Fine-granularity inference and estimations to network traffic for SDN.
Jiang, Dingde; Huo, Liuwei; Li, Ya
2018-01-01
An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective.
Fine-granularity inference and estimations to network traffic for SDN
Huo, Liuwei; Li, Ya
2018-01-01
An end-to-end network traffic matrix is significantly helpful for network management and for Software Defined Networks (SDN). However, the end-to-end network traffic matrix's inferences and estimations are a challenging problem. Moreover, attaining the traffic matrix in high-speed networks for SDN is a prohibitive challenge. This paper investigates how to estimate and recover the end-to-end network traffic matrix in fine time granularity from the sampled traffic traces, which is a hard inverse problem. Different from previous methods, the fractal interpolation is used to reconstruct the finer-granularity network traffic. Then, the cubic spline interpolation method is used to obtain the smooth reconstruction values. To attain an accurate the end-to-end network traffic in fine time granularity, we perform a weighted-geometric-average process for two interpolation results that are obtained. The simulation results show that our approaches are feasible and effective. PMID:29718913
DOT National Transportation Integrated Search
2014-05-01
Travel demand forecasting models are used to predict future traffic volumes to evaluate : roadway improvement alternatives. Each of the metropolitan planning organizations (MPO) in : Alabama maintains a travel demand model to support planning efforts...
NASA Technical Reports Server (NTRS)
Wang, Jianzhong Jay; Datta, Koushik; Landis, Michael R. (Technical Monitor)
2002-01-01
This paper describes the development of a life-cycle cost (LCC) estimating methodology for air traffic control Decision Support Tools (DSTs) under development by the National Aeronautics and Space Administration (NASA), using a combination of parametric, analogy, and expert opinion methods. There is no one standard methodology and technique that is used by NASA or by the Federal Aviation Administration (FAA) for LCC estimation of prospective Decision Support Tools. Some of the frequently used methodologies include bottom-up, analogy, top-down, parametric, expert judgement, and Parkinson's Law. The developed LCC estimating methodology can be visualized as a three-dimensional matrix where the three axes represent coverage, estimation, and timing. This paper focuses on the three characteristics of this methodology that correspond to the three axes.
NASA Technical Reports Server (NTRS)
Wade, T. O.
1984-01-01
Reduction techniques for traffic matrices are explored in some detail. These matrices arise in satellite switched time-division multiple access (SS/TDMA) techniques whereby switching of uplink and downlink beams is required to facilitate interconnectivity of beam zones. A traffic matrix is given to represent that traffic to be transmitted from n uplink beams to n downlink beams within a TDMA frame typically of 1 ms duration. The frame is divided into segments of time and during each segment a portion of the traffic is represented by a switching mode. This time slot assignment is characterized by a mode matrix in which there is not more than a single non-zero entry on each line (row or column) of the matrix. Investigation is confined to decomposition of an n x n traffic matrix by mode matrices with a requirement that the decomposition be 100 percent efficient or, equivalently, that the line(s) in the original traffic matrix whose sum is maximal (called critical line(s)) remain maximal as mode matrices are subtracted throughout the decomposition process. A method of decomposition of an n x n traffic matrix by mode matrices results in a number of steps that is bounded by n(2) - 2n + 2. It is shown that this upper bound exists for an n x n matrix wherein all the lines are maximal (called a quasi doubly stochastic (QDS) matrix) or for an n x n matrix that is completely arbitrary. That is, the fact that no method can exist with a lower upper bound is shown for both QDS and arbitrary matrices, in an elementary and straightforward manner.
Krall, Jenna R; Ladva, Chandresh N; Russell, Armistead G; Golan, Rachel; Peng, Xing; Shi, Guoliang; Greenwald, Roby; Raysoni, Amit U; Waller, Lance A; Sarnat, Jeremy A
2018-06-01
Concentrations of traffic-related air pollutants are frequently higher within commuting vehicles than in ambient air. Pollutants found within vehicles may include those generated by tailpipe exhaust, brake wear, and road dust sources, as well as pollutants from in-cabin sources. Source-specific pollution, compared to total pollution, may represent regulation targets that can better protect human health. We estimated source-specific pollution exposures and corresponding pulmonary response in a panel study of commuters. We used constrained positive matrix factorization to estimate source-specific pollution factors and, subsequently, mixed effects models to estimate associations between source-specific pollution and pulmonary response. We identified four pollution factors that we named: crustal, primary tailpipe traffic, non-tailpipe traffic, and secondary. Among asthmatic subjects (N = 48), interquartile range increases in crustal and secondary pollution were associated with changes in lung function of -1.33% (95% confidence interval (CI): -2.45, -0.22) and -2.19% (95% CI: -3.46, -0.92) relative to baseline, respectively. Among non-asthmatic subjects (N = 51), non-tailpipe pollution was associated with pulmonary response only at 2.5 h post-commute. We found no significant associations between pulmonary response and primary tailpipe pollution. Health effects associated with traffic-related pollution may vary by source, and therefore some traffic pollution sources may require targeted interventions to protect health.
Performance of Stone Matrix Asphalt (SMA) Mixtures in the United States
DOT National Transportation Integrated Search
1997-01-01
Stone Matrix Asphalt (SMA) mixtures have been used in the United States since 1991. The traffic rate has been high on many of these pavements resulting in a significant amount of traffic during a short period of time. In 1994 the Federal Highway Admi...
Sahu, Manoranjan; Hu, Shaohua; Ryan, Patrick H; Le Masters, Grace; Grinshpun, Sergey A; Chow, Judith C; Biswas, Pratim
2011-06-01
Exposure to traffic-related pollution during childhood has been associated with asthma exacerbation, and asthma incidence. The objective of the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is to determine if the development of allergic and respiratory disease is associated with exposure to diesel engine exhaust particles. A detailed receptor model analyses was undertaken by applying positive matrix factorization (PMF) and UNMIX receptor models to two PM₂.₅ data sets: one consisting of two carbon fractions and the other of eight temperature-resolved carbon fractions. Based on the source profiles resolved from the analyses, markers of traffic-related air pollution were estimated: the elemental carbon attributed to traffic (ECAT) and elemental carbon attributed to diesel vehicle emission (ECAD). Application of UNMIX to the two data sets generated four source factors: combustion related sulfate, traffic, metal processing and soil/crustal. The PMF application generated six source factors derived from analyzing two carbon fractions and seven factors from temperature-resolved eight carbon fractions. The source factors (with source contribution estimates by mass concentrations in parentheses) are: combustion sulfate (46.8%), vegetative burning (15.8%), secondary sulfate (12.9%), diesel vehicle emission (10.9%), metal processing (7.5%), gasoline vehicle emission (5.6%) and soil/crustal (0.7%). Diesel and gasoline vehicle emission sources were separated using eight temperature-resolved organic and elemental carbon fractions. Application of PMF to both datasets also differentiated the sulfate rich source from the vegetative burning source, which are combined in a single factor by UNMIX modeling. Calculated ECAT and ECAD values at different locations indicated that traffic source impacts depend on factors such as traffic volumes, meteorological parameters, and the mode of vehicle operation apart from the proximity of the sites to highways. The difference in ECAT and ECAD, however, was less than one standard deviation. Thus, a cost benefit consideration should be used when deciding on the benefits of an eight or two carbon approach. Published by Elsevier B.V.
Wang, Yong; Ma, Xiaolei; Liu, Yong; Gong, Ke; Henricakson, Kristian C.; Xu, Maozeng; Wang, Yinhai
2016-01-01
This paper proposes a two-stage algorithm to simultaneously estimate origin-destination (OD) matrix, link choice proportion, and dispersion parameter using partial traffic counts in a congested network. A non-linear optimization model is developed which incorporates a dynamic dispersion parameter, followed by a two-stage algorithm in which Generalized Least Squares (GLS) estimation and a Stochastic User Equilibrium (SUE) assignment model are iteratively applied until the convergence is reached. To evaluate the performance of the algorithm, the proposed approach is implemented in a hypothetical network using input data with high error, and tested under a range of variation coefficients. The root mean squared error (RMSE) of the estimated OD demand and link flows are used to evaluate the model estimation results. The results indicate that the estimated dispersion parameter theta is insensitive to the choice of variation coefficients. The proposed approach is shown to outperform two established OD estimation methods and produce parameter estimates that are close to the ground truth. In addition, the proposed approach is applied to an empirical network in Seattle, WA to validate the robustness and practicality of this methodology. In summary, this study proposes and evaluates an innovative computational approach to accurately estimate OD matrices using link-level traffic flow data, and provides useful insight for optimal parameter selection in modeling travelers’ route choice behavior. PMID:26761209
Achieving Passive Localization with Traffic Light Schedules in Urban Road Sensor Networks
Niu, Qiang; Yang, Xu; Gao, Shouwan; Chen, Pengpeng; Chan, Shibing
2016-01-01
Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS), which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region. PMID:27735871
Joint parameter and state estimation algorithms for real-time traffic monitoring.
DOT National Transportation Integrated Search
2013-12-01
A common approach to traffic monitoring is to combine a macroscopic traffic flow model with traffic sensor data in a process called state estimation, data fusion, or data assimilation. The main challenge of traffic state estimation is the integration...
Towards Realistic Urban Traffic Experiments Using DFROUTER: Heuristic, Validation and Extensions.
Zambrano-Martinez, Jorge Luis; Calafate, Carlos T; Soler, David; Cano, Juan-Carlos
2017-12-15
Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels.
Ran, Bin; Song, Li; Cheng, Yang; Tan, Huachun
2016-01-01
Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%. PMID:27448326
Ran, Bin; Song, Li; Zhang, Jian; Cheng, Yang; Tan, Huachun
2016-01-01
Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%.
Barba, Lida; Rodríguez, Nibaldo; Montt, Cecilia
2014-01-01
Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel matrix (HSVD). In the second stage, an ARIMA model and two ANNs for one-step-ahead time series forecasting are used. The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. The proposed models are evaluated using a weekly time series of traffic accidents of Valparaíso, Chilean region, from 2003 to 2012. The best result is given by the combination HSVD-ARIMA, with a MAPE of 0:26%, followed by MA-ARIMA with a MAPE of 1:12%; the worst result is given by the MA-ANN based on PSO with a MAPE of 15:51%.
