation Integrated Search
2007-01-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
DOT National Transportation Integrated Search
2001-12-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
DOT National Transportation Integrated Search
2002-12-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
DOT National Transportation Integrated Search
1999-10-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
DOT National Transportation Integrated Search
2004-01-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
DOT National Transportation Integrated Search
2005-01-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
DOT National Transportation Integrated Search
2000-12-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
DOT National Transportation Integrated Search
1995-08-01
This annual report presents descriptive statistics about traffic crashes of all severities, from those that result in property damage to those that result in the loss of human life. Information from two of the National Highway Traffic Safety Administ...
Hoffenson, Steven; Frischknecht, Bart D; Papalambros, Panos Y
2013-01-01
Active safety features and adjustments to the New Car Assessment Program (NCAP) consumer-information crash tests have the potential to decrease the number of serious traffic injuries each year, according to previous studies. However, literature suggests that risk reductions, particularly in the automotive market, are often accompanied by adjusted consumer risk tolerance, and so these potential safety benefits may not be fully realized due to changes in consumer purchasing or driving behavior. This article approaches safety in the new vehicle market, particularly in the Sport Utility Vehicle and Crossover Utility Vehicle segments, from a market systems perspective. Crash statistics and simulations are used to predict the effects of design and policy changes on occupant crash safety, and discrete choice experiments are conducted to estimate the values consumers place on vehicle attributes. These models are combined in a market simulation that forecasts how consumers respond to the available vehicle alternatives, resulting in predictions of the market share of each vehicle and how the change in fleet mixture influences societal outcomes including injuries, fuel consumption, and firm profits. The model is tested for a scenario where active safety features are implemented across the new vehicle fleet and a scenario where the U.S. frontal NCAP test speed is modified. While results exhibit evidence of consumer risk adjustment, they support adding active safety features and lowering the NCAP frontal test speed, as these changes are predicted to improve the welfare of both firms and society. Copyright © 2012 Elsevier Ltd. All rights reserved.
System crash as dynamics of complex networks.
Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim
2016-10-18
Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.
Zheng, Lai; Ismail, Karim
2017-05-01
Traffic conflict indicators measure the temporal and spatial proximity of conflict-involved road users. These indicators can reflect the severity of traffic conflicts to a reliable extent. Instead of using the indicator value directly as a severity index, many link functions have been developed to map the conflict indicator to a severity index. However, little information is available about the choice of a particular link function. To guard against link misspecification or subjectivity, a generalized exponential link function was developed. The severity index generated by this link was introduced to a parametric safety continuum model which objectively models the centre and tail regions. An empirical method, together with full Bayesian estimation method was adopted to estimate model parameters. The safety implication of return level was calculated based on the model parameters. The proposed approach was applied to the conflict and crash data collected from 21 segments from three freeways located in Guangdong province, China. The Pearson's correlation test between return levels and observed crashes showed that a θ value of 1.2 was the best choice of the generalized parameter for current data set. This provides statistical support for using the generalized exponential link function. With the determined generalized exponential link function, the visualization of parametric safety continuum was found to be a gyroscope-shaped hierarchy. Copyright © 2017 Elsevier Ltd. All rights reserved.
DOT National Transportation Integrated Search
2009-04-28
Severe injury involvements on arterial roads account for a quarter of the total severe injuries reported statewide. Crash severity analysis was conducted and consisted of six road entity models and twenty crash type models. The data preparation and s...
The nature of the alcohol problem in U.S. fatal crashes.
Fell, J C; Nash, C E
1989-01-01
Alcohol is involved in more than half of all U.S. traffic fatalities. In 1987, an estimated 23,630 people were killed in alcohol-related crashes. Alcohol-related traffic fatalities continue to be the leading cause of death for young people. Alcohol is involved in almost 80% of the fatal crashes that occur between 8 p.m. and 4 a.m. on any night of the week. During the 1980s, alcohol involvement in fatal crashes declined. The proportion of drivers involved in fatal crashes who were intoxicated at the time of the crash decreased 17% from 1982 to 1987. The reduction was especially significant for teenaged drivers, females, surviving drivers, teenaged pedestrians, older drivers, and drivers in daytime crashes. On the other hand, there was little or no change for drivers aged 25-34, motorcycle drivers, pedestrians aged 20 to 64, and drivers in late-night crashes. Reasons for the reduction in alcohol appear to be: (1) increased public awareness of the problem during that time period; (2) tougher laws and better enforcement of existing laws by state and local governments; (3) the raising of the drinking age to 21 in most states; (4) other public and private programs to reduce drinking and driving, and (5) socioeconomic and demographic factors.
Issues and challenges for pedestrian active safety systems based on real world accidents.
Hamdane, Hédi; Serre, Thierry; Masson, Catherine; Anderson, Robert
2015-09-01
The purpose of this study was to analyze real crashes involving pedestrians in order to evaluate the potential effectiveness of autonomous emergency braking systems (AEB) in pedestrian protection. A sample of 100 real accident cases were reconstructed providing a comprehensive set of data describing the interaction between the vehicle, the environment and the pedestrian all along the scenario of the accident. A generic AEB system based on a camera sensor for pedestrian detection was modeled in order to identify the functionality of its different attributes in the timeline of each crash scenario. These attributes were assessed to determine their impact on pedestrian safety. The influence of the detection and the activation of the AEB system were explored by varying the field of view (FOV) of the sensor and the level of deceleration. A FOV of 35° was estimated to be required to detect and react to the majority of crash scenarios. For the reaction of a system (from hazard detection to triggering the brakes), between 0.5 and 1s appears necessary. Copyright © 2015 Elsevier Ltd. All rights reserved.
Child Passengers Injured in Motor Vehicle Crashes
Romano, Eduardo; Kelley-Baker, Tara
2015-01-01
Introduction—During 2010, 171,000 children aged 0-14 were injured in motor vehicle crashes. Despite the severity of the problem, research has been limited, and most of what we know about these children emanates from fatal crash databases. Method—Using information from the General Estimates System, this effort examines the occurrence of non-fatal crashes among children aged 0-14 over the last decade. Results—We found about 1% of the non-injured children in the file had been driven by a driver who was positive for alcohol. This percentage climbed to about 2% among children who had suffered injuries. Compared with the proportion of alcohol-positive drivers at the time of the crash, the proportion of drivers who sped or failed to obey a traffic signal were significantly higher. Practical Applications—The finding that drinking and driving with children did not decrease over time questions the adequacy of the extant child endangerment laws. PMID:25662876
Factors Related to Fatal Injury in Frontal Crashes Involving European Cars
Frampton, Richard; Page, Marianne; Thomas, Pete
2006-01-01
Despite considerable improvements in frontal impact crashworthiness, frontal crashes still account for a major number of front seat occupant fatalities in Great Britain. This study attempted to determine the remaining potential for further fatality reduction with passive safety improvements in frontal crashes. No evidence was found to support an increase in crash test speeds. Instead, assessment of scope for survival showed that at least 27% of all fatal drivers and 39% of all fatal front seat passengers have survival potential given attention to older occupant’s chest injury tolerance and passenger compartment intrusion under 60 km/h. Considering only fatal frontal crashes that might be assessed with a barrier test, showed an estimated survival potential of at least 49% of belted drivers and 60% of belted front seat passengers. The high proportion of unbelted fatalities suggested that targeting unbelted occupant protection could have additional benefit. PMID:16968628
Pirdavani, Ali; Brijs, Tom; Bellemans, Tom; Kochan, Bruno; Wets, Geert
2013-01-01
Travel demand management (TDM) consists of a variety of policy measures that affect the transportation system's effectiveness by changing travel behavior. The primary objective to implement such TDM strategies is not to improve traffic safety, although their impact on traffic safety should not be neglected. The main purpose of this study is to evaluate the traffic safety impact of conducting a fuel-cost increase scenario (i.e. increasing the fuel price by 20%) in Flanders, Belgium. Since TDM strategies are usually conducted at an aggregate level, crash prediction models (CPMs) should also be developed at a geographically aggregated level. Therefore zonal crash prediction models (ZCPMs) are considered to present the association between observed crashes in each zone and a set of predictor variables. To this end, an activity-based transportation model framework is applied to produce exposure metrics which will be used in prediction models. This allows us to conduct a more detailed and reliable assessment while TDM strategies are inherently modeled in the activity-based models unlike traditional models in which the impact of TDM strategies are assumed. The crash data used in this study consist of fatal and injury crashes observed between 2004 and 2007. The network and socio-demographic variables are also collected from other sources. In this study, different ZCPMs are developed to predict the number of injury crashes (NOCs) (disaggregated by different severity levels and crash types) for both the null and the fuel-cost increase scenario. The results show a considerable traffic safety benefit of conducting the fuel-cost increase scenario apart from its impact on the reduction of the total vehicle kilometers traveled (VKT). A 20% increase in fuel price is predicted to reduce the annual VKT by 5.02 billion (11.57% of the total annual VKT in Flanders), which causes the total NOCs to decline by 2.83%. Copyright © 2012 Elsevier Ltd. All rights reserved.
Research on simplified parametric finite element model of automobile frontal crash
NASA Astrophysics Data System (ADS)
Wu, Linan; Zhang, Xin; Yang, Changhai
2018-05-01
The modeling method and key technologies of the automobile frontal crash simplified parametric finite element model is studied in this paper. By establishing the auto body topological structure, extracting and parameterizing the stiffness properties of substructures, choosing appropriate material models for substructures, the simplified parametric FE model of M6 car is built. The comparison of the results indicates that the simplified parametric FE model can accurately calculate the automobile crash responses and the deformation of the key substructures, and the simulation time is reduced from 6 hours to 2 minutes.