Towards Realistic Urban Traffic Experiments Using DFROUTER: Heuristic, Validation and Extensions
2017-01-01
Traffic congestion is an important problem faced by Intelligent Transportation Systems (ITS), requiring models that allow predicting the impact of different solutions on urban traffic flow. Such an approach typically requires the use of simulations, which should be as realistic as possible. However, achieving high degrees of realism can be complex when the actual traffic patterns, defined through an Origin/Destination (O-D) matrix for the vehicles in a city, remain unknown. Thus, the main contribution of this paper is a heuristic for improving traffic congestion modeling. In particular, we propose a procedure that, starting from real induction loop measurements made available by traffic authorities, iteratively refines the output of DFROUTER, which is a module provided by the SUMO (Simulation of Urban MObility) tool. This way, it is able to generate an O-D matrix for traffic that resembles the real traffic distribution and that can be directly imported by SUMO. We apply our technique to the city of Valencia, and we then compare the obtained results against other existing traffic mobility data for the cities of Cologne (Germany) and Bologna (Italy), thereby validating our approach. We also use our technique to determine what degree of congestion is expectable if certain conditions cause additional traffic to circulate in the city, adopting both a uniform pattern and a hotspot-based pattern for traffic injection to demonstrate how to regulate the overall number of vehicles in the city. This study allows evaluating the impact of vehicle flow changes on the overall traffic congestion levels. PMID:29244762
Traffic control device evaluation program : FY 2016.
DOT National Transportation Integrated Search
2017-03-01
This report presents findings on three different activities conducted in the Traffic Control Device Evaluation Program during the 2016 fiscal year. The first two activities are evaluations of full-matrix color light-emitting diode changeable message ...
Evaluation of the public health impacts of traffic congestion: a health risk assessment.
Levy, Jonathan I; Buonocore, Jonathan J; von Stackelberg, Katherine
2010-10-27
Traffic congestion is a significant issue in urban areas in the United States and around the world. Previous analyses have estimated the economic costs of congestion, related to fuel and time wasted, but few have quantified the public health impacts or determined how these impacts compare in magnitude to the economic costs. Moreover, the relative magnitudes of economic and public health impacts of congestion would be expected to vary significantly across urban areas, as a function of road infrastructure, population density, and atmospheric conditions influencing pollutant formation, but this variability has not been explored. In this study, we evaluate the public health impacts of ambient exposures to fine particulate matter (PM2.5) concentrations associated with a business-as-usual scenario of predicted traffic congestion. We evaluate 83 individual urban areas using traffic demand models to estimate the degree of congestion in each area from 2000 to 2030. We link traffic volume and speed data with the MOBILE6 model to characterize emissions of PM2.5 and particle precursors attributable to congestion, and we use a source-receptor matrix to evaluate the impact of these emissions on ambient PM2.5 concentrations. Marginal concentration changes are related to a concentration-response function for mortality, with a value of statistical life approach used to monetize the impacts. We estimate that the monetized value of PM2.5-related mortality attributable to congestion in these 83 cities in 2000 was approximately $31 billion (2007 dollars), as compared with a value of time and fuel wasted of $60 billion. In future years, the economic impacts grow (to over $100 billion in 2030) while the public health impacts decrease to $13 billion in 2020 before increasing to $17 billion in 2030, given increasing population and congestion but lower emissions per vehicle. Across cities and years, the public health impacts range from more than an order of magnitude less to in excess of the economic impacts. Our analyses indicate that the public health impacts of congestion may be significant enough in magnitude, at least in some urban areas, to be considered in future evaluations of the benefits of policies to mitigate congestion.
Masoumi, Kambiz; Forouzan, Arash; Barzegari, Hassan; Asgari Darian, Ali; Rahim, Fakher; Zohrevandi, Behzad; Nabi, Somayeh
2016-01-01
Introduction: Traffic accidents are the 8th cause of mortality in different countries and are expected to rise to the 3rd rank by 2020. Based on the Haddon matrix numerous factors such as environment, host, and agent can affect the severity of traffic-related traumas. Therefore, the present study aimed to evaluate the effective factors in severity of these traumas based on Haddon matrix. Methods: In the present 1-month cross-sectional study, all the patients injured in traffic accidents, who were referred to the ED of Imam Khomeini and Golestan Hospitals, Ahvaz, Iran, during March 2013 were evaluated. Based on the Haddon matrix, effective factors in accident occurrence were defined in 3 groups of host, agent, and environment. Demographic data of the patients and data regarding Haddon risk factors were extracted and analyzed using SPSS version 20. Results: 700 injured people with the mean age of 29.66 ± 12.64 years (3-82) were evaluated (92.4% male). Trauma mechanism was car-pedestrian in 308 (44%) of the cases and car-motorcycle in 175 (25%). 610 (87.1%) cases were traffic accidents and 371 (53%) occurred in the time between 2 pm and 8 pm. Violation of speed limit was the most common violation with 570 (81.4%) cases, followed by violation of right-of-way in 57 (8.1%) patients. 59.9% of the severe and critical injuries had occurred on road accidents, while 61.3% of the injuries caused by traffic accidents were mild to moderate (p < 0.001). The most common mechanisms of trauma for critical injuries were rollover (72.5%), motorcycle-pedestrian (23.8%), and car-motorcycle (13.14%) accidents (p < 0.001). Conclusion: Based on the results of the present study, the most important effective factors in severity of traffic accident-related traumas were age over 50, not using safety tools, and undertaking among host-related factors; insufficient environment safety, road accidents and time between 2 pm and 8 pm among environmental factors; and finally, rollover, car-pedestrian, and motorcycle-pedestrian accidents among the agent factors PMID:27274517
A wireless sensor network for urban traffic characterization and trend monitoring.
Fernández-Lozano, J J; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A
2015-10-15
Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.
Applicability of models to estimate traffic noise for urban roads.
Melo, Ricardo A; Pimentel, Roberto L; Lacerda, Diego M; Silva, Wekisley M
2015-01-01
Traffic noise is a highly relevant environmental impact in cities. Models to estimate traffic noise, in turn, can be useful tools to guide mitigation measures. In this paper, the applicability of models to estimate noise levels produced by a continuous flow of vehicles on urban roads is investigated. The aim is to identify which models are more appropriate to estimate traffic noise in urban areas since several models available were conceived to estimate noise from highway traffic. First, measurements of traffic noise, vehicle count and speed were carried out in five arterial urban roads of a brazilian city. Together with geometric measurements of width of lanes and distance from noise meter to lanes, these data were input in several models to estimate traffic noise. The predicted noise levels were then compared to the respective measured counterparts for each road investigated. In addition, a chart showing mean differences in noise between estimations and measurements is presented, to evaluate the overall performance of the models. Measured Leq values varied from 69 to 79 dB(A) for traffic flows varying from 1618 to 5220 vehicles/h. Mean noise level differences between estimations and measurements for all urban roads investigated ranged from -3.5 to 5.5 dB(A). According to the results, deficiencies of some models are discussed while other models are identified as applicable to noise estimations on urban roads in a condition of continuous flow. Key issues to apply such models to urban roads are highlighted.
Rodríguez, Nibaldo
2014-01-01
Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel matrix (HSVD). In the second stage, an ARIMA model and two ANNs for one-step-ahead time series forecasting are used. The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. The proposed models are evaluated using a weekly time series of traffic accidents of Valparaíso, Chilean region, from 2003 to 2012. The best result is given by the combination HSVD-ARIMA, with a MAPE of 0 : 26%, followed by MA-ARIMA with a MAPE of 1 : 12%; the worst result is given by the MA-ANN based on PSO with a MAPE of 15 : 51%. PMID:25243200
ERIC Educational Resources Information Center
Hart, Vincent G.
1981-01-01
Two examples are given of ways traffic engineers estimate traffic flow. The first, Floating Car Method, involves some basic ideas and the notion of relative velocity. The second, Maximum Traffic Flow, is viewed to involve simple applications of calculus. The material provides insight into specialized applications of mathematics. (MP)
Traffic evacuation time under nonhomogeneous conditions.
Fazio, Joseph; Shetkar, Rohan; Mathew, Tom V
2017-06-01
During many manmade and natural crises such as terrorist threats, floods, hazardous chemical and gas leaks, emergency personnel need to estimate the time in which people can evacuate from the affected urban area. Knowing an estimated evacuation time for a given crisis, emergency personnel can plan and prepare accordingly with the understanding that the actual evacuation time will take longer. Given the urban area to be evacuated, street widths exiting the area's perimeter, the area's population density, average vehicle occupancy, transport mode share and crawl speed, an estimation of traffic evacuation time can be derived. Peak-hour traffic data collected at three, midblock, Mumbai sites of varying geometric features and traffic composition were used in calibrating a model that estimates peak-hour traffic flow rates. Model validation revealed a correlation coefficient of +0.98 between observed and predicted peak-hour flow rates. A methodology is developed that estimates traffic evacuation time using the model.
DOT National Transportation Integrated Search
2009-09-15
Average annual daily traffic (AADT) is perhaps the most fundamental measure of traffic flow. The data used to produce AADT estimates are largely collected by in-highway traffic counters operated by traffic monitoring crews who must cover thousands of...
A Wireless Sensor Network for Urban Traffic Characterization and Trend Monitoring
Fernández-Lozano, J.J.; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A.