Zhang, Wei; Gkritza, Konstantina; Keren, Nir; Nambisan, Shashi
2011-10-01
This paper investigates potential gender and age differences in conviction and crash occurrence subsequent to being directed to attend Iowa's Driver Improvement Program (DIP). Binary logit models were developed to investigate the factors that influence conviction occurrence after DIP by gender and age. Because of the low crash occurrence subsequent to DIP, association rules were applied to investigate the factors that influence crash occurrence subsequent to DIP, in lieu of econometric models. There were statistical significant differences by driver gender, age, and conviction history in the likelihood of subsequent convictions. However, this paper found no association between DIP outcome, crash history, and crash occurrence. Evaluating the differences in conviction and crash occurrence subsequent to DIP between female and male drivers, and among different age groups can lead to improvements of the effectiveness of DIPs and help to identify low-cost intervention measures, customized based on drivers' gender and age, for improving driving behaviors. Copyright © 2011 National Safety Council and Elsevier Ltd. All rights reserved.
Analysis of work zone rear-end crash risk for different vehicle-following patterns.
Weng, Jinxian; Meng, Qiang; Yan, Xuedong
2014-11-01
This study evaluates rear-end crash risk associated with work zone operations for four different vehicle-following patterns: car-car, car-truck, truck-car and truck-truck. The deceleration rate to avoid the crash (DRAC) is adopted to measure work zone rear-end crash risk. Results show that the car-truck following pattern has the largest rear-end crash risk, followed by truck-truck, truck-car and car-car patterns. This implies that it is more likely for a car which is following a truck to be involved in a rear-end crash accident. The statistical test results further confirm that rear-end crash risk is statistically different between any two of the four patterns. We therefore develop a rear-end crash risk model for each vehicle-following pattern in order to examine the relationship between rear-end crash risk and its influencing factors, including lane position, the heavy vehicle percentage, lane traffic flow and work intensity which can be characterized by the number of lane reductions, the number of workers and the amount of equipment at the work zone site. The model results show that, for each pattern, there will be a greater rear-end crash risk in the following situations: (i) heavy work intensity; (ii) the lane adjacent to work zone; (iii) a higher proportion of heavy vehicles and (iv) greater traffic flow. However, the effects of these factors on rear-end crash risk are found to vary according to the vehicle-following patterns. Compared with the car-car pattern, lane position has less effect on rear-end crash risk in the car-truck pattern. The effect of work intensity on rear-end crash risk is also reduced in the truck-car pattern. Copyright © 2014 Elsevier Ltd. All rights reserved.
Zhu, Motao; Cummings, Peter; Chu, Haitao; Coben, Jeffrey H; Li, Guohua
2013-02-01
Graduated Driver Licensing (GDL) has been implemented in Australia, Canada, New Zealand, USA and Israel. We conducted an exploratory summary of available data to estimate whether GDL effects varied with age. We searched MEDLINE and other sources from 1991-2011. GDL evaluation studies with crashes resulting in injuries or deaths were eligible. They had to provide age-specific incidence rate ratios with CI or information for calculating these quantities. We included studies from individual states or provinces, but excluded national studies. We examined rates based on person-years, not license-years. Of 1397 papers, 144 were screened by abstract and 47 were reviewed. Twelve studies from 11 US states and one Canadian province were selected for meta-analysis for age 16, eight were selected for age 17, and four for age 18. Adjusted rate ratios were pooled using random effects models. The pooled adjusted rate ratios for the association of GDL presence with crash rates was 0.78 (95% CI 0.72 to 0.84) for age 16 years, 0.94 (95% CI 0.93 to 0.96) for 17 and 1.00 (95% CI 0.95 to 1.04) for 18. The difference between these three rate ratios was statistically significant: p<0.001. GDL policies were associated with a 22% reduction in crash rates among 16-year-old drivers, but only a 6% reduction for 17-year-old drivers. GDL showed no association with crashes among 18-year-old drivers. Because we had few studies to summarise, particularly for older adolescents, our findings should be considered exploratory.
Yuan, Quan; Lu, Meng; Theofilatos, Athanasios; Li, Yi-Bing
2017-02-01
Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the critical factors for occupant injury severity in the specific rear-end crash type involving trucks as the front vehicle (FV). This paper investigated crashes occurred from 2011 to 2013 in Beijing area, China and selected 100 qualified cases i.e., rear-end crashes involving trucks as the FV. The crash data were supplemented with interviews from police officers and vehicle inspection. A binary logistic regression model was used to build the relationship between occupant injury severity and corresponding affecting factors. Moreover, a multinomial logistic model was used to predict the likelihood of fatal or severe injury or no injury in a rear-end crash. The results provided insights on the characteristics of driver, vehicle and environment, and the corresponding influences on the likelihood of a rear-end crash. The binary logistic model showed that drivers' age, weight difference between vehicles, visibility condition and lane number of road significantly increased the likelihood for severe injury of rear-end crash. The multinomial logistic model and the average direct pseudo-elasticity of variables showed that night time, weekdays, drivers from other provinces and passenger vehicles as rear vehicles significantly increased the likelihood of rear drivers being fatal. All the abovementioned significant factors should be improved, such as the conditions of lighting and the layout of lanes on roads. Two of the most common driver factors are drivers' age and drivers' original residence. Young drivers and outsiders have a higher injury severity. Therefore it is imperative to enhance the safety education and management on the young drivers who steer heavy duty truck from other cities to Beijing on weekdays. Copyright © 2016 Daping Hospital and the Research Institute of Surgery of the Third Military Medical University. Production and hosting by Elsevier B.V. All rights reserved.
Physical injury risks associated with drinking water arsenic treatment.
Frost, Floyd J; Chwirka, Joseph; Craun, Gunther F; Thomson, Bruce; Stomps, John
2002-04-01
We estimated the number of transportation deaths that would be associated with water treatment in Albuquerque to meet the EPA's recently proposed revisions of the Maximum Contaminant Level (MCL) for arsenic. Vehicle mileage was estimated for ion exchange, activated alumina, and iron coagulation/microfiltration water treatment processes to meet an MCL of 0.020 mg/L, 0.010 mg/L, 0.005 mg/L, and 0.003 mg/L. Local crash, injury, and death rates per million vehicle miles were used to estimate the number of injuries and deaths. Depending on the water treatment options chosen, we estimate that meeting an arsenic MCL of 0.005 mg/L will result in 143 to 237 crashes, 58 to 98 injuries, and 0.6 to 2.6 deaths in Albuquerque over a 70-year period, resulting in 26 to 113 years of life lost. The anticipated health benefits for Albuquerque residents from a 0.005 mg/L arsenic MCL, estimated using either a multistage Weibull or Poisson model, ranged from 3 to 80 arsenic-related bladder and lung cancer deaths prevented over a 70-year period, adding between 43 and 1,123 years of life. Whether a revised arsenic MCL increases or reduces overall loss of life in Albuquerque depends on the accuracy of EPA's cancer risk assessment. If the multistage Weibull model accurately estimates the benefits, the years of life added is comparable or lower than the anticipated years lost due to transportation associated with the delivery of chemicals, disposal of treatment waste, and operation of the water treatment system. Coagulation/microfiltration treatment will result in substantially fewer transportation deaths than either ion exchange or activated alumina.
Bakhtiyari, Mahmood; Mehmandar, Mohammad Reza; Mirbagheri, Babak; Hariri, Gholam Reza; Delpisheh, Ali; Soori, Hamid
2014-01-01
Risk factors of human-related traffic crashes are the most important and preventable challenges for community health due to their noteworthy burden in developing countries in particular. The present study aims to investigate the role of human risk factors of road traffic crashes in Iran. Through a cross-sectional study using the COM 114 data collection forms, the police records of almost 600,000 crashes occurred in 2010 are investigated. The binary logistic regression and proportional odds regression models are used. The odds ratio for each risk factor is calculated. These models are adjusted for known confounding factors including age, sex and driving time. The traffic crash reports of 537,688 men (90.8%) and 54,480 women (9.2%) are analysed. The mean age is 34.1 ± 14 years. Not maintaining eyes on the road (53.7%) and losing control of the vehicle (21.4%) are the main causes of drivers' deaths in traffic crashes within cities. Not maintaining eyes on the road is also the most frequent human risk factor for road traffic crashes out of cities. Sudden lane excursion (OR = 9.9, 95% CI: 8.2-11.9) and seat belt non-compliance (OR = 8.7, CI: 6.7-10.1), exceeding authorised speed (OR = 17.9, CI: 12.7-25.1) and exceeding safe speed (OR = 9.7, CI: 7.2-13.2) are the most significant human risk factors for traffic crashes in Iran. The high mortality rate of 39 people for every 100,000 population emphasises on the importance of traffic crashes in Iran. Considering the important role of human risk factors in traffic crashes, struggling efforts are required to control dangerous driving behaviours such as exceeding speed, illegal overtaking and not maintaining eyes on the road.
Head injuries (TBI) to adults and children in motor vehicle crashes.