2015-01-01
Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach. PMID:26501278
Evaluation of the public health impacts of traffic congestion: a health risk assessment
2010-01-01
Background Traffic congestion is a significant issue in urban areas in the United States and around the world. Previous analyses have estimated the economic costs of congestion, related to fuel and time wasted, but few have quantified the public health impacts or determined how these impacts compare in magnitude to the economic costs. Moreover, the relative magnitudes of economic and public health impacts of congestion would be expected to vary significantly across urban areas, as a function of road infrastructure, population density, and atmospheric conditions influencing pollutant formation, but this variability has not been explored. Methods In this study, we evaluate the public health impacts of ambient exposures to fine particulate matter (PM2.5) concentrations associated with a business-as-usual scenario of predicted traffic congestion. We evaluate 83 individual urban areas using traffic demand models to estimate the degree of congestion in each area from 2000 to 2030. We link traffic volume and speed data with the MOBILE6 model to characterize emissions of PM2.5 and particle precursors attributable to congestion, and we use a source-receptor matrix to evaluate the impact of these emissions on ambient PM2.5 concentrations. Marginal concentration changes are related to a concentration-response function for mortality, with a value of statistical life approach used to monetize the impacts. Results We estimate that the monetized value of PM2.5-related mortality attributable to congestion in these 83 cities in 2000 was approximately $31 billion (2007 dollars), as compared with a value of time and fuel wasted of $60 billion. In future years, the economic impacts grow (to over $100 billion in 2030) while the public health impacts decrease to $13 billion in 2020 before increasing to $17 billion in 2030, given increasing population and congestion but lower emissions per vehicle. Across cities and years, the public health impacts range from more than an order of magnitude less to in excess of the economic impacts. Conclusions Our analyses indicate that the public health impacts of congestion may be significant enough in magnitude, at least in some urban areas, to be considered in future evaluations of the benefits of policies to mitigate congestion. PMID:20979626
Accuracy Of LTPP Traffic Loading Estimates
DOT National Transportation Integrated Search
1998-07-01
The accuracy and reliability of traffic load estimates are key to determining a pavement's life expectancy. To better understand the variability of traffic loading rates and its effect on the accuracy of the Long Term Pavement Performance (LTPP) prog...
Pan, Long; Yao, Enjian; Yang, Yang
2016-12-01
With the rapid development of urbanization and motorization in China, traffic-related air pollution has become a major component of air pollution which constantly jeopardizes public health. This study proposes an integrated framework for estimating the concentration of traffic-related air pollution with real-time traffic and basic meteorological information and also for further evaluating the impact of traffic-related air pollution. First, based on the vehicle emission factor models sensitive to traffic status, traffic emissions are calculated according to the real-time link-based average traffic speed, traffic volume, and vehicular fleet composition. Then, based on differences in meteorological conditions, traffic pollution sources are divided into line sources and point sources, and the corresponding methods to determine the dynamic affecting areas are also proposed. Subsequently, with basic meteorological data, Gaussian dispersion model and puff integration model are applied respectively to estimate the concentration of traffic-related air pollution. Finally, the proposed estimating framework is applied to calculate the distribution of CO concentration in the main area of Beijing, and the population exposure is also calculated to evaluate the impact of traffic-related air pollution on public health. Results show that there is a certain correlation between traffic indicators (i.e., traffic speed and traffic intensity) of the affecting area and traffic-related CO concentration of the target grid, which indicates the methods to determine the affecting areas are reliable. Furthermore, the reliability of the proposed estimating framework is verified by comparing the predicted and the observed ambient CO concentration. In addition, results also show that the traffic-related CO concentration is higher in morning and evening peak hours, and has a heavier impact on public health within the Fourth Ring Road of Beijing due to higher population density and higher CO concentration under calm wind condition in this area. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Chen, Shimon; Bekhor, Shlomo; Yuval; Broday, David M.
2016-10-01
Most air quality models use traffic-related variables as an input. Previous studies estimated nearby vehicular activity through sporadic traffic counts or via traffic assignment models. Both methods have previously produced poor or no data for nights, weekends and holidays. Emerging technologies allow the estimation of traffic through passive monitoring of location-aware devices. Examples of such devices are GPS transceivers installed in vehicles. In this work, we studied traffic volumes that were derived from such data. Additionally, we used these data for estimating ambient nitrogen dioxide concentrations, using a non-linear optimisation model that includes basic dispersion properties. The GPS-derived data show great potential for use as a proxy for pollutant emissions from motor-vehicles.
Traffic Tech: National Traffic Speeds Survey III: 2015
DOT National Transportation Integrated Search
2018-03-01
Vehicle speeds are an important factor in traffic safety. NHTSAs most recent data estimates that approximately 27 percent of all fatal motor vehicle crashes are speeding-related (NCSA, 2018). NHTSA estimated the economic cost of speeding-related c...
Implementation and Evaluation of Weather Responsive Traffic Estimation and Prediction System
DOT National Transportation Integrated Search
2012-06-01
The objective of the project is to develop a framework and procedures for implementing and evaluating weather-responsive traffic management (WRTM) strategies using Traffic Estimation and Prediction System (TrEPS) methodologies. In a previous FHWA-fun...
Using Mobile Device Samples to Estimate Traffic Volumes
DOT National Transportation Integrated Search
2017-12-01
In this project, TTI worked with StreetLight Data to evaluate a beta version of its traffic volume estimates derived from global positioning system (GPS)-based mobile devices. TTI evaluated the accuracy of average annual daily traffic (AADT) volume :...
Estimation of annual average daily traffic for off-system roads in Florida
DOT National Transportation Integrated Search
1999-07-28
Estimation of Annual Average Daily Traffic (AADT) is extremely important in traffic planning and operations for the state departments of transportation (DOTs), because AADT provides information for the planning of new road construction, determination...
NASA Technical Reports Server (NTRS)
Wickens, Christopher D.; Alexander, Amy L.
2004-01-01
We examined the ability for pilots to estimate traffic location in an Integrated Hazard Display, and how such estimations should be measured. Twelve pilots viewed static images of traffic scenarios and then estimated the outside world locations of queried traffic represented in one of three display types (2D coplanar, 3D exocentric, and split-screen) and in one of four conditions (display present/blank crossed with outside world present/blank). Overall, the 2D coplanar display best supported both vertical (compared to 3D) and lateral (compared to split-screen) traffic position estimation performance. Costs of the 3D display were associated with perceptual ambiguity. Costs of the split screen display were inferred to result from inappropriate attention allocation. Furthermore, although pilots were faster in estimating traffic locations when relying on memory, accuracy was greatest when the display was available.
A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data.
Wang, Xiaomeng; Peng, Ling; Chi, Tianhe; Li, Mengzhu; Yao, Xiaojing; Shao, Jing
2015-01-01
Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.
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...
Planning Inmarsat's second generation of spacecraft
NASA Astrophysics Data System (ADS)
Williams, W. P.
1982-09-01
The next generation of studies of the Inmarsat service are outlined, such as traffic forecasting studies, communications capacity estimates, space segment design, cost estimates, and financial analysis. Traffic forecasting will require future demand estimates, and a computer model has been developed which estimates demand over the Atlantic, Pacific, and Indian ocean regions. Communications estimates are based on traffic estimates, as a model converts traffic demand into a required capacity figure for a given area. The Erlang formula is used, requiring additional data such as peak hour ratios and distribution estimates. Basic space segment technical requirements are outlined (communications payload, transponder arrangements, etc), and further design studies involve such areas as space segment configuration, launcher and spacecraft studies, transmission planning, and earth segment configurations. Cost estimates of proposed design parameters will be performed, but options must be reduced to make construction feasible. Finally, a financial analysis will be carried out in order to calculate financial returns.
Estimation of traffic recovery time for different flow regimes on freeways.
DOT National Transportation Integrated Search
2008-06-01
This study attempts to estimate post-incident traffic recovery time along a freeway using Monte Carlo simulation techniques. It has been found that there is a linear relationship between post-incident traffic recovery time, and incident time and traf...
INTEGRATED SPEED ESTIMATION MODEL FOR MULTILANE EXPREESSWAYS
NASA Astrophysics Data System (ADS)
Hong, Sungjoon; Oguchi, Takashi
In this paper, an integrated speed-estimation model is developed based on empirical analyses for the basic sections of intercity multilane expressway un der the uncongested condition. This model enables a speed estimation for each lane at any site under arb itrary highway-alignment, traffic (traffic flow and truck percentage), and rainfall conditions. By combin ing this model and a lane-use model which estimates traffic distribution on the lanes by each vehicle type, it is also possible to es timate an average speed across all the lanes of one direction from a traffic demand by vehicle type under specific highway-alignment and rainfall conditions. This model is exp ected to be a tool for the evaluation of traffic performance for expressways when the performance me asure is travel speed, which is necessary for Performance-Oriented Highway Planning and Design. Regarding the highway-alignment condition, two new estimators, called effective horizo ntal curvature and effective vertical grade, are proposed in this paper which take into account the influence of upstream and downstream alignment conditions. They are applied to the speed-estimation model, and it shows increased accuracy of the estimation.
Padula, Amy M; Mortimer, Kathleen; Hubbard, Alan; Lurmann, Frederick; Jerrett, Michael; Tager, Ira B
2012-11-01
Traffic-related air pollution is recognized as an important contributor to health problems. Epidemiologic analyses suggest that prenatal exposure to traffic-related air pollutants may be associated with adverse birth outcomes; however, there is insufficient evidence to conclude that the relation is causal. The Study of Air Pollution, Genetics and Early Life Events comprises all births to women living in 4 counties in California's San Joaquin Valley during the years 2000-2006. The probability of low birth weight among full-term infants in the population was estimated using machine learning and targeted maximum likelihood estimation for each quartile of traffic exposure during pregnancy. If everyone lived near high-volume freeways (approximated as the fourth quartile of traffic density), the estimated probability of term low birth weight would be 2.27% (95% confidence interval: 2.16, 2.38) as compared with 2.02% (95% confidence interval: 1.90, 2.12) if everyone lived near smaller local roads (first quartile of traffic density). Assessment of potentially causal associations, in the absence of arbitrary model assumptions applied to the data, should result in relatively unbiased estimates. The current results support findings from previous studies that prenatal exposure to traffic-related air pollution may adversely affect birth weight among full-term infants.
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 ...
A Study on Urban Road Traffic Safety Based on Matter Element Analysis
Hu, Qizhou; Zhou, Zhuping; Sun, Xu
2014-01-01
This paper examines a new evaluation of urban road traffic safety based on a matter element analysis, avoiding the difficulties found in other traffic safety evaluations. The issue of urban road traffic safety has been investigated through the matter element analysis theory. The chief aim of the present work is to investigate the features of urban road traffic safety. Emphasis was placed on the construction of a criterion function by which traffic safety achieved a hierarchical system of objectives to be evaluated. The matter element analysis theory was used to create the comprehensive appraisal model of urban road traffic safety. The technique was used to employ a newly developed and versatile matter element analysis algorithm. The matter element matrix solves the uncertainty and incompatibility of the evaluated factors used to assess urban road traffic safety. The application results showed the superiority of the evaluation model and a didactic example was included to illustrate the computational procedure. PMID:25587267
DOT National Transportation Integrated Search
2016-05-31
We developed and implemented a traffic count program in Blacksburg, VA to estimate performance measures of bicycle and pedestrian traffic. We deployed and validated automated counters at 101 count sites; the count sites consisted of 4 permanent refer...