Viano, David C; Parenteau, Chantal S; Xu, Likang; Faul, Mark
2017-08-18
This is a descriptive study. It determined the annual, national incidence of head injuries (traumatic brain injury, TBI) to adults and children in motor vehicle crashes. It evaluated NASS-CDS for exposure and incidence of various head injuries in towaway crashes. It evaluated 3 health databases for emergency department (ED) visits, hospitalizations, and deaths due to TBI in motor vehicle occupants. Four databases were evaluated using 1997-2010 data on adult (15+ years old) and child (0-14 years old) occupants in motor vehicle crashes: (1) NASS-CDS estimated the annual incidence of various head injuries and outcomes in towaway crashes, (2) National Hospital Ambulatory Medical Care Survey (NHAMCS)-estimated ED visits for TBI, (3) National Hospital Discharge Survey (NHDS) estimated hospitalizations for TBI, and (4) National Vital Statistics System (NVSS) estimated TBI deaths. The 4 databases provide annual national totals for TBI related injury and death in motor vehicle crashes based on differing definitions with TBI coded by the Abbreviated Injury Scale (AIS) in NASS-CDS and by International Classification of Diseases (ICD) in the health data. Adults: NASS-CDS had 16,980 ± 2,411 (risk = 0.43 ± 0.06%) with severe head injury (AIS 4+) out of 3,930,543 exposed adults in towaway crashes annually. There were 49,881 ± 9,729 (risk = 1.27 ± 0.25%) hospitalized with AIS 2+ head injury, without death. There were 6,753 ± 882 (risk = 0.17 ± 0.02%) fatalities with a head injury cause. The public health data had 89,331 ± 6,870 ED visits, 33,598 ± 1,052 hospitalizations, and 6,682 ± 22 deaths with TBI. NASS-CDS estimated 48% more hospitalized with AIS 2+ head injury without death than NHDS occupants hospitalized with TBI. NASS-CDS estimated 29% more deaths with AIS 3+ head injury than NVSS occupant TBI deaths but only 1% more deaths with a head injury cause. Children: NASS-CDS had 1,453 ± 318 (risk = 0.32 ± 0.07%) with severe head injury (AIS 4+) out of 454,973 exposed children annually. There were 2,581 ± 683 (risk = 0.57 ± 0.15%) hospitalized with AIS 2+ head injury, without death. There were 466 ± 132 (risk = 0.10 ± 0.03%) fatalities with a head injury cause. The public health data had 19,251 ± 2,803 ED visits, 3,363 ± 255 hospitalizations, and 488 ± 6 deaths with TBI. NASS-CDS estimated 24% fewer hospitalized children with AIS 2+ head injury without death than NHDS hospitalization with TBI. NASS-CDS estimated 31% more deaths with AIS 3+ head injury than NVSS child deaths but 5% fewer deaths with a head injury cause. The annual national incidence of motor vehicle-related head injury (TBI) was estimated using 1997-2010 NASS-CDS from the Department of Transportation and NHAMCS (ED visits), NHDS (hospitalizations), and NVSS (deaths) from the Department of Health and Human Services. The transportation and health databases use different definitions and coding, which complicates direct comparisons. Future work is needed where ICD to AIS translators are used if comparisons of serious head injuries in NASS and health data sets are to be made.
Keall, M D; Fildes, B; Newstead, S
2017-02-01
Backover injuries to pedestrians are a significant road safety issue, but their prevalence is underestimated as the majority of such injuries are often outside the scope of official road injury recording systems, which just focus on public roads. Based on experimental evidence, reversing cameras have been found to be effective in reducing the rate of collisions when reversing; the evidence for the effectiveness of reverse parking sensors has been mixed. The wide availability of these technologies in recent model vehicles provides impetus for real-world evaluations using crash data. A logistic model was fitted to data from crashes that occurred on public roads constituting 3172 pedestrian injuries in New Zealand and four Australian States to estimate the odds of backover injury (compared to other sorts of pedestrian injury crashes) for the different technology combinations fitted as standard equipment (both reversing cameras and sensors; just reversing cameras; just sensors; neither cameras nor sensors) controlling for vehicle type, jurisdiction, speed limit area and year of manufacture restricted to the range 2007-2013. Compared to vehicles without any of these technologies, reduced odds of backover injury were estimated for all three of these technology configurations: 0.59 (95% CI 0.39-0.88) for reversing cameras by themselves; 0.70 (95% CI 0.49-1.01) for both reversing cameras and sensors; 0.69 (95% CI 0.47-1.03) for reverse parking sensors by themselves. These findings are important as they are the first to our knowledge to present an assessment of real-world safety effectiveness of these technologies. Copyright © 2016 Elsevier Ltd. All rights reserved.
O'Connor, Stephen S; Shain, Lindsey M; Whitehill, Jennifer M; Ebel, Beth E
2017-02-01
Previous research suggests that anticipation of incoming phone calls or messages and impulsivity are significantly associated with motor vehicle crash. We took a more explanative approach to investigate a conceptual model regarding the direct and indirect effect of compulsive cell phone use and impulsive personality traits on crash risk. We recruited a sample of 307 undergraduate college students to complete an online survey that included measures of cell phone use, impulsivity, and history of motor vehicle crash. Using a structural equation model, we examined the direct and indirect relationships between factors of the Cell Phone Overuse Scale-II (CPOS-II), impulsivity, in-vehicle phone use, and severity and frequency of previous motor vehicle crash. Self-reported miles driven per week and year in college were included as covariates in the model. Our findings suggest that anticipation of incoming communication has a direct association with greater in-vehicle phone use, but was not directly or indirectly associated with increasing risk of previous motor vehicle crash. Of the three latent factors comprising the CPOS-II, only anticipation was significantly associated with elevated cell phone use while driving. Greater impulsivity and use of in-vehicle cell phone use while driving were directly and significantly associated with greater risk of motor vehicle crash. Anticipation of incoming cellular contacts (calls or texts) is associated with greater in-vehicle phone use, while greater in-vehicle cell phone use and impulsive traits are associated with elevated risk of motor vehicle crashes. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Sliseris, J.; Yan, L.; Kasal, B.
2017-09-01
Numerical methods for simulating hollow and foam-filled flax-fabric-reinforced epoxy tubular energy absorbers subjected to lateral crashing are presented. The crashing characteristics, such as the progressive failure, load-displacement response, absorbed energy, peak load, and failure modes, of the tubes were simulated and calculated numerically. A 3D nonlinear finite-element model that allows for the plasticity of materials using an isotropic hardening model with strain rate dependence and failure is proposed. An explicit finite-element solver is used to address the lateral crashing of the tubes considering large displacements and strains, plasticity, and damage. The experimental nonlinear crashing load vs. displacement data are successfully described by using the finite-element model proposed. The simulated peak loads and absorbed energy of the tubes are also in good agreement with experimental results.
Comparative analysis of zonal systems for macro-level crash modeling.
Cai, Qing; Abdel-Aty, Mohamed; Lee, Jaeyoung; Eluru, Naveen
2017-06-01
Macro-level traffic safety analysis has been undertaken at different spatial configurations. However, clear guidelines for the appropriate zonal system selection for safety analysis are unavailable. In this study, a comparative analysis was conducted to determine the optimal zonal system for macroscopic crash modeling considering census tracts (CTs), state-wide traffic analysis zones (STAZs), and a newly developed traffic-related zone system labeled traffic analysis districts (TADs). Poisson lognormal models for three crash types (i.e., total, severe, and non-motorized mode crashes) are developed based on the three zonal systems without and with consideration of spatial autocorrelation. The study proposes a method to compare the modeling performance of the three types of geographic units at different spatial configurations through a grid based framework. Specifically, the study region is partitioned to grids of various sizes and the model prediction accuracy of the various macro models is considered within these grids of various sizes. These model comparison results for all crash types indicated that the models based on TADs consistently offer a better performance compared to the others. Besides, the models considering spatial autocorrelation outperform the ones that do not consider it. Based on the modeling results and motivation for developing the different zonal systems, it is recommended using CTs for socio-demographic data collection, employing TAZs for transportation demand forecasting, and adopting TADs for transportation safety planning. The findings from this study can help practitioners select appropriate zonal systems for traffic crash modeling, which leads to develop more efficient policies to enhance transportation safety. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.
DOT National Transportation Integrated Search
2010-10-01
The Volvo-Ford-UMTRI project: Safety Impact Methodology (SIM) for Lane Departure Warning is part of the U.S. Department of Transportation's Advanced Crash Avoidance Technologies (ACAT) program. The project developed a basic analytical framework for e...
Impaired Driving among Youth: Trends & Tools for Prevention. Technical Report.
ERIC Educational Resources Information Center
Substance Abuse and Mental Health Services Administration (DHHS/PHS), Rockville, MD. Center for Substance Abuse Prevention.
In 1996, after years of decline, alcohol-related crashes involving youth between 15 and 20 years old increased by nearly 5%. The estimated medical, monetary, and lost quality-of-life costs associated with injuries in crashes of young drivers are staggering. Policymakers are being called upon to address the problem of underage drinking and…
Life-threatening motor vehicle crashes in bright sunlight
Redelmeier, Donald A.; Raza, Sheharyar
2017-01-01
Abstract Bright sunlight may create visual illusions that lead to driver error, including fallible distance judgment from aerial perspective. We tested whether the risk of a life-threatening motor vehicle crash was increased when driving in bright sunlight. This longitudinal, case-only, paired-comparison analysis evaluated patients hospitalized because of a motor vehicle crash between January 1, 1995 and December 31, 2014. The relative risk of a crash associated with bright sunlight was estimated by evaluating the prevailing weather at the time and place of the crash compared with the weather at the same hour and location on control days a week earlier and a week later. The majority of patients (n = 6962) were injured during daylight hours and bright sunlight was the most common weather condition at the time and place of the crash. The risk of a life-threatening crash was 16% higher during bright sunlight than normal weather (95% confidence interval: 9–24, P < 0.001). The increased risk was accentuated in the early afternoon, disappeared at night, extended to patients with different characteristics, involved crashes with diverse features, not apparent with cloudy weather, and contributed to about 5000 additional patient-days in hospital. The increased risk extended to patients with high crash severity as indicated by ambulance involvement, surgical procedures, length of hospital stay, intensive care unit admission, and patient mortality. The increased risk was not easily attributed to differences in alcohol consumption, driving distances, or anomalies of adverse weather. Bright sunlight is associated with an increased risk of a life-threatening motor vehicle crash. An awareness of this risk might inform driver education, trauma staffing, and safety warnings to prevent a life-threatening motor vehicle crash. Level of evidence: Epidemiologic Study, level III. PMID:28072708
Life-threatening motor vehicle crashes in bright sunlight.
Redelmeier, Donald A; Raza, Sheharyar
2017-01-01
Bright sunlight may create visual illusions that lead to driver error, including fallible distance judgment from aerial perspective. We tested whether the risk of a life-threatening motor vehicle crash was increased when driving in bright sunlight.This longitudinal, case-only, paired-comparison analysis evaluated patients hospitalized because of a motor vehicle crash between January 1, 1995 and December 31, 2014. The relative risk of a crash associated with bright sunlight was estimated by evaluating the prevailing weather at the time and place of the crash compared with the weather at the same hour and location on control days a week earlier and a week later.The majority of patients (n = 6962) were injured during daylight hours and bright sunlight was the most common weather condition at the time and place of the crash. The risk of a life-threatening crash was 16% higher during bright sunlight than normal weather (95% confidence interval: 9-24, P < 0.001). The increased risk was accentuated in the early afternoon, disappeared at night, extended to patients with different characteristics, involved crashes with diverse features, not apparent with cloudy weather, and contributed to about 5000 additional patient-days in hospital. The increased risk extended to patients with high crash severity as indicated by ambulance involvement, surgical procedures, length of hospital stay, intensive care unit admission, and patient mortality. The increased risk was not easily attributed to differences in alcohol consumption, driving distances, or anomalies of adverse weather.Bright sunlight is associated with an increased risk of a life-threatening motor vehicle crash. An awareness of this risk might inform driver education, trauma staffing, and safety warnings to prevent a life-threatening motor vehicle crash. Epidemiologic Study, level III.
Characteristics of Single Vehicle Crashes with a Teen Driver in South Carolina, 2005-2008.
Shults, Ruth A; Bergen, Gwen; Smith, Tracy J; Cook, Larry; Kindelberger, John; West, Bethany
2017-09-22
Teens' crash risk is highest in the first years of independent driving. Circumstances surrounding fatal crashes have been widely documented, but less is known about factors related to nonfatal teen driver crashes. This study describes single vehicle nonfatal crashes involving the youngest teen drivers (15-17 years), compares these crashes to single vehicle nonfatal crashes among adult drivers (35-44 years) and examines factors related to nonfatal injury producing crashes for teen drivers. Police crash data linked to hospital inpatient and emergency department data for 2005-2008 from the South Carolina Crash Outcomes Data Evaluation System (CODES) were analyzed. Nonfatal, single vehicle crashes involving passenger vehicles occurring on public roadways for teen (15-17 years) drivers were compared with those for adult (35-44 years) drivers on temporal patterns and crash risk factors per licensed driver and per vehicle miles traveled. Vehicle miles traveled by age group was estimated using data from the 2009 National Household Travel Survey. Multivariable log-linear regression analysis was conducted for teen driver crashes to determine which characteristics were related to crashes resulting in a minor/moderate injury or serious injury to at least one vehicle occupant. Compared with adult drivers, teen drivers in South Carolina had 2.5 times the single vehicle nonfatal crash rate per licensed driver and 11 times the rate per vehicle mile traveled. Teen drivers were nearly twice as likely to be speeding at the time of the crash compared with adult drivers. Teen driver crashes per licensed driver were highest during the afternoon hours of 3:00-5:59 pm and crashes per mile driven were highest during the nighttime hours of 9:00-11:59 pm. In 66% of the teen driver crashes, the driver was the only occupant. Crashes were twice as likely to result in serious injury when teen passengers were present than when the teen driver was alone. When teen drivers crashed while transporting teen passengers, the passengers were >5 times more likely to all be restrained if the teen driver was restrained. Crashes in which the teen driver was unrestrained were 80% more likely to result in minor/moderate injury and 6 times more likely to result in serious injury compared with crashes in which the teen driver was restrained. Despite the reductions in teen driver crashes associated with Graduated Driver Licensing (GDL), South Carolina's teen driver crash rates remain substantially higher than those for adult drivers. Established risk factors for fatal teen driver crashes, including restraint nonuse, transporting teen passengers, and speeding also increase the risk of nonfatal injury in single vehicle crashes. As South Carolina examines strategies to further reduce teen driver crashes and associated injuries, the state could consider updating its GDL passenger restriction to either none or one passenger <21years and dropping the passenger restriction exemption for trips to and from school. Surveillance systems such as CODES that link crash data with health outcome data provide needed information to more fully understand the circumstances and consequences of teen driver nonfatal crashes and evaluate the effectiveness of strategies to improve teen driver safety. Published by Elsevier Ltd.
Viano, David C; Parenteau, Chantal S
2018-06-21
This study investigated trends in severe injury and ejection in rollover crashes involving lap-shoulder belted drivers and right-front passengers. It was conducted because of changes in 2009 to consumer information programs and regulations related to rollover protection. The data is presented by model year (MY) of the vehicle in groups from 1995-2016. NASS-CDS cases with 2010-16 MY vehicles were also evaluated to determine the crash circumstances and causes for severe injury of belted occupants in vehicles with a high strength-to-weight (SWR) roof, curtain and side airbags and other safety improvements. 1997-2015 NASS-CDS data was evaluated for severe injury and ejection of lap-shoulder belted front-outboard occupants in light vehicles. Crashes were grouped by front, side, rear and rollover. The injury and ejection data was grouped by vehicle MY: 1995-99, 2000-04, 2005-09 and 2010-16. Only drivers and right-front passengers were included if they were lap-shoulder belted and 15+ years old. Severely injured occupants were defined as those with MAIS 4-6 or fatality (MAIS 4+F). National estimates were made with weighted data using the ratio weight in NASS-CDS. All NASS-CDS electronic cases were evaluated for belted occupants with MAIS 4+F injury in rollovers involving 2010-16 MY vehicles. The crash circumstances and injuries were studied. These vehicles had high SWR roofs to meet IIHS ratings and FMVSS 216. The 1997-2015 NASS-CDS included 2,083,776 belted front occupants in rollover crashes with 24,466 (1.17%) MAIS 4+F injuries. The frequency of rollover crashes has decreased with modern vehicles (p < 0.0001). The 1995-1999 MY vehicles involved in a rollover accounted for 7.03% of all crashes (756,228/10,760,000). The corresponding proportion was 3.57% with 2010-2016 MY vehicles (81,406 v 2,282,062). The risk for MAIS 4+F was 1.325 ± 0.347% in rollover crashes with 1995-99 MY vehicles. It was 27.2% lower in 2010-16 MY vehicles at 0.964 ± 0.331% (p < 0.001). There were 42,567 (2.002%) ejections of belted occupants in rollover crashes, irrespective of injury outcome. The risk for ejection was 3.042 ± 1.44% in rollover crashes with 1995-99 MY vehicles. It was 43.6% lower in 2004-2009 MY vehicle at 1.715 ± 0.660% (p <0.001) and 83.4% lower in 2010-16 MY vehicle at 0.505 ± 0.336% (p < 0.001). There were 17 rollovers with MAIS 4+F in 2010-16 MY vehicles in NASS-CDS. Their roof strength was SWR = 4.15 ± 1.05 based on 15 vehicles. Many of the collisions involved front or side impacts and then a rollover. Four cases involved 16-30 year old drivers in extremely high-speed loss of control crashes resulting in >10 cm vertical roof deformation or substantial roof deformation based on photos. The roof strength (SWR) of 4.20 ± 1.0 was not sufficient to prevent roof deformation in these crashes. This study found a reduction in severe injury and ejection risk with modern vehicles. It indicates vehicle safety has improved in response to IIHS and NHTSA efforts to expand the array of safety requirements and increase performance so that newer models are safer than earlier ones. There has been an incremental improvement in safety by these advances.
Graduated licensing laws and fatal crashes of teenage drivers: a national study.
McCartt, Anne T; Teoh, Eric R; Fields, Michele; Braitman, Keli A; Hellinga, Laurie A
2010-06-01
The objective of the current study was to quantify the effects of the strength of US state graduated driver licensing laws and specific licensing components on the rate of teenage driver fatal crash involvements per 100,000 teenagers during 1996-2007. The strengths of state laws were rated good, fair, marginal, or poor based on a system developed previously by the Insurance Institute for Highway Safety. Analysis was based on quarterly counts of drivers involved in fatal crashes. Associations of overall ratings and individual licensing components with teenage crash rates were evaluated using Poisson regression, with the corresponding fatal crash rate for drivers ages 30-59 controlling for state- or time-dependent influences on crash rates unrelated to graduated licensing laws. Compared with licensing laws rated poor, laws rated good were associated with 30 percent lower fatal crash rates among 15- to 17-year-olds. Laws rated fair yielded fatal crash rates 11 percent lower. The longer the permit age was delayed, or the longer the licensing age was delayed, the lower the estimated fatal crash rates among 15- to 17-year-olds. Stronger nighttime restrictions were associated with larger reductions, and reductions were larger for laws limiting teenage passengers to zero or one than laws allowing two or more teenage passengers or laws without passenger restrictions. After the effects of any related delay in licensure were accounted for, an increase in the minimum learner's permit holding period showed no association with fatal crash rates. An increase in required practice driving hours did not appear to have an independent association with fatal crash rates. Graduated licensing laws that include strong nighttime and passenger restrictions and laws that delay the learner's permit age and licensing age are associated with lower teenage fatal crash rates. States that adopt such laws can expect to achieve substantial reductions in crash deaths.
McEvoy, Suzanne P; Stevenson, Mark R; Woodward, Mark
2007-11-01
There is evidence that mobile phone use while driving (including hands-free) is associated with motor vehicle crashes. However, whether the effects of mobile phone use differ from that of passengers in the vehicle remains unclear. The aim of this research was to estimate the risk of crash associated with passenger carriage and compare that with mobile phone use. A case-control study ('passenger study') was performed in Perth, Western Australia in 2003 and 2004. Cases were 274 drivers who attended hospital following a motor vehicle crash and controls were 1096 drivers (1:4 matching) recruited at service stations matched to the location and time and day of week of the crash. The results were compared with those of a case-crossover study ('mobile phone study') undertaken concurrently (n=456); 152 cases were common to both studies. Passenger carriage increased the likelihood of a crash (adjusted odds ratio (adj. OR), 95% confidence interval (95% CI), 1.6, 1.1-2.2). Drivers carrying two or more passengers were twice as likely to crash as unaccompanied drivers (adj. OR 2.2, 95% CI 1.3-3.8). By comparison, driver's use of a mobile phone within 5 min before a crash was associated with a fourfold increased likelihood of crashing (OR 4.1, 95% CI 2.2-7.7). Passenger carriage and increasing numbers of passengers are associated with an increased likelihood of crash, though not to the same extent as mobile phone use. Further research is needed to investigate the factors underlying the increased risks.
Increased traffic accident rates associated with shale gas drilling in Pennsylvania.