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...
Early estimate of motor vehicle traffic fatalities in 2009 : a brief statistical summary
DOT National Transportation Integrated Search
2010-03-01
statistical projection of traffic fatalities in 2009 shows that an estimated 33,963 people died in motor vehicle traffic crashes. This represents a decline of about 8.9 percent as compared to the 37,261 fatalities that occurred in 2008, as shown in T...
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 ...
Highway traffic estimation of improved precision using the derivative-free nonlinear Kalman Filter
NASA Astrophysics Data System (ADS)
Rigatos, Gerasimos; Siano, Pierluigi; Zervos, Nikolaos; Melkikh, Alexey
2015-12-01
The paper proves that the PDE dynamic model of the highway traffic is a differentially flat one and by applying spatial discretization its shows that the model's transformation into an equivalent linear canonical state-space form is possible. For the latter representation of the traffic's dynamics, state estimation is performed with the use of the Derivative-free nonlinear Kalman Filter. The proposed filter consists of the Kalman Filter recursion applied on the transformed state-space model of the highway traffic. Moreover, it makes use of an inverse transformation, based again on differential flatness theory which enables to obtain estimates of the state variables of the initial nonlinear PDE model. By avoiding approximate linearizations and the truncation of nonlinear terms from the PDE model of the traffic's dynamics the proposed filtering methods outperforms, in terms of accuracy, other nonlinear estimators such as the Extended Kalman Filter. The article's theoretical findings are confirmed through simulation experiments.
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
The use of uncalibrated roadside CCTV cameras to estimate mean traffic speed
DOT National Transportation Integrated Search
2001-12-01
In this report, we present a novel approach for estimating traffic speed using a sequence of images from an un-calibrated camera. We assert that exact calibration is not necessary to estimate speed. Instead, to estimate speed, we use: (1) geometric r...
Padula, Amy M.; Mortimer, Kathleen; Hubbard, Alan; Lurmann, Frederick; Jerrett, Michael; Tager, Ira B.
2012-01-01
Traffic-related air pollution is recognized as an important contributor to health problems. Epidemiologic analyses suggest that prenatal exposure to traffic-related air pollutants may be associated with adverse birth outcomes; however, there is insufficient evidence to conclude that the relation is causal. The Study of Air Pollution, Genetics and Early Life Events comprises all births to women living in 4 counties in California's San Joaquin Valley during the years 2000–2006. The probability of low birth weight among full-term infants in the population was estimated using machine learning and targeted maximum likelihood estimation for each quartile of traffic exposure during pregnancy. If everyone lived near high-volume freeways (approximated as the fourth quartile of traffic density), the estimated probability of term low birth weight would be 2.27% (95% confidence interval: 2.16, 2.38) as compared with 2.02% (95% confidence interval: 1.90, 2.12) if everyone lived near smaller local roads (first quartile of traffic density). Assessment of potentially causal associations, in the absence of arbitrary model assumptions applied to the data, should result in relatively unbiased estimates. The current results support findings from previous studies that prenatal exposure to traffic-related air pollution may adversely affect birth weight among full-term infants. PMID:23045474
DOT National Transportation Integrated Search
2009-06-01
A statistical projection of traffic fatalities for the first quarter of 2009 shows that an estimated 7,689 people died in motor vehicle traffic crashes. This represents a decline of about 9 percent as compared to the 8,451 fatalities that occurred in...
DOT National Transportation Integrated Search
2010-09-01
A statistical projection of traffic fatalities for the first half of : 2010 shows that an estimated 14,996 people died in motor : vehicle traffic crashes. This represents a decline of about 9.2 : percent as compared to the 16,509 fatalities that occu...
Torija, Antonio J; Ruiz, Diego P
2012-10-01
Road traffic has a heavy impact on the urban sound environment, constituting the main source of noise and widely dominating its spectral composition. In this context, our research investigates the use of recorded sound spectra as input data for the development of real-time short-term road traffic flow estimation models. For this, a series of models based on the use of Multilayer Perceptron Neural Networks, multiple linear regression, and the Fisher linear discriminant were implemented to estimate road traffic flow as well as to classify it according to the composition of heavy vehicles and motorcycles/mopeds. In view of the results, the use of the 50-400 Hz and 1-2.5 kHz frequency ranges as input variables in multilayer perceptron-based models successfully estimated urban road traffic flow with an average percentage of explained variance equal to 86%, while the classification of the urban road traffic flow gave an average success rate of 96.1%. Copyright © 2012 Elsevier B.V. All rights reserved.
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...
25 CFR Appendix A to Subpart C - IRR High Priority Project Scoring Matrix
Code of Federal Regulations, 2010 CFR
2010-04-01
...—IRR High Priority Project Scoring Matrix Score 10 5 3 1 0 Accident and fatality rate for candidate route 1 Severe X Moderate Minimal No accidents. Years since last IRR construction project completed... elements Addresses 1 element. 1 National Highway Traffic Safety Board standards. 2 Total funds requested...
Productivity losses from road traffic deaths in Turkey.
Naci, Huseyin; Baker, Timothy D
2008-03-01
The importance of road traffic injuries in Turkey is not generally appreciated, in part due to lack of knowledge of its economic burden and in part due to major underestimation in official statistics. The total years of potential life lost and potentially productive years of life lost from mortality were calculated in order to estimate the cost of productivity losses from road traffic deaths in Turkey. More years of potentially productive life are lost due to road traffic deaths than to respiratory tract illnesses or diabetes mellitus, two other serious health problems in Turkey. Road traffic deaths cost Turkey an estimated USD 2.6 billion every year in productivity losses alone, more than the World Bank estimate of the indirect costs from the 1999 Marmara earthquake (USD 1.2-2 billion), Turkey's worst earthquake since 1939 (World Bank Turkey Country Office, 1999). This study highlights the importance of accurate information in ameliorating the burden of road traffic safety in Turkey. Turkey has great opportunities to implement cost-effective interventions to reduce the economic burden of fatal and non-fatal road traffic injuries.
NASA Astrophysics Data System (ADS)
Batterman, Stuart; Cook, Richard; Justin, Thomas
2015-04-01
Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates.
Batterman, Stuart; Cook, Richard; Justin, Thomas
2015-01-01
Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates. PMID:25844042
NASA Astrophysics Data System (ADS)
Ryu, B. Y.; Jung, H. J.; Bae, S. H.; Choi, C. U.
2013-12-01
CO2 emissions on roads in urban centers substantially affect global warming. It is important to quantify CO2 emissions in terms of the link unit in order to reduce these emissions on the roads. Therefore, in this study, we utilized real-time traffic data and attempted to develop a methodology for estimating CO2 emissions per link unit. Because of the recent development of the vehicle-to-infrastructure (V2I) communication technology, data from probe vehicles (PVs) can be collected and speed per link unit can be calculated. Among the existing emission calculation methodologies, mesoscale modeling, which is a representative modeling measurement technique, requires speed and traffic data per link unit. As it is not feasible to install fixed detectors at every link for traffic data collection, in this study, we developed a model for traffic volume estimation by utilizing the number of PVs that can be additionally collected when the PV data are collected. Multiple linear regression and an artificial neural network (ANN) were used for estimating the traffic volume. The independent variables and input data for each model are the number of PVs, travel time index (TTI), the number of lanes, and time slots. The result from the traffic volume estimate model shows that the mean absolute percentage error (MAPE) of the ANN is 18.67%, thus proving that it is more effective. The ANN-based traffic volume estimation served as the basis for the calculation of emissions per link unit. The daily average emissions for Daejeon, where this study was based, were 2210.19 ton/day. By vehicle type, passenger cars accounted for 71.28% of the total emissions. By road, Gyeryongro emitted 125.48 ton/day, accounting for 5.68% of the total emission, the highest percentage of all roads. In terms of emissions per kilometer, Hanbatdaero had the highest emission volume, with 7.26 ton/day/km on average. This study proves that real-time traffic data allow an emissions estimate in terms of the link unit. Furthermore, an analysis of CO2 emissions can support traffic management to make decisions related to the reduction of carbon emissions.
DOT National Transportation Integrated Search
2009-10-15
In typical road traffic corridors, freeway systems are generally well-equipped with traffic surveillance systems such as vehicle detector (VD) and/or closed circuit television (CCTV) systems in order to gather timely traffic information for traffic c...
NASA Astrophysics Data System (ADS)
Palatella, Luigi; Trevisan, Anna; Rambaldi, Sandro
2013-08-01
Valuable information for estimating the traffic flow is obtained with current GPS technology by monitoring position and velocity of vehicles. In this paper, we present a proof of concept study that shows how the traffic state can be estimated using only partial and noisy data by assimilating them in a dynamical model. Our approach is based on a data assimilation algorithm, developed by the authors for chaotic geophysical models, designed to be equivalent but computationally much less demanding than the traditional extended Kalman filter. Here we show that the algorithm is even more efficient if the system is not chaotic and demonstrate by numerical experiments that an accurate reconstruction of the complete traffic state can be obtained at a very low computational cost by monitoring only a small percentage of vehicles.
MIMO channel estimation and evaluation for airborne traffic surveillance in cellular networks
NASA Astrophysics Data System (ADS)
Vahidi, Vahid; Saberinia, Ebrahim
2018-01-01
A channel estimation (CE) procedure based on compressed sensing is proposed to estimate the multiple-input multiple-output sparse channel for traffic data transmission from drones to ground stations. The proposed procedure consists of an offline phase and a real-time phase. In the offline phase, a pilot arrangement method, which considers the interblock and block mutual coherence simultaneously, is proposed. The real-time phase contains three steps. At the first step, it obtains the priori estimate of the channel by block orthogonal matching pursuit; afterward, it utilizes that estimated channel to calculate the linear minimum mean square error of the received pilots. Finally, the block compressive sampling matching pursuit utilizes the enhanced received pilots to estimate the channel more accurately. The performance of the CE procedure is evaluated by simulating the transmission of traffic data through the communication channel and evaluating its fidelity for car detection after demodulation. Simulation results indicate that the proposed CE technique enhances the performance of the car detection in a traffic image considerably.
Wyoming Low-Volume Roads Traffic Volume Estimation
DOT National Transportation Integrated Search
2015-10-01
Low-volume roads are excluded from regular traffic counts except on a need to know basis. But needs for traffic volume data on low-volume roads in road infrastructure management, safety, and air quality analysis have necessitated regular traffic volu...
National traffic speeds survey II: 2009 : traffic tech.
DOT National Transportation Integrated Search
2012-08-01
Vehicle speeds are a crucial factor in traffic safety. : NHTSA estimates that speeding is involved in approximately : 31% of fatal motor vehicle crashes, costing society : over $40 billion per year. : Since speeding is such a : pervasive traffic safe...
Traffic Light Detection Using Conic Section Geometry
NASA Astrophysics Data System (ADS)
Hosseinyalmdary, S.; Yilmaz, A.
2016-06-01
Traffic lights detection and their state recognition is a crucial task that autonomous vehicles must reliably fulfill. Despite scientific endeavors, it still is an open problem due to the variations of traffic lights and their perception in image form. Unlike previous studies, this paper investigates the use of inaccurate and publicly available GIS databases such as OpenStreetMap. In addition, we are the first to exploit conic section geometry to improve the shape cue of the traffic lights in images. Conic section also enables us to estimate the pose of the traffic lights with respect to the camera. Our approach can detect multiple traffic lights in the scene, it also is able to detect the traffic lights in the absence of prior knowledge, and detect the traffics lights as far as 70 meters. The proposed approach has been evaluated for different scenarios and the results show that the use of stereo cameras significantly improves the accuracy of the traffic lights detection and pose estimation.
Spatial correlation analysis of urban traffic state under a perspective of community detection
NASA Astrophysics Data System (ADS)
Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan
2018-05-01
Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.
GBD-2010 overestimates deaths from road injuries in OECD countries: new methods perform poorly.
Bhalla, Kavi; Harrison, James E
2015-10-01
We assessed the quality of Global Burden of Disease-2010 (GBD-2010) estimates of road injury deaths by comparing with government statistics for Organisation for Economic Co-operation and Development (OECD) countries that report to the International Road Traffic Accident Database (IRTAD). We obtained tabulated data for 25 OECD countries that report to IRTAD and also report vital registration (VR) data to WHO. We collated VR deaths corresponding to the GBD-2010 road injury definition and estimated 'traffic', 'non-traffic' and 'unspecified whether traffic or non-traffic' components. We estimated national road injury deaths by redistributing partially specified causes of death, as was done by GBD until this was replaced by more complex methods in GBD-2010. GBD-2010 estimates of road injury deaths exceeded IRTAD by 45% overall. IRTAD values fell below the GBD-2010 95% uncertainty interval in all but three countries. Mismatch of conceptual scope accounted for about 8% of this discrepancy, 5% was because GBD-2010 included cases other than road traffic and 3% because GBD-2010 (unlike IRTAD) includes deaths >30 days after injury. Pro rata distribution of partially specified causes in VR data gave estimates that were 18% higher than IRTAD but closer than GBD-2010 estimates for all but two countries. Cases in VR data specified as road injury gave estimates closer to IRTAD. GBD-2010 road injury mortality estimates are substantially higher than the road death toll in OECD countries. The discrepancy is not explained by wider scope of the GBD road injury construct nor by undercounting by IRTAD. GBD-2010 likely attributed substantially more deaths with partially specified causes to road injuries than is appropriate. © The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
Developing a stochastic traffic volume prediction model for public-private partnership projects
NASA Astrophysics Data System (ADS)
Phong, Nguyen Thanh; Likhitruangsilp, Veerasak; Onishi, Masamitsu
2017-11-01
Transportation projects require an enormous amount of capital investment resulting from their tremendous size, complexity, and risk. Due to the limitation of public finances, the private sector is invited to participate in transportation project development. The private sector can entirely or partially invest in transportation projects in the form of Public-Private Partnership (PPP) scheme, which has been an attractive option for several developing countries, including Vietnam. There are many factors affecting the success of PPP projects. The accurate prediction of traffic volume is considered one of the key success factors of PPP transportation projects. However, only few research works investigated how to predict traffic volume over a long period of time. Moreover, conventional traffic volume forecasting methods are usually based on deterministic models which predict a single value of traffic volume but do not consider risk and uncertainty. This knowledge gap makes it difficult for concessionaires to estimate PPP transportation project revenues accurately. The objective of this paper is to develop a probabilistic traffic volume prediction model. First, traffic volumes were estimated following the Geometric Brownian Motion (GBM) process. Monte Carlo technique is then applied to simulate different scenarios. The results show that this stochastic approach can systematically analyze variations in the traffic volume and yield more reliable estimates for PPP projects.
User-friendly traffic incident management (TIM) program benefit-cost estimation tool, Version 1.2
DOT National Transportation Integrated Search
2016-01-01
Traffic incidents contribute significantly to the deterioration of the level of service of both freeways and arterials. Traffic Incident Management (TIM) programs have been introduced worldwide with the aim of mitigating the impact of traffic inciden...
Occupant traffic estimation through structural vibration sensing
NASA Astrophysics Data System (ADS)
Pan, Shijia; Mirshekari, Mostafa; Zhang, Pei; Noh, Hae Young
2016-04-01
The number of people passing through different indoor areas is useful in various smart structure applications, including occupancy-based building energy/space management, marketing research, security, etc. Existing approaches to estimate occupant traffic include vision-, sound-, and radio-based (mobile) sensing methods, which have placement limitations (e.g., requirement of line-of-sight, quiet environment, carrying a device all the time). Such limitations make these direct sensing approaches difficult to deploy and maintain. An indirect approach using geophones to measure floor vibration induced by footsteps can be utilized. However, the main challenge lies in distinguishing multiple simultaneous walkers by developing features that can effectively represent the number of mixed signals and characterize the selected features under different traffic conditions. This paper presents a method to monitor multiple persons. Once the vibration signals are obtained, features are extracted to describe the overlapping vibration signals induced by multiple footsteps, which are used for occupancy traffic estimation. In particular, we focus on analysis of the efficiency and limitations of the four selected key features when used for estimating various traffic conditions. We characterize these features with signals collected from controlled impulse load tests as well as from multiple people walking through a real-world sensing area. In our experiments, the system achieves the mean estimation error of +/-0.2 people for different occupant traffic conditions (from one to four) using k-nearest neighbor classifier.
Estimation of average daily traffic on local roads in Kentucky.
DOT National Transportation Integrated Search
2016-07-01
Kentucky Transportation Cabinet (KYTC) officials use annual average daily traffic (AADT) to estimate intersection : performance across the state maintained highway system. KYTC currently collects AADTs for state maintained : roads but frequently lack...
Optimizing traffic counting procedures.
DOT National Transportation Integrated Search
1986-01-01
Estimates of annual average daily traffic volumes are important in the planning and operations of state highway departments. These estimates are used in the planning of new construction and improvement of existing facilities, and, in some cases, in t...
Air Traffic Demand Estimates for 1995
DOT National Transportation Integrated Search
1975-04-01
The forecasts provide a range of reasonable 1995 activity levels for analyzing and comparing cost and performance characteristics of future air traffic management system concept alternatives. High and low estimates of the various demand measures are ...
Thompson, Jacqueline Y; Akanbi, Moses A; Azuh, Dominic; Samuel, Victoria; Omoregbe, Nicholas; Ayo, Charles K
2016-01-01
Abstract Objective To estimate the burden of road traffic injuries and deaths for all road users and among different road user groups in Africa. Methods We searched MEDLINE, EMBASE, Global Health, Google Scholar, websites of African road safety agencies and organizations for registry- and population-based studies and reports on road traffic injury and death estimates in Africa, published between 1980 and 2015. Available data for all road users and by road user group were extracted and analysed. We conducted a random-effects meta-analysis and estimated pooled rates of road traffic injuries and deaths. Findings We identified 39 studies from 15 African countries. The estimated pooled rate for road traffic injury was 65.2 per 100 000 population (95% confidence interval, CI: 60.8–69.5) and the death rate was 16.6 per 100 000 population (95% CI: 15.2–18.0). Road traffic injury rates increased from 40.7 per 100 000 population in the 1990s to 92.9 per 100 000 population between 2010 and 2015, while death rates decreased from 19.9 per 100 000 population in the 1990s to 9.3 per 100 000 population between 2010 and 2015. The highest road traffic death rate was among motorized four-wheeler occupants at 5.9 per 100 000 population (95% CI: 4.4–7.4), closely followed by pedestrians at 3.4 per 100 000 population (95% CI: 2.5–4.2). Conclusion The burden of road traffic injury and death is high in Africa. Since registry-based reports underestimate the burden, a systematic collation of road traffic injury and death data is needed to determine the true burden. PMID:27429490
Hong, Kimyong; Lee, Kyoung-Mu; Jang, Soong-nang
2015-01-01
To estimate the incidence of traffic accidents and find related factors among the older population. We used the cross-sectional data from the Korean Community Health Survey (KCHS), which was conducted between 2008 and 2010 and completed by 680,202 adults aged 19 years or more. And we used individuals aged 60 years or above (n=210,914). The incidence of traffic accidents was estimated as number of traffic accidents experienced per thousand per year by a number of factors including age, sex, residential area, education, employment status, and diagnosis with chronic diseases. Multiple logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for each potential risk factor adjusted for the others. Incidence of traffic accidents was estimated as 11.74/1,000 per year for men, and 7.65/1,000 per year for women. It tended to decline as age increased among women; compared to the youngest old age group (60-64), the older old groups (70-74 and 80+) were at lower risk for traffic accidents. Depressive symptom was the strongest predictor for both men (OR=1.83, 95% CI=1.28-2.61) and women (1.70, 1.23-2.35). Risk of traffic accident was greater in employed men (1.76, 1.40-2.22) and women diagnosis with arthritis (1.36, 1.06-1.75). Given that the incidence of and factors associated with traffic accidents differ between men and women, preventive strategies, such as driver education and traffic safety counseling for older adults, should be modified in accordance with these differences. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Road Network State Estimation Using Random Forest Ensemble Learning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hou, Yi; Edara, Praveen; Chang, Yohan
Network-scale travel time prediction not only enables traffic management centers (TMC) to proactively implement traffic management strategies, but also allows travelers make informed decisions about route choices between various origins and destinations. In this paper, a random forest estimator was proposed to predict travel time in a network. The estimator was trained using two years of historical travel time data for a case study network in St. Louis, Missouri. Both temporal and spatial effects were considered in the modeling process. The random forest models predicted travel times accurately during both congested and uncongested traffic conditions. The computational times for themore » models were low, thus useful for real-time traffic management and traveler information applications.« less
Use of permanent traffic recorder data to develop factors for traffic and truck variations
DOT National Transportation Integrated Search
2002-10-01
This project entailed the development of the following four traffic volume adjustment factors from 1995 and 1996 permanent traffic recorder data: (1) A truck (axle) adjustment factor for single pneumatic tube counters; (2) A factor for estimating Des...