Graham, Jove; Irving, Jennifer; Tang, Xiaoqin; Sellers, Stephen; Crisp, Joshua; Horwitz, Daniel; Muehlenbachs, Lucija; Krupnick, Alan; Carey, David
2015-01-01
We examined the association between shale gas drilling and motor vehicle accident rates in Pennsylvania. Using publicly available data on all reported vehicle crashes in Pennsylvania, we compared accident rates in counties with and without shale gas drilling, in periods with and without intermittent drilling (using data from 2005 to 2012). Counties with drilling were matched to non-drilling counties with similar population and traffic in the pre-drilling period. Heavily drilled counties in the north experienced 15-23% higher vehicle crash rates in 2010-2012 and 61-65% higher heavy truck crash rates in 2011-2012 than control counties. We estimated 5-23% increases in crash rates when comparing months with drilling and months without, but did not find significant effects on fatalities and major injury crashes. Heavily drilled counties in the southwest showed 45-47% higher rates of fatal and major injury crashes in 2012 than control counties, but monthly comparisons of drilling activity showed no significant differences associated with drilling. Vehicle accidents have measurably increased in conjunction with shale gas drilling. Copyright © 2014. Published by Elsevier Ltd.
The economic cost of road traffic crashes in an urban setting
García‐Altés, A; Pérez, K
2007-01-01
The objective of this article is to assess the total economic costs of road traffic crashes in Barcelona, a metropolitan city located in Southern Europe. A cost‐of‐illness study was conducted using a prevalence approximation, a societal and healthcare system perspective, and a 1‐year time horizon. Results were measured in terms of Euros in 2003. Total costs of road traffic crashes in Barcelona in 2003 were €367 million. Direct costs equalled €329 million (89.8% of total costs), including property damage costs, insurance administration costs and hospital costs. Police, emergency costs and transportation costs had a minimum effect on total direct costs. Indirect costs were €37 million, including lost productivity due to hospitalization and mortality. The results of the sensitivity analysis showed the upper limit of total economic cost of road traffic crashes in Barcelona to be €782 million. This is the first study to estimate the costs of road traffic crashes for a city in a developed country. The importance of the problem calls for further interventions to reduce road traffic crashes. PMID:17296693
Redelmeier, Donald A; Tibshirani, Robert J
2018-06-01
To demonstrate analytic approaches for matched studies where two controls are linked to each case and events are accumulating counts rather than binary outcomes. A secondary intent is to clarify the distinction between total risk and excess risk (unmatched vs. matched perspectives). We review past research testing whether elections can lead to increased traffic risks. The results are reinterpreted by analyzing both the total count of individuals in fatal crashes and the excess count of individuals in fatal crashes, each time accounting for the matched double controls. Overall, 1,546 individuals were in fatal crashes on the 10 election days (average = 155/d), and 2,593 individuals were in fatal crashes on the 20 control days (average = 130/d). Poisson regression of total counts yielded a relative risk of 1.19 (95% confidence interval: 1.12-1.27). Poisson regression of excess counts yielded a relative risk of 3.22 (95% confidence interval: 2.72-3.80). The discrepancy between analyses of total counts and excess counts replicated with alternative statistical models and was visualized in graphical displays. Available approaches provide methods for analyzing count data in matched designs with double controls and help clarify the distinction between increases in total risk and increases in excess risk. Copyright © 2018 Elsevier Inc. All rights reserved.
Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya
2017-02-01
Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.
Modeling driver response to lead vehicle decelerating
DOT National Transportation Integrated Search
2004-01-01
This paper presents a driver performance map of braking and steering in response to three driving scenarios that lead to rear-end crashes. This map encompasses low risk, conflict, near-crash, and crash imminent driving states that correspond to advis...
Sleep deficiency and motor vehicle crash risk in the general population: a prospective cohort study.
Gottlieb, Daniel J; Ellenbogen, Jeffrey M; Bianchi, Matt T; Czeisler, Charles A
2018-03-20
Insufficient sleep duration and obstructive sleep apnea, two common causes of sleep deficiency in adults, can result in excessive sleepiness, a well-recognized cause of motor vehicle crashes, although their contribution to crash risk in the general population remains uncertain. The objective of this study was to evaluate the relation of sleep apnea, sleep duration, and excessive sleepiness to crash risk in a community-dwelling population. This was a prospective observational cohort study nested within the Sleep Heart Health Study, a community-based study of the health consequences of sleep apnea. The participants were 1745 men and 1456 women aged 40-89 years. Sleep apnea was measured by home polysomnography and questionnaires were used to assess usual sleep duration and daytime sleepiness. A follow-up questionnaire 2 years after baseline ascertained driving habits and motor vehicle crash history. Logistic regression analysis was used to examine the relation of sleep apnea and sleep duration at baseline to the occurrence of motor vehicle crashes during the year preceding the follow-up visit, adjusting for relevant covariates. The population-attributable fraction of motor vehicle crashes was estimated from the sample proportion of motor vehicle crashes and the adjusted odds ratios for motor vehicle crash within each exposure category. Among 3201 evaluable participants, 222 (6.9%) reported at least one motor vehicle crash during the prior year. A higher apnea-hypopnea index (p < 0.01), fewer hours of sleep (p = 0.04), and self-reported excessive sleepiness (p < 0.01) were each significantly associated with crash risk. Severe sleep apnea was associated with a 123% increased crash risk, compared to no sleep apnea. Sleeping 6 hours per night was associated with a 33% increased crash risk, compared to sleeping 7 or 8 hours per night. These associations were present even in those who did not report excessive sleepiness. The population-attributable fraction of motor vehicle crashes was 10% due to sleep apnea and 9% due to sleep duration less than 7 hours. Sleep deficiency due to either sleep apnea or insufficient sleep duration is strongly associated with motor vehicle crashes in the general population, independent of self-reported excessive sleepiness.
Luxcey, Audrey; Contrand, Benjamin; Gadegbeku, Blandine; Delorme, Bernard; Tricotel, Aurore; Moore, Nicholas; Salmi, Louis‐Rachid; Lagarde, Emmanuel
2016-01-01
Aims To assess potential change in medicine exposure and association with the risk of road traffic crash across a time period that started before the implementation of a grading system warning of the effect of medicine on driving performance. Methods Data from three French national databases were extracted and matched: the national health care insurance database, police reports and the national police database of injurious crashes. Drivers involved in such crashes in France, from July 2005 to December 2011 and identified by their national identifier, were included. Association with the risk of crash was estimated using a case–control analysis comparing benzodiazepine and z‐hypnotic use among drivers responsible or not responsible for the crash. Results Totals of 69 353 responsible and 73 410 non‐responsible drivers involved in an injurious crash were included. Exposure to benzodiazepine anxiolytics was associated with an increased risk of being responsible for a road traffic crash during the pre‐intervention period (OR = 1.42 [1.24–1.62]). The association disappeared in the post‐intervention period, but became significant again thereafter. The risk of being responsible for a crash increased in users of z‐hypnotics across the study period. Conclusions Our results question the efficacy of the measures implemented to promote awareness about the effects of medicines on driving abilities. Prevention policies relating to the general driving population, but also to healthcare professionals, should be reviewed. PMID:27544927
Dezman, Zachary; de Andrade, Luciano; Vissoci, Joao Ricardo; El-Gabri, Deena; Johnson, Abree; Hirshon, Jon Mark; Staton, Catherine A.
2017-01-01
Introduction Road traffic injuries are a leading killer of youth (aged 15–29) and are projected to be the 7th leading cause of death by 2030. To better understand road traffic crash locations and characteristics in the city of Baltimore, we used police and census data, to describe the epidemiology, hotspots, and modifiable risk factors involved to guide further interventions. Materials and methods Data on all crashes in Baltimore City from 2009 to 2013 were made available from the Maryland Automated Accident Reporting System. Socioeconomic data collected by the US CENSUS 2010 were obtained. A time series analysis was conducted using an ARIMA model. We analyzed the geographical distribution of traffic crashes and hotspots using exploratory spatial data analysis and spatial autocorrelation. Spatial regression was performed to evaluate the impact of socioeconomic indicators on hotspots. Results In Baltimore City, between 2009 and 2013, there were a total of 100,110 crashes reported, with 1% of crashes considered severe. Of all crashes, 7% involved vulnerable road users and 12% had elderly or youth involvement. Reasons for crashes included: distracted driving (31%), speeding (6%), and alcohol or drug use (5%). After 2010, we observed an increasing trend in all crashes especially from March to June. Distracted driving then youth and elderly drivers were consistently the highest risk factors over time. Multivariate spatial regression model including socioeconomic indicators and controlling for age, gender and population size did not show a distinct predictor of crashes explaining only 20% of the road crash variability, indicating crashes are not geographically explained by socioeconomic indicators alone. Conclusion In Baltimore City, road traffic crashes occurred predominantly in the high density center of the city, involved distracted driving and extremes of age with an increase in crashes from March to June. There was no association between socioeconomic variables where crashes occurred and hotspots. In depth analysis of how modifiable risk factors are impacted by geospatial characteristics and the built environment is warranted in Baltimore to tailor interventions. PMID:27614672
Dezman, Zachary; de Andrade, Luciano; Vissoci, Joao Ricardo; El-Gabri, Deena; Johnson, Abree; Hirshon, Jon Mark; Staton, Catherine A
2016-11-01
Road traffic injuries are a leading killer of youth (aged 15-29) and are projected to be the 7th leading cause of death by 2030. To better understand road traffic crash locations and characteristics in the city of Baltimore, we used police and census data, to describe the epidemiology, hotspots, and modifiable risk factors involved to guide further interventions. Data on all crashes in Baltimore City from 2009 to 2013 were made available from the Maryland Automated Accident Reporting System. Socioeconomic data collected by the US CENSUS 2010 were obtained. A time series analysis was conducted using an ARIMA model. We analyzed the geographical distribution of traffic crashes and hotspots using exploratory spatial data analysis and spatial autocorrelation. Spatial regression was performed to evaluate the impact of socioeconomic indicators on hotspots. In Baltimore City, between 2009 and 2013, there were a total of 100,110 crashes reported, with 1% of crashes considered severe. Of all crashes, 7% involved vulnerable road users and 12% had elderly or youth involvement. Reasons for crashes included: distracted driving (31%), speeding (6%), and alcohol or drug use (5%). After 2010, we observed an increasing trend in all crashes especially from March to June. Distracted driving then youth and elderly drivers were consistently the highest risk factors over time. Multivariate spatial regression model including socioeconomic indicators and controlling for age, gender and population size did not show a distinct predictor of crashes explaining only 20% of the road crash variability, indicating crashes are not geographically explained by socioeconomic indicators alone. In Baltimore City, road traffic crashes occurred predominantly in the high density center of the city, involved distracted driving and extremes of age with an increase in crashes from March to June. There was no association between socioeconomic variables where crashes occurred and hotspots. In depth analysis of how modifiable risk factors are impacted by geospatial characteristics and the built environment is warranted in Baltimore to tailor interventions. Copyright © 2016 Elsevier Ltd. All rights reserved.