NASA Astrophysics Data System (ADS)
Davies, Rebecca; Speldewinde, Peter C.; Stewart, Barbara A.
2016-04-01
Off-road vehicle use is arguably one of the most environmentally damaging human activities undertaken on sandy beaches worldwide. Existing studies focused on areas of high traffic volumes have demonstrated significantly lower abundance, diversity and species richness of fauna in zones where traffic is concentrated. The impact of lower traffic volumes is unknown. This study aimed to investigate the impacts of relatively low-level vehicle traffic on sandy beach fauna by sampling invertebrate communities at eight beaches located in south-western Australia. We found that even low-level vehicle traffic negatively impacts the physical beach environment, and consequently, the ability of many species to survive in this habitat in the face of this disturbance. Compaction, rutting and displacement of the sand matrix were observed over a large area, resulting in significant decreases in species diversity and density, and measurable shifts in community structure on beaches that experienced off-road vehicle traffic. Communities at impact sites did not display seasonal recovery as traffic was not significantly different between seasons. Given a choice between either reducing traffic volumes, or excluding ORV traffic from beaches, our results suggest that the latter would be more appropriate when the retention of ecological integrity is the objective.
Mordukhovich, Irina; Beyea, Jan; Herring, Amy H; Hatch, Maureen; Stellman, Steven D; Teitelbaum, Susan L; Richardson, David B; Millikan, Robert C; Engel, Lawrence S; Shantakumar, Sumitra; Steck, Susan E; Neugut, Alfred I; Rossner, Pavel; Santella, Regina M; Gammon, Marilie D
2016-01-01
Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental pollutants, known human lung carcinogens, and potent mammary carcinogens in laboratory animals. However, the association between PAHs and breast cancer in women is unclear. Vehicular traffic is a major ambient source of PAH exposure. Our study aim was to evaluate the association between residential exposure to vehicular traffic and breast cancer incidence. Residential histories of 1,508 participants with breast cancer (case participants) and 1,556 particpants with no breast cancer (control participants) were assessed in a population-based investigation conducted in 1996-1997. Traffic exposure estimates of benzo[a]pyrene (B[a]P), as a proxy for traffic-related PAHs, for the years 1960-1995 were reconstructed using a model previously shown to generate estimates consistent with measured soil PAHs, PAH-DNA adducts, and CO readings. Associations between vehicular traffic exposure estimates and breast cancer incidence were evaluated using unconditional logistic regression. The odds ratio (95% CI) was modestly elevated by 1.44 (0.78, 2.68) for the association between breast cancer and long-term 1960-1990 vehicular traffic estimates in the top 5%, compared with below the median. The association with recent 1995 traffic exposure was elevated by 1.14 (0.80, 1.64) for the top 5%, compared with below the median, which was stronger among women with low fruit/vegetable intake [1.46 (0.89, 2.40)], but not among those with high fruit/vegetable intake [0.92 (0.53, 1.60)]. Among the subset of women with information regarding traffic exposure and tumor hormone receptor subtype, the traffic-breast cancer association was higher for those with estrogen/progesterone-negative tumors [1.67 (0.91, 3.05) relative to control participants], but lower among all other tumor subtypes [0.80 (0.50, 1.27) compared with control participants]. In our population-based study, we observed positive associations between vehicular traffic-related B[a]P exposure and breast cancer incidence among women with comparatively high long-term traffic B[a]P exposures, although effect estimates were imprecise. Mordukhovich I, Beyea J, Herring AH, Hatch M, Stellman SD, Teitelbaum SL, Richardson DB, Millikan RC, Engel LS, Shantakumar S, Steck SE, Neugut AI, Rossner P Jr., Santella RM, Gammon MD. 2016. Vehicular traffic-related polycyclic aromatic hydrocarbon exposure and breast cancer incidence: the Long Island Breast Cancer Study Project (LIBCSP). Environ Health Perspect 124:30-38; http://dx.doi.org/10.1289/ehp.1307736.
1990 traffic fatalities : semiannual report
DOT National Transportation Integrated Search
1990-11-01
Author's abstract: This report contains preliminary estimates of traffic fatalities and fatal accidents for the first six months of 1990. Trend data are presented for both the long and short term. The national estimates of fatalities are quite extens...
Lipfert, Frederick W; Wyzga, Ronald E; Baty, Jack D; Miller, J Philip
2009-04-01
For this paper, we considered relationships between mortality, vehicular traffic density, and ambient levels of 12 hazardous air pollutants, elemental carbon (EC), oxides of nitrogen (NOx), sulfur dioxide (SO2), and sulfate (SO4(2-)). These pollutant species were selected as markers for specific types of emission sources, including vehicular traffic, coal combustion, smelters, and metal-working industries. Pollutant exposures were estimated using emissions inventories and atmospheric dispersion models. We analyzed associations between county ambient levels of these pollutants and survival patterns among approximately 70,000 U.S. male veterans by mortality period (1976-2001 and subsets), type of exposure model, and traffic density level. We found significant associations between all-cause mortality and traffic-related air quality indicators and with traffic density per se, with stronger associations for benzene, formaldehyde, diesel particulate, NOx, and EC. The maximum effect on mortality for all cohort subjects during the 26-yr follow-up period is approximately 10%, but most of the pollution-related deaths in this cohort occurred in the higher-traffic counties, where excess risks approach 20%. However, mortality associations with diesel particulates are similar in high- and low-traffic counties. Sensitivity analyses show risks decreasing slightly over time and minor differences between linear and logarithmic exposure models. Two-pollutant models show stronger risks associated with specific traffic-related pollutants than with traffic density per se, although traffic density retains statistical significance in most cases. We conclude that tailpipe emissions of both gases and particles are among the most significant and robust predictors of mortality in this cohort and that most of those associations have weakened over time. However, we have not evaluated possible contributions from road dust or traffic noise. Stratification by traffic density level suggests the presence of response thresholds, especially for gaseous pollutants. Because of their wider distributions of estimated exposures, risk estimates based on emissions and atmospheric dispersion models tend to be more precise than those based on local ambient measurements.
Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng
2017-04-10
This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.
Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng
2017-01-01
This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks. PMID:28394270
DOT National Transportation Integrated Search
2017-12-01
In designing an effective traffic management plan for non-recurrent congestion, it is critical for responsible highway agencies to have some vital information, such as estimated incident duration, resulting traffic queues, and the expected delays. Ov...
Samuel, Jonathan C; Sankhulani, Edward; Qureshi, Javeria S; Baloyi, Paul; Thupi, Charles; Lee, Clara N; Miller, William C; Cairns, Bruce A; Charles, Anthony G
2012-01-01
Road traffic injuries are a major cause of preventable death in sub-Saharan Africa. Accurate epidemiologic data are scarce and under-reporting from primary data sources is common. Our objectives were to estimate the incidence of road traffic deaths in Malawi using capture-recapture statistical analysis and determine what future efforts will best improve upon this estimate. Our capture-recapture model combined primary data from both police and hospital-based registries over a one year period (July 2008 to June 2009). The mortality incidences from the primary data sources were 0.075 and 0.051 deaths/1000 person-years, respectively. Using capture-recapture analysis, the combined incidence of road traffic deaths ranged 0.192-0.209 deaths/1000 person-years. Additionally, police data were more likely to include victims who were male, drivers or pedestrians, and victims from incidents with greater than one vehicle involved. We concluded that capture-recapture analysis is a good tool to estimate the incidence of road traffic deaths, and that capture-recapture analysis overcomes limitations of incomplete data sources. The World Health Organization estimated incidence of road traffic deaths for Malawi utilizing a binomial regression model and survey data and found a similar estimate despite strikingly different methods, suggesting both approaches are valid. Further research should seek to improve capture-recapture data through utilization of more than two data sources and improving accuracy of matches by minimizing missing data, application of geographic information systems, and use of names and civil registration numbers if available.
Samuel, Jonathan C.; Sankhulani, Edward; Qureshi, Javeria S.; Baloyi, Paul; Thupi, Charles; Lee, Clara N.; Miller, William C.; Cairns, Bruce A.; Charles, Anthony G.
2012-01-01
Road traffic injuries are a major cause of preventable death in sub-Saharan Africa. Accurate epidemiologic data are scarce and under-reporting from primary data sources is common. Our objectives were to estimate the incidence of road traffic deaths in Malawi using capture-recapture statistical analysis and determine what future efforts will best improve upon this estimate. Our capture-recapture model combined primary data from both police and hospital-based registries over a one year period (July 2008 to June 2009). The mortality incidences from the primary data sources were 0.075 and 0.051 deaths/1000 person-years, respectively. Using capture-recapture analysis, the combined incidence of road traffic deaths ranged 0.192–0.209 deaths/1000 person-years. Additionally, police data were more likely to include victims who were male, drivers or pedestrians, and victims from incidents with greater than one vehicle involved. We concluded that capture-recapture analysis is a good tool to estimate the incidence of road traffic deaths, and that capture-recapture analysis overcomes limitations of incomplete data sources. The World Health Organization estimated incidence of road traffic deaths for Malawi utilizing a binomial regression model and survey data and found a similar estimate despite strikingly different methods, suggesting both approaches are valid. Further research should seek to improve capture-recapture data through utilization of more than two data sources and improving accuracy of matches by minimizing missing data, application of geographic information systems, and use of names and civil registration numbers if available. PMID:22355338
Jung, Sungwoon; Kim, Jounghwa; Kim, Jeongsoo; Hong, Dahee; Park, Dongjoo
2017-04-01
The objective of this study is to estimate the vehicle kilometer traveled (VKT) and on-road emissions using the traffic volume in urban. We estimated two VKT; one is based on registered vehicles and the other is based on traffic volumes. VKT for registered vehicles was 2.11 times greater than that of the applied traffic volumes because each VKT estimation method is different. Therefore, we had to define the inner VKT is moved VKT inner in urban to compare two values. Also, we focused on freight modes because these are discharged much air pollutant emissions. From analysis results, we found middle and large trucks registered in other regions traveled to target city in order to carry freight, target city has included many industrial and logistics areas. Freight is transferred through the harbors, large logistics centers, or via locations before being moved to the final destination. During this process, most freight is moved by middle and large trucks, and trailers rather than small trucks for freight import and export. Therefore, these trucks from other areas are inflow more than registered vehicles. Most emissions from diesel trucks had been overestimated in comparison to VKT from applied traffic volumes in target city. From these findings, VKT is essential based on traffic volume and travel speed on road links in order to estimate accurately the emissions of diesel trucks in target city. Our findings support the estimation of the effect of on-road emissions on urban air quality in Korea. Copyright © 2016. Published by Elsevier B.V.
Estimation of Traffic Variables Using Point Processing Techniques
DOT National Transportation Integrated Search
1978-05-01
An alternative approach to estimating aggregate traffic variables on freeways--spatial mean velocity and density--is presented. Vehicle arrival times at a given location on a roadway, typically a presence detector, are regarded as a point or counting...
Collective Human Mobility Pattern from Taxi Trips in Urban Area
Peng, Chengbin; Jin, Xiaogang; Wong, Ka-Chun; Shi, Meixia; Liò, Pietro
2012-01-01
We analyze the passengers' traffic pattern for 1.58 million taxi trips of Shanghai, China. By employing the non-negative matrix factorization and optimization methods, we find that, people travel on workdays mainly for three purposes: commuting between home and workplace, traveling from workplace to workplace, and others such as leisure activities. Therefore, traffic flow in one area or between any pair of locations can be approximated by a linear combination of three basis flows, corresponding to the three purposes respectively. We name the coefficients in the linear combination as traffic powers, each of which indicates the strength of each basis flow. The traffic powers on different days are typically different even for the same location, due to the uncertainty of the human motion. Therefore, we provide a probability distribution function for the relative deviation of the traffic power. This distribution function is in terms of a series of functions for normalized binomial distributions. It can be well explained by statistical theories and is verified by empirical data. These findings are applicable in predicting the road traffic, tracing the traffic pattern and diagnosing the traffic related abnormal events. These results can also be used to infer land uses of urban area quite parsimoniously. PMID:22529917
Massively parallel processor networks with optical express channels
Deri, R.J.; Brooks, E.D. III; Haigh, R.E.; DeGroot, A.J.
1999-08-24
An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination. 3 figs.
Massively parallel processor networks with optical express channels
Deri, Robert J.; Brooks, III, Eugene D.; Haigh, Ronald E.; DeGroot, Anthony J.
1999-01-01
An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination.
NASA Astrophysics Data System (ADS)
Balouchestani, Mohammadreza
2017-05-01
Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.
14 CFR 271.5 - Carrier revenues.
Code of Federal Regulations, 2014 CFR
2014-01-01
... one-line passengers; and (2) The traffic (including both local and beyond traffic) projected to flow..., Department estimates, and on traffic levels in the market at issue when such data are available. (b) The... proposed fare with the fare charged in other city-pair markets of similar distances and traffic densities...
14 CFR 271.5 - Carrier revenues.
Code of Federal Regulations, 2013 CFR
2013-01-01
... one-line passengers; and (2) The traffic (including both local and beyond traffic) projected to flow..., Department estimates, and on traffic levels in the market at issue when such data are available. (b) The... proposed fare with the fare charged in other city-pair markets of similar distances and traffic densities...
14 CFR 271.5 - Carrier revenues.
Code of Federal Regulations, 2011 CFR
2011-01-01
... one-line passengers; and (2) The traffic (including both local and beyond traffic) projected to flow..., Department estimates, and on traffic levels in the market at issue when such data are available. (b) The... proposed fare with the fare charged in other city-pair markets of similar distances and traffic densities...
14 CFR 271.5 - Carrier revenues.
Code of Federal Regulations, 2012 CFR
2012-01-01
... one-line passengers; and (2) The traffic (including both local and beyond traffic) projected to flow..., Department estimates, and on traffic levels in the market at issue when such data are available. (b) The... proposed fare with the fare charged in other city-pair markets of similar distances and traffic densities...
GIS Tools to Estimate Average Annual Daily Traffic
DOT National Transportation Integrated Search
2012-06-01
This project presents five tools that were created for a geographical information system to estimate Annual Average Daily : Traffic using linear regression. Three of the tools can be used to prepare spatial data for linear regression. One tool can be...
Traffic safety facts 1999 : state alcohol estimates
DOT National Transportation Integrated Search
2000-01-01
The data in this traffic safety fact sheet provide estimates of alcohol involvement in fatal crashes for the United States and individually for the 50 states, the District of Columbia, and Puerto Rico (not included in the national totals). These esti...
Traffic safety facts 1994 : state alcohol estimates
DOT National Transportation Integrated Search
1995-01-01
Nationwide in 1994, alcohol was involved in 40.8 percent of the traffic fatalities (8.6 percent low alcohol and 32.2 percent high alcohol), translating to 16,589 alcohol-related fatalities. These tables provide estimates of alcohol involvement in fat...
Traffic safety facts 1995 : state alcohol estimates
DOT National Transportation Integrated Search
1996-01-01
Nationwide in 1995, alcohol was involved in 41.3 percent of the traffic fatalities (8.9 percent low alcohol and 32.5 percent high alcohol), translating to 17,274 alcohol-related fatalities. These tables provide estimates of alcohol involvement in fat...
Sources of error in estimating truck traffic from automatic vehicle classification data
DOT National Transportation Integrated Search
1998-10-01
Truck annual average daily traffic estimation errors resulting from sample classification counts are computed in this paper under two scenarios. One scenario investigates an improper factoring procedure that may be used by highway agencies. The study...
Model Development for Risk Assessment of Driving on Freeway under Rainy Weather Conditions
Cai, Xiaonan; Wang, Chen; Chen, Shengdi; Lu, Jian
2016-01-01
Rainy weather conditions could result in significantly negative impacts on driving on freeways. However, due to lack of enough historical data and monitoring facilities, many regions are not able to establish reliable risk assessment models to identify such impacts. Given the situation, this paper provides an alternative solution where the procedure of risk assessment is developed based on drivers’ subjective questionnaire and its performance is validated by using actual crash data. First, an ordered logit model was developed, based on questionnaire data collected from Freeway G15 in China, to estimate the relationship between drivers’ perceived risk and factors, including vehicle type, rain intensity, traffic volume, and location. Then, weighted driving risk for different conditions was obtained by the model, and further divided into four levels of early warning (specified by colors) using a rank order cluster analysis. After that, a risk matrix was established to determine which warning color should be disseminated to drivers, given a specific condition. Finally, to validate the proposed procedure, actual crash data from Freeway G15 were compared with the safety prediction based on the risk matrix. The results show that the risk matrix obtained in the study is able to predict driving risk consistent with actual safety implications, under rainy weather conditions. PMID:26894434
NASA Astrophysics Data System (ADS)
Skene, Katherine J.; Gent, Janneane F.; McKay, Lisa A.; Belanger, Kathleen; Leaderer, Brian P.; Holford, Theodore R.
2010-12-01
An integrated exposure model was developed that estimates nitrogen dioxide (NO 2) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO 2 taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO 2 measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO 2 levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.
Trajectory Planning by Preserving Flexibility: Metrics and Analysis
NASA Technical Reports Server (NTRS)
Idris, Husni R.; El-Wakil, Tarek; Wing, David J.
2008-01-01
In order to support traffic management functions, such as mitigating traffic complexity, ground and airborne systems may benefit from preserving or optimizing trajectory flexibility. To help support this hypothesis trajectory flexibility metrics have been defined in previous work to represent the trajectory robustness and adaptability to the risk of violating safety and traffic management constraints. In this paper these metrics are instantiated in the case of planning a trajectory with the heading degree of freedom. A metric estimation method is presented based on simplifying assumptions, namely discrete time and heading maneuvers. A case is analyzed to demonstrate the estimation method and its use in trajectory planning in a situation involving meeting a time constraint and avoiding loss of separation with nearby traffic. The case involves comparing path-stretch trajectories, in terms of adaptability and robustness along each, deduced from a map of estimated flexibility metrics over the solution space. The case demonstrated anecdotally that preserving flexibility may result in enhancing certain factors that contribute to traffic complexity, namely reducing proximity and confrontation.
Freeway travel time estimation using existing fixed traffic sensors : phase 2.
DOT National Transportation Integrated Search
2015-03-01
Travel time, one of the most important freeway performance metrics, can be easily estimated using the : data collected from fixed traffic sensors, avoiding the need to install additional travel time data collectors. : This project is aimed at fully u...
State traffic volume systems council estimation process.
DOT National Transportation Integrated Search
2004-10-01
The Kentucky Transportation Cabinet has an immense traffic data collection program that is an essential source for many other programs. The Division of Planning processes traffic volume counts annually. These counts are maintained in the Counts Datab...