Vehicular crash data used to rank intersections by injury crash frequency and severity.
Liu, Yi; Li, Zongzhi; Liu, Jingxian; Patel, Harshingar
2016-09-01
This article contains data on research conducted in "A double standard model for allocating limited emergency medical service vehicle resources ensuring service reliability" (Liu et al., 2016) [1]. The crash counts were sorted out from comprehensive crash records of over one thousand major signalized intersections in the city of Chicago from 2004 to 2010. For each intersection, vehicular crashes were counted by crash severity levels, including fatal, injury Types A, B, and C for major, moderate, and minor injury levels, property damage only (PDO), and unknown. The crash data was further used to rank intersections by equivalent injury crash frequency. The top 200 intersections with the highest number of crash occurrences identified based on crash frequency- and severity-based scenarios are shared in this brief. The provided data would be a valuable source for research in urban traffic safety analysis and could also be utilized to examine the effectiveness of traffic safety improvement planning and programming, intersection design enhancement, incident and emergency management, and law enforcement strategies.
Stuckey, Rwth; LaMontagne, Anthony D; Glass, Deborah C; Sim, Malcolm R
2010-04-01
To estimate occupational light vehicle (OLV) fatality numbers using vehicle registration and crash data and compare these with previous estimates based on workers' compensation data. New South Wales (NSW) Roads and Traffic Authority (RTA) vehicle registration and crash data were obtained for 2004. NSW is the only Australian jurisdiction with mandatory work-use registration, which was used as a proxy for work-relatedness. OLV fatality rates based on registration data as the denominator were calculated and comparisons made with published 2003/04 fatalities based on workers' compensation data. Thirty-four NSW RTA OLV-user fatalities were identified, a rate of 4.5 deaths per 100,000 organisationally registered OLV, whereas the Australian Safety and Compensation Council (ASCC), reported 28 OLV deaths Australia-wide. More OLV user fatalities were identified from vehicle registration-based data than those based on workers' compensation estimates and the data are likely to provide an improved estimate of fatalities specific to OLV use. OLV-use is an important cause of traumatic fatalities that would be better identified through the use of vehicle-registration data, which provides a stronger evidence base from which to develop policy responses. © 2010 The Authors. Journal Compilation © 2010 Public Health Association of Australia.
Injury risk functions for frontal oblique collisions.
Andricevic, Nino; Junge, Mirko; Krampe, Jonas
2018-03-09
The objective of this article was the construction of injury risk functions (IRFs) for front row occupants in oblique frontal crashes and a comparison to IRF of nonoblique frontal crashes from the same data set. Crashes of modern vehicles from GIDAS (German In-Depth Accident Study) were used as the basis for the construction of a logistic injury risk model. Static deformation, measured via displaced voxels on the postcrash vehicles, was used to calculate the energy dissipated in the crash. This measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year. Imputation from property damage cases was used to describe underrepresented low-severity crashes-a known shortcoming of GIDAS. Binary logistic regression was used to relate the stimuli (oEES) to the binary outcome variable (injured or not injured). IRFs for the oblique frontal impact and nonoblique frontal impact were computed for the Maximum Abbreviated Injury Scale (MAIS) 2+ and 3+ levels for adults (18-64 years). For a given stimulus, the probability of injury for a belted driver was higher in oblique crashes than in nonoblique frontal crashes. For the 25% injury risk at MAIS 2+ level, the corresponding stimulus for oblique crashes was 40 km/h but it was 64 km/h for nonoblique frontal crashes. The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes. In the real world, most MAIS 2+ injuries occur in an oEES range from 30 to 60 km/h.
Rear seat safety: Variation in protection by occupant, crash and vehicle characteristics.
Durbin, Dennis R; Jermakian, Jessica S; Kallan, Michael J; McCartt, Anne T; Arbogast, Kristy B; Zonfrillo, Mark R; Myers, Rachel K
2015-07-01
Current information on the safety of rear row occupants of all ages is needed to inform further advances in rear seat restraint system design and testing. The objectives of this study were to describe characteristics of occupants in the front and rear rows of model year 2000 and newer vehicles involved in crashes and determine the risk of serious injury for restrained crash-involved rear row occupants and the relative risk of fatal injury for restrained rear row vs. front passenger seat occupants by age group, impact direction, and vehicle model year. Data from the National Automotive Sampling System Crashworthiness Data System (NASS-CDS) and Fatality Analysis Reporting System (FARS) were queried for all crashes during 2007-2012 involving model year 2000 and newer passenger vehicles. Data from NASS-CDS were used to describe characteristics of occupants in the front and rear rows and to determine the risk of serious injury (AIS 3+) for restrained rear row occupants by occupant age, vehicle model year, and impact direction. Using a combined data set containing data on fatalities from FARS and estimates of the total population of occupants in crashes from NASS-CDS, logistic regression modeling was used to compute the relative risk (RR) of death for restrained occupants in the rear vs. front passenger seat by occupant age, impact direction, and vehicle model year. Among all vehicle occupants in tow-away crashes during 2007-2012, 12.3% were in the rear row where the overall risk of serious injury was 1.3%. Among restrained rear row occupants, the risk of serious injury varied by occupant age, with older adults at the highest risk of serious injury (2.9%); by impact direction, with rollover crashes associated with the highest risk (1.5%); and by vehicle model year, with model year 2007 and newer vehicles having the lowest risk of serious injury (0.3%). Relative risk of death was lower for restrained children up to age 8 in the rear compared with passengers in the right front seat (RR=0.27, 95% CI 0.12-0.58 for 0-3 years, RR=0.55, 95% CI 0.30-0.98 for 4-8 years) but was higher for restrained 9-12-year-old children (RR=1.83, 95% CI 1.18-2.84). There was no evidence for a difference in risk of death in the rear vs. front seat for occupants ages 13-54, but there was some evidence for an increased relative risk of death for adults age 55 and older in the rear vs. passengers in the right front seat (RR=1.41, 95% CI 0.94-2.13), though we could not exclude the possibility of no difference. After controlling for occupant age and gender, the relative risk of death for restrained rear row occupants was significantly higher than that of front seat occupants in model year 2007 and newer vehicles and significantly higher in rear and right side impact crashes. Results of this study extend prior research on the relative safety of the rear seat compared with the front by examining a more contemporary fleet of vehicles. The rear row is primarily occupied by children and adolescents, but the variable relative risk of death in the rear compared with the front seat for occupants of different age groups highlights the challenges in providing optimal protection to a wide range of rear seat occupants. Findings of an elevated risk of death for rear row occupants, as compared with front row passengers, in the newest model year vehicles provides further evidence that rear seat safety is not keeping pace with advances in the front seat. Copyright © 2015 Elsevier Ltd. All rights reserved.
Risk of injurious road traffic crash after prescription of antidepressants.
Orriols, Ludivine; Queinec, Raphaëlle; Philip, Pierre; Gadegbeku, Blandine; Delorme, Bernard; Moore, Nicholas; Suissa, Samy; Lagarde, Emmanuel
2012-08-01
To estimate the risk of road traffic crash associated with prescription of antidepressants. Data were extracted and matched from 3 French national databases: the national health care insurance database, police reports, and the national police database of injurious crashes. A case-control analysis comparing 34,896 responsible versus 37,789 nonresponsible drivers was conducted. Case-crossover analysis was performed to investigate the acute effect of medicine exposure. 72,685 drivers, identified by their national health care number, involved in an injurious crash in France from July 2005 to May 2008 were included. 2,936 drivers (4.0%) were exposed to at least 1 antidepressant on the day of the crash. The results showed a significant association between the risk of being responsible for a crash and prescription of antidepressants (odds ratio [OR] = 1.34; 95% CI, 1.22-1.47). The case-crossover analysis showed no association with treatment prescription, but the risk of road traffic crash increased after an initiation of antidepressant treatment (OR = 1.49; 95% CI, 1.24-1.79) and after a change in antidepressant treatment (OR = 1.32; 95% CI, 1.09-1.60). Patients and prescribers should be warned about the risk of crash during periods of treatment with antidepressant medication and about particularly high vulnerability periods such as those when a treatment is initiated or modified. © Copyright 2012 Physicians Postgraduate Press, Inc.
Light aircraft crash safety program
NASA Technical Reports Server (NTRS)
Thomson, R. G.; Hayduk, R. J.
1974-01-01
NASA is embarked upon research and development tasks aimed at providing the general aviation industry with a reliable crashworthy airframe design technology. The goals of the NASA program are: reliable analytical techniques for predicting the nonlinear behavior of structures; significant design improvements of airframes; and simulated full-scale crash test data. The analytical tools will include both simplified procedures for estimating energy absorption characteristics and more complex computer programs for analysis of general airframe structures under crash loading conditions. The analytical techniques being developed both in-house and under contract are described, and a comparison of some analytical predictions with experimental results is shown.
ITS impacts on safety and traffic management : an investigation of secondary crash causes
DOT National Transportation Integrated Search
1999-01-01
In this paper, the authors focus on identifying potential savings from lowering the likelihood of secondary crash occurrences in incidents. Logistic regression models are developed to examine which primary crash characteristics are likely to influenc...
A cross-comparison of different techniques for modeling macro-level cyclist crashes.
Guo, Yanyong; Osama, Ahmed; Sayed, Tarek
2018-04-01
Despite the recognized benefits of cycling as a sustainable mode of transportation, cyclists are considered vulnerable road users and there are concerns about their safety. Therefore, it is essential to investigate the factors affecting cyclist safety. The goal of this study is to evaluate and compare different approaches of modeling macro-level cyclist safety as well as investigating factors that contribute to cyclist crashes using a comprehensive list of covariates. Data from 134 traffic analysis zones (TAZs) in the City of Vancouver were used to develop macro-level crash models (CM) incorporating variables related to actual traffic exposure, socio-economics, land use, built environment, and bike network. Four types of CMs were developed under a full Bayesian framework: Poisson lognormal model (PLN), random intercepts PLN model (RIPLN), random parameters PLN model (RPPLN), and spatial PLN model (SPLN). The SPLN model had the best goodness of fit, and the results highlighted the significant effects of spatial correlation. The models showed that the cyclist crashes were positively associated with bike and vehicle exposure measures, households, commercial area density, and signal density. On the other hand, negative associations were found between cyclist crashes and some bike network indicators such as average edge length, average zonal slope, and off-street bike links. Copyright © 2018 Elsevier Ltd. All rights reserved.
General aviation crash safety program at Langley Research Center
NASA Technical Reports Server (NTRS)
Thomson, R. G.
1976-01-01
The purpose of the crash safety program is to support development of the technology to define and demonstrate new structural concepts for improved crash safety and occupant survivability in general aviation aircraft. The program involves three basic areas of research: full-scale crash simulation testing, nonlinear structural analyses necessary to predict failure modes and collapse mechanisms of the vehicle, and evaluation of energy absorption concepts for specific component design. Both analytical and experimental methods are being used to develop expertise in these areas. Analyses include both simplified procedures for estimating energy absorption capabilities and more complex computer programs for analysis of general airframe response. Full-scale tests of typical structures as well as tests on structural components are being used to verify the analyses and to demonstrate improved design concepts.
Effect of vehicular size on chain-reaction crash
NASA Astrophysics Data System (ADS)
Nagatani, Takashi
2015-11-01
We present the dynamic model of the chain-reaction crash to take account of the vehicular size. Drivers brake according to taillights of the forward vehicle. We investigate the effect of the vehicular size on the chain-reaction crash (multiple-vehicle collision) in the traffic flow controlled by taillights. In the multiple-vehicle collision, the first crash induces more collisions. We investigate how the first collision induces the chain-reaction crash numerically. We derive, analytically, the transition points and the region maps for the chain-reaction crash in the traffic flow of vehicles with finite sizes. We clarify the effect of the vehicular size on the multiple-vehicle collision.
The effect of crash experience on changes in risk taking among urban and rural young people.
Lin, Mau-Roung; Huang, Wenzheng; Hwang, Hei-Fen; Wu, Hong-Dar Isaac; Yen, Lee-Lan
2004-03-01
A 20-month prospective study was conducted to investigate the effect of motorcycle crash experience on changes in risk taking among 2514 urban and 2304 rural students in Taiwan. Risk taking was assessed using a 14-item self-administered questionnaire at the beginning and end of the study. A risk-taking score for each student at the initial and the last follow-up assessments was generated from adding up points across all 14 items. For exposure variables, the study documented past motorcycle crash history at the initial assessment and collected detailed information about any motorcycle crash involvement that occurred during the study period. A general linear mixed model was applied to assess the effects of prior and recent crash involvements on the path of risk-taking behavior. The results show that at the initial assessment, students with crash experience had higher risk-taking levels than those without crash experience. However, crash experience, irregardless of whether it was measured in terms of crash history prior to the study, crash frequency, time elapsed since the last crash, or crash severity, did not significantly change the risk-taking path among students, even though its effect differed between urban and rural areas.
Cai, Qing; Lee, Jaeyoung; Eluru, Naveen; Abdel-Aty, Mohamed
2016-08-01
This study attempts to explore the viability of dual-state models (i.e., zero-inflated and hurdle models) for traffic analysis zones (TAZs) based pedestrian and bicycle crash frequency analysis. Additionally, spatial spillover effects are explored in the models by employing exogenous variables from neighboring zones. The dual-state models such as zero-inflated negative binomial and hurdle negative binomial models (with and without spatial effects) are compared with the conventional single-state model (i.e., negative binomial). The model comparison for pedestrian and bicycle crashes revealed that the models that considered observed spatial effects perform better than the models that did not consider the observed spatial effects. Across the models with spatial spillover effects, the dual-state models especially zero-inflated negative binomial model offered better performance compared to single-state models. Moreover, the model results clearly highlighted the importance of various traffic, roadway, and sociodemographic characteristics of the TAZ as well as neighboring TAZs on pedestrian and bicycle crash frequency. Copyright © 2016 Elsevier Ltd. All rights reserved.
Fatigue and crashes: the case of freight transport in Colombia.
Torregroza-Vargas, Nathaly M; Bocarejo, Juan Pablo; Ramos-Bonilla, Juan P
2014-11-01
Truck drivers have been involved in a significant number of road fatalities in Colombia. To identify variables that could be associated with crashes in which truck drivers are involved, a logistic regression model was constructed. The model had as the response variable a dichotomous variable that included the presence or absence of a crash during a specific trip. As independent variables the model included information regarding a driver's work shift, with variables that could be associated with driver's fatigue. The model also included potential confounders related with road conditions. With the model, it was possible to determine the odds ratio of a crash in relation to several variables, adjusting for confounding. To collect the information about the trips included in the model, a survey among truck drivers was conducted. The results suggest strong associations between crashes (i.e., some of them statistically significant) with the number of stops made during the trip, and the average time of each stop. Survey analysis allowed us to identify the practices that contribute to generating fatigue and unhealthy conditions on the road among professional drivers. A review of national regulations confirmed the lack of legislation on this topic. Copyright © 2014 Elsevier Ltd. All rights reserved.
Jiang, Ximiao; Huang, Baoshan; Yan, Xuedong; Zaretzki, Russell L; Richards, Stephen
2013-01-01
The severity of traffic-related injuries has been studied by many researchers in recent decades. However, the evaluation of many factors is still in dispute and, until this point, few studies have taken into account pavement management factors as points of interest. The objective of this article is to evaluate the combined influences of pavement management factors and traditional traffic engineering factors on the injury severity of 2-vehicle crashes. This study examines 2-vehicle rear-end, sideswipe, and angle collisions that occurred on Tennessee state routes from 2004 to 2008. Both the traditional ordered probit (OP) model and Bayesian ordered probit (BOP) model with weak informative prior were fitted for each collision type. The performances of these models were evaluated based on the parameter estimates and deviances. The results indicated that pavement management factors played identical roles in all 3 collision types. Pavement serviceability produces significant positive effects on the severity of injuries. The pavement distress index (PDI), rutting depth (RD), and rutting depth difference between right and left wheels (RD_df) were not significant in any of these 3 collision types. The effects of traffic engineering factors varied across collision types, except that a few were consistently significant in all 3 collision types, such as annual average daily traffic (AADT), rural-urban location, speed limit, peaking hour, and light condition. The findings of this study indicated that improved pavement quality does not necessarily lessen the severity of injuries when a 2-vehicle crash occurs. The effects of traffic engineering factors are not universal but vary by the type of crash. The study also found that the BOP model with a weak informative prior can be used as an alternative but was not superior to the traditional OP model in terms of overall performance.
Teh, Boon Kin; Cheong, Siew Ann
2016-01-01
The Global Financial Crisis of 2007-2008 wiped out US$37 trillions across global financial markets, this value is equivalent to the combined GDPs of the United States and the European Union in 2014. The defining moment of this crisis was the failure of Lehman Brothers, which precipitated the October 2008 crash and the Asian Correction (March 2009). Had the Federal Reserve seen these crashes coming, they might have bailed out Lehman Brothers, and prevented the crashes altogether. In this paper, we show that some of these market crashes (like the Asian Correction) can be predicted, if we assume that a large number of adaptive traders employing competing trading strategies. As the number of adherents for some strategies grow, others decline in the constantly changing strategy space. When a strategy group grows into a giant component, trader actions become increasingly correlated and this is reflected in the stock price. The fragmentation of this giant component will leads to a market crash. In this paper, we also derived the mean-field market crash forecast equation based on a model of fusions and fissions in the trading strategy space. By fitting the continuous returns of 20 stocks traded in Singapore Exchange to the market crash forecast equation, we obtain crash predictions ranging from end October 2008 to mid-February 2009, with early warning four to six months prior to the crashes.
Teh, Boon Kin; Cheong, Siew Ann
2016-01-01
The Global Financial Crisis of 2007-2008 wiped out US$37 trillions across global financial markets, this value is equivalent to the combined GDPs of the United States and the European Union in 2014. The defining moment of this crisis was the failure of Lehman Brothers, which precipitated the October 2008 crash and the Asian Correction (March 2009). Had the Federal Reserve seen these crashes coming, they might have bailed out Lehman Brothers, and prevented the crashes altogether. In this paper, we show that some of these market crashes (like the Asian Correction) can be predicted, if we assume that a large number of adaptive traders employing competing trading strategies. As the number of adherents for some strategies grow, others decline in the constantly changing strategy space. When a strategy group grows into a giant component, trader actions become increasingly correlated and this is reflected in the stock price. The fragmentation of this giant component will leads to a market crash. In this paper, we also derived the mean-field market crash forecast equation based on a model of fusions and fissions in the trading strategy space. By fitting the continuous returns of 20 stocks traded in Singapore Exchange to the market crash forecast equation, we obtain crash predictions ranging from end October 2008 to mid-February 2009, with early warning four to six months prior to the crashes. PMID:27706198
Dynamic compositional modeling of pedestrian crash counts on urban roads in Connecticut.
Serhiyenko, Volodymyr; Ivan, John N; Ravishanker, Nalini; Islam, Md Saidul
2014-03-01
Uncovering the temporal trend in crash counts provides a good understanding of the context for pedestrian safety. With a rareness of pedestrian crashes it is impossible to investigate monthly temporal effects with an individual segment/intersection level data, thus the time dependence should be derived from the aggregated level data. Most previous studies have used annual data to investigate the differences in pedestrian crashes between different regions or countries in a given year, and/or to look at time trends of fatal pedestrian injuries annually. Use of annual data unfortunately does not provide sufficient information on patterns in time trends or seasonal effects. This paper describes statistical methods uncovering patterns in monthly pedestrian crashes aggregated on urban roads in Connecticut from January 1995 to December 2009. We investigate the temporal behavior of injury severity levels, including fatal (K), severe injury (A), evident minor injury (B), and non-evident possible injury and property damage only (C and O), as proportions of all pedestrian crashes in each month, taking into consideration effects of time trend, seasonal variations and VMT (vehicle miles traveled). This type of dependent multivariate data is characterized by positive components which sum to one, and occurs in several applications in science and engineering. We describe a dynamic framework with vector autoregressions (VAR) for modeling and predicting compositional time series. Combining these predictions with predictions from a univariate statistical model for total crash counts will then enable us to predict pedestrian crash counts with the different injury severity levels. We compare these predictions with those obtained from fitting separate univariate models to time series of crash counts at each injury severity level. We also show that the dynamic models perform better than the corresponding static models. We implement the Integrated Nested Laplace Approximation (INLA) approach to enable fast Bayesian posterior computation. Taking CO injury severity level as a baseline for the compositional analysis, we conclude that there was a noticeable shift in the proportion of pedestrian crashes from injury severity A to B, while the increase for injury severity K was extremely small over time. This shift to the less severe injury level (from A to B) suggests that the overall safety on urban roads in Connecticut is improving. In January and February, there was some increase in the proportions for levels A and B over the baseline, indicating a seasonal effect. We found evidence that an increase in VMT would result in a decrease of proportions over the baseline for all injury severity levels. Our dynamic model uncovered a decreasing trend in all pedestrian crash counts before April 2005, followed by a noticeable increase and a flattening out until the end of the fitting period. This appears to be largely due to the behavior of injury severity level A pedestrian crashes. Copyright © 2013 Elsevier Ltd. All rights reserved.
Assessing the Impact of Local Agency Traffic Safety Training Using Ethnographic Techniques
ERIC Educational Resources Information Center
Colling, Timothy K.
2010-01-01
Traffic crashes are a significant source of loss of life, personal injury and financial expense in the United States. In 2008 there were 37,261 people killed and an estimated 2,346,000 people injured nationwide in motor vehicle traffic crashes. State and federal agencies are beginning to focus traffic safety improvement effort on local agency…
Explaining reduction of pedestrian-motor vehicle crashes in Arkhangelsk, Russia, in 2005-2010.
Kudryavtsev, Alexander V; Nilssen, Odd; Lund, Johan; Grjibovski, Andrej M; Ytterstad, Børge
2012-01-01
To explain a reduction in pedestrian-motor vehicle crashes in Arkhangelsk, Russia, in 2005-2010. Retrospective ecological study. For 2005-2010, police data on pedestrian-motor vehicle crashes, traffic violations, and total motor vehicles (MVs) were combined with data on changes in national road traffic legislation and municipal road infrastructure. Negative binomial regression was used to investigate trends in monthly rates of pedestrian-motor vehicle crashes per total MVs and estimate changes in these rates per unit changes in the safety measures. During the 6 years, the police registered 2,565 pedestrian-motor vehicle crashes: 1,597 (62%) outside crosswalks, 766 (30%) on non-signalized crosswalks, and 202 (8%) on signalized crosswalks. Crash rates outside crosswalks and on signalized crosswalks decreased on average by 1.1% per month, whereas the crash rate on non-signalized crosswalks remained unchanged. Numbers of signalized and non-signalized crosswalks increased by 14 and 19%, respectively. Also, 10% of non-signalized crosswalks were combined with speed humps, and 4% with light-reflecting vertical signs. Pedestrian penalties for traffic violations increased 4-fold. Driver penalties for ignoring prohibiting signal and failure to give way to pedestrian on non-signalized crosswalk increased 7- and 8-fold, respectively. The rate of total registered drivers' traffic violations per total MVs decreased on average by 0.3% per month. All studied infrastructure and legislative measures had inverse associations with the rate of crashes outside crosswalks. The rate of crashes on signalized crosswalks showed inverse associations with related monetary penalties. The introduction of infrastructure and legislative measures is the most probable explanation of the reduction of pedestrian-motor vehicle crashes in Arkhangelsk. The overall reduction is due to decreases in rates of crashes outside crosswalks and on signalized crosswalks. No change was observed in the rate of crashes on non-signalized crosswalks.
Comprehensive target populations for current active safety systems using national crash databases.
Kusano, Kristofer D; Gabler, Hampton C
2014-01-01
The objective of active safety systems is to prevent or mitigate collisions. A critical component in the design of active safety systems is the identification of the target population for a proposed system. The target population for an active safety system is that set of crashes that a proposed system could prevent or mitigate. Target crashes have scenarios in which the sensors and algorithms would likely activate. For example, the rear-end crash scenario, where the front of one vehicle contacts another vehicle traveling in the same direction and in the same lane as the striking vehicle, is one scenario for which forward collision warning (FCW) would be most effective in mitigating or preventing. This article presents a novel set of precrash scenarios based on coded variables from NHTSA's nationally representative crash databases in the United States. Using 4 databases (National Automotive Sampling System-General Estimates System [NASS-GES], NASS Crashworthiness Data System [NASS-CDS], Fatality Analysis Reporting System [FARS], and National Motor Vehicle Crash Causation Survey [NMVCCS]) the scenarios developed in this study can be used to quantify the number of police-reported crashes, seriously injured occupants, and fatalities that are applicable to proposed active safety systems. In this article, we use the precrash scenarios to identify the target populations for FCW, pedestrian crash avoidance systems (PCAS), lane departure warning (LDW), and vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) systems. Crash scenarios were derived using precrash variables (critical event, accident type, precrash movement) present in all 4 data sources. This study found that these active safety systems could potentially mitigate approximately 1 in 5 of all severity and serious injury crashes in the United States and 26 percent of fatal crashes. Annually, this corresponds to 1.2 million all severity, 14,353 serious injury (MAIS 3+), and 7412 fatal crashes. In addition, we provide the source code for the crash scenarios as an appendix (see online supplement) to this article so that researchers can use the crash scenarios in future research.
Effect of Maryland's 2011 Alcohol Sales Tax Increase on Alcohol-Positive Driving.
Lavoie, Marie-Claude; Langenberg, Patricia; Villaveces, Andres; Dischinger, Patricia C; Simoni-Wastila, Linda; Hoke, Kathleen; Smith, Gordon S
2017-07-01
The 2011 Maryland alcohol sales tax increase from 6% to 9% provided an opportunity to evaluate the impact on rates of alcohol-positive drivers involved in injury crashes. Maryland police crash reports from 2001 to 2013 were analyzed using an interrupted time series design and a multivariable analysis employing generalized estimating equations models with a negative binomial distribution. Data were analyzed in 2014-2015. There was a significant gradual annual reduction of 6% in the population-based rate of all alcohol-positive drivers (p<0.03), and a 12% reduction for drivers aged 15-20 years (p<0.007), and 21-34 years (p<0.001) following the alcohol sales tax increase. There were no significant changes in rates of alcohol-positive drivers aged 35-54 years (rate ratio, 0.98; 95% CI=0.89, 1.09). Drivers aged ≥55 years had a significant immediate 10% increase in the rate of alcohol-positive drivers (rate ratio, 1.10; 95% CI=1.04, 1.16) and a gradual increase of 4.8% per year after the intervention. Models using different denominators and controlling for multiple factors including a proxy for unmeasured factors found similar results overall. The 2011 Maryland alcohol sales tax increase led to a significant reduction in the rate of all alcohol-positive drivers involved in injury crashes especially among drivers aged 15-34 years. This is the first study to examine the impact of alcohol sales taxes on crashes; previous research focused on excise tax. Increasing alcohol taxes is an important but often neglected intervention to reduce alcohol-impaired driving. Copyright © 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Røe, Cecilie; Skandsen, Toril; Manskow, Unn; Ader, Tiina; Anke, Audny
2015-01-01
The aim of the present study was to evaluate mortality and functional outcome in old and very old patients with severe traumatic brain injury (TBI) and compare to the predicted outcome according to the internet based CRASH (Corticosteroid Randomization After Significant Head injury) model based prediction, from the Medical Research Council (MRC). Methods. Prospective, national multicenter study including patients with severe TBI ≥65 years. Predicted mortality and outcome were calculated based on clinical information (CRASH basic) (age, GCS score, and pupil reactivity to light), as well as with additional CT findings (CRASH CT). Observed 14-day mortality and favorable/unfavorable outcome according to the Glasgow Outcome Scale at one year was compared to the predicted outcome according to the CRASH models. Results. 97 patients, mean age 75 (SD 7) years, 64% men, were included. Two patients were lost to follow-up; 48 died within 14 days. The predicted versus the observed odds ratio (OR) for mortality was 2.65. Unfavorable outcome (GOSE < 5) was observed at one year follow-up in 72% of patients. The CRASH models predicted unfavorable outcome in all patients. Conclusion. The CRASH model overestimated mortality and unfavorable outcome in old and very old Norwegian patients with severe TBI. PMID:26688614
Child passengers injured in motor vehicle crashes.
Romano, Eduardo; Kelley-Baker, Tara
2015-02-01
During 2010, 171,000 children aged 0-14 were injured in motor vehicle crashes. Despite the severity of the problem, research has been limited, and most of what we know about these children emanates from fatal crash databases. Using information from the General Estimates System, this effort examines the occurrence of non-fatal crashes among children aged 0-14 over the last decade. We found that about 1% of the non-injured children in the file had been driven by a driver who was positive for alcohol. This percentage climbed to about 2% among children who had suffered injuries. Compared with the proportion of alcohol-positive drivers at the time of the crash, the proportion of drivers who sped or failed to obey a traffic signal was significantly higher. The finding that drinking and driving with children did not decrease over time questions the adequacy of the extant child endangerment laws. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.