Cho, Nahye; Son, Serin
2018-01-01
The purpose of this study is to analyze how the spatiotemporal characteristics of traffic accidents involving the elderly population in Seoul are changing by time period. We applied kernel density estimation and hotspot analyses to analyze the spatial characteristics of elderly people’s traffic accidents, and the space-time cube, emerging hotspot, and space-time kernel density estimation analyses to analyze the spatiotemporal characteristics. In addition, we analyzed elderly people’s traffic accidents by dividing cases into those in which the drivers were elderly people and those in which elderly people were victims of traffic accidents, and used the traffic accidents data in Seoul for 2013 for analysis. The main findings were as follows: (1) the hotspots for elderly people’s traffic accidents differed according to whether they were drivers or victims. (2) The hourly analysis showed that the hotspots for elderly drivers’ traffic accidents are in specific areas north of the Han River during the period from morning to afternoon, whereas the hotspots for elderly victims are distributed over a wide area from daytime to evening. (3) Monthly analysis showed that the hotspots are weak during winter and summer, whereas they are strong in the hiking and climbing areas in Seoul during spring and fall. Further, elderly victims’ hotspots are more sporadic than elderly drivers’ hotspots. (4) The analysis for the entire period of 2013 indicates that traffic accidents involving elderly people are increasing in specific areas on the north side of the Han River. We expect the results of this study to aid in reducing the number of traffic accidents involving elderly people in the future. PMID:29768453
Kang, Youngok; Cho, Nahye; Son, Serin
2018-01-01
The purpose of this study is to analyze how the spatiotemporal characteristics of traffic accidents involving the elderly population in Seoul are changing by time period. We applied kernel density estimation and hotspot analyses to analyze the spatial characteristics of elderly people's traffic accidents, and the space-time cube, emerging hotspot, and space-time kernel density estimation analyses to analyze the spatiotemporal characteristics. In addition, we analyzed elderly people's traffic accidents by dividing cases into those in which the drivers were elderly people and those in which elderly people were victims of traffic accidents, and used the traffic accidents data in Seoul for 2013 for analysis. The main findings were as follows: (1) the hotspots for elderly people's traffic accidents differed according to whether they were drivers or victims. (2) The hourly analysis showed that the hotspots for elderly drivers' traffic accidents are in specific areas north of the Han River during the period from morning to afternoon, whereas the hotspots for elderly victims are distributed over a wide area from daytime to evening. (3) Monthly analysis showed that the hotspots are weak during winter and summer, whereas they are strong in the hiking and climbing areas in Seoul during spring and fall. Further, elderly victims' hotspots are more sporadic than elderly drivers' hotspots. (4) The analysis for the entire period of 2013 indicates that traffic accidents involving elderly people are increasing in specific areas on the north side of the Han River. We expect the results of this study to aid in reducing the number of traffic accidents involving elderly people in the future.
Quaassdorff, Christina; Borge, Rafael; Pérez, Javier; Lumbreras, Julio; de la Paz, David; de Andrés, Juan Manuel
2016-10-01
This paper presents the evaluation of emissions from vehicle operations in a domain of 300m×300m covering a complex urban roundabout with high traffic density in Madrid. Micro-level simulation was successfully applied to estimate the emissions on a scale of meters. Two programs were used: i) VISSIM to simulate the traffic on the square and to compute velocity-time profiles; and ii) VERSIT+micro through ENVIVER that uses VISSIM outputs to compute the related emissions at vehicle level. Data collection was achieved by a measurement campaign obtaining empirical data of vehicle flows and traffic intensities. Twelve simulations of different traffic situations (scenarios) were conducted, representing different hours from several days in a week and the corresponding NOX and PM10 emissions were estimated. The results show a general reduction on average speeds for higher intensities due to braking-acceleration patterns that contribute to increase the average emission factor and, therefore, the total emissions in the domain, especially on weekdays. The emissions are clearly related to traffic volume, although maximum emission scenario does not correspond to the highest traffic intensity due to congestion and variations in fleet composition throughout the day. These results evidence the potential that local measures aimed at alleviating congestion may have in urban areas to reduce emissions. In general, scenario-averaged emission factors estimated with the VISSIM-VERSIT+micro modelling system fitted well those from the average-speed model COPERT, used as a preliminary validation of the results. The largest deviations between these two models occur in those scenarios with more congestion. The design and resolution of the microscale modelling system allow to reflect the impact of actual traffic conditions on driving patterns and related emissions, making it useful for the design of mitigation measures for specific traffic hot-spots. Copyright © 2016 Elsevier B.V. All rights reserved.
Evidence of Long Range Dependence and Self-similarity in Urban Traffic Systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thakur, Gautam S; Helmy, Ahmed; Hui, Pan
2015-01-01
Transportation simulation technologies should accurately model traffic demand, distribution, and assignment parame- ters for urban environment simulation. These three param- eters significantly impact transportation engineering bench- mark process, are also critical in realizing realistic traffic modeling situations. In this paper, we model and charac- terize traffic density distribution of thousands of locations around the world. The traffic densities are generated from millions of images collected over several years and processed using computer vision techniques. The resulting traffic den- sity distribution time series are then analyzed. It is found using the goodness-of-fit test that the traffic density dis- tributions follows heavy-tailmore » models such as Log-gamma, Log-logistic, and Weibull in over 90% of analyzed locations. Moreover, a heavy-tail gives rise to long-range dependence and self-similarity, which we studied by estimating the Hurst exponent (H). Our analysis based on seven different Hurst estimators strongly indicate that the traffic distribution pat- terns are stochastically self-similar (0.5 H 1.0). We believe this is an important finding that will influence the design and development of the next generation traffic simu- lation techniques and also aid in accurately modeling traffic engineering of urban systems. In addition, it shall provide a much needed input for the development of smart cities.« less
Concept for a Satellite-Based Advanced Air Traffic Management System : Volume 7. System Cost.
DOT National Transportation Integrated Search
1973-02-01
The volume presents estimates of the federal government and user costs for the Satellite-Based Advanced Air Traffic Management System and the supporting rationale. The system configuration is that presented in volumes II and III. The cost estimates a...
MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems
2007-05-03
34Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Porne ", Parameter estimation for 3-parameter log-logistic distribu- tion...section V we physical security, air traffic control, traffic monitoring, andvidefaconu s cribedy. video surveillance, industrial automation etc. Each
DOT National Transportation Integrated Search
1997-01-01
The success of Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) depends on the availability and dissemination of timely and accurate estimates of current and emerging traffic network conditions. Real-time Dy...
Application of dynamic traffic assignment to advanced managed lane modeling.
DOT National Transportation Integrated Search
2013-11-01
In this study, a demand estimation framework is developed for assessing the managed lane (ML) : strategies by utilizing dynamic traffic assignment (DTA) modeling, instead of the traditional : approaches that are based on the static traffic assignment...
Data preprocessing for a vehicle-based localization system used in road traffic applications
NASA Astrophysics Data System (ADS)
Patelczyk, Timo; Löffler, Andreas; Biebl, Erwin
2016-09-01
This paper presents a fixed-point implementation of the preprocessing using a field programmable gate array (FPGA), which is required for a multipath joint angle and delay estimation (JADE) used in road traffic applications. This paper lays the foundation for many model-based parameter estimation methods. Here, a simulation of a vehicle-based localization system application for protecting vulnerable road users, which were equipped with appropriate transponders, is considered. For such safety critical applications, the robustness and real-time capability of the localization is particularly important. Additionally, a motivation to use a fixed-point implementation for the data preprocessing is a limited computing power of the head unit of a vehicle. This study aims to process the raw data provided by the localization system used in this paper. The data preprocessing applied includes a wideband calibration of the physical localization system, separation of relevant information from the received sampled signal, and preparation of the incoming data via further processing. Further, a channel matrix estimation was implemented to complete the data preprocessing, which contains information on channel parameters, e.g., the positions of the objects to be located. In the presented case of a vehicle-based localization system application we assume an urban environment, in which multipath propagation occurs. Since most methods for localization are based on uncorrelated signals, this fact must be addressed. Hence, a decorrelation of incoming data stream in terms of a further localization is required. This decorrelation was accomplished by considering several snapshots in different time slots. As a final aspect of the use of fixed-point arithmetic, quantization errors are considered. In addition, the resources and runtime of the presented implementation are discussed; these factors are strongly linked to a practical implementation.
Curve Estimation of Number of People Killed in Traffic Accidents in Turkey
NASA Astrophysics Data System (ADS)
Berkhan Akalin, Kadir; Karacasu, Murat; Altin, Arzu Yavuz; Ergül, Bariş
2016-10-01
One or more than one vehicle in motion on the highway involving death, injury and loss events which have resulted are called accidents. As a result of increasing population and traffic density, traffic accidents continue to increase and this leads to both human losses and harm to the economy. In addition, also leads to social problems. As a result of increasing population and traffic density, traffic accidents continue to increase and this leads to both human losses and harm to the economy. In addition to this, it also leads to social problems. As a result of traffic accidents, millions of people die year by year. A great majority of these accidents occur in developing countries. One of the most important tasks of transportation engineers is to reduce traffic accidents by creating a specific system. For that reason, statistical information about traffic accidents which occur in the past years should be organized by versed people. Factors affecting the traffic accidents are analyzed in various ways. In this study, modelling the number of people killed in traffic accidents in Turkey is determined. The dead people were modelled using curve fitting method with the number of people killed in traffic accidents in Turkey dataset between 1990 and 2014. It was also predicted the number of dead people by using various models for the future. It is decided that linear model is suitable for the estimates.
Quantifying incident-induced travel delays on freeways using traffic sensor data
DOT National Transportation Integrated Search
2008-02-01
Traffic congestion is a major operational problem for freeways in Washington State. Recent studies have estimated that more than 50% of freeway congestion is caused by traffic incidents. To help the Washington State Department of Transportation (WSDO...
Quantifying incident-induced travel delays on freeways using traffic sensor data
DOT National Transportation Integrated Search
2008-05-01
Traffic congestion is a major operational problem for freeways in Washington State. Recent studies have estimated that more than 50 percent of freeway congestion is caused by traffic incidents. To help the Washington State Department of Transportatio...
Cubí-Mollá, Patricia; Peña-Longobardo, Luz María; Casal, Bruno; Rivera, Berta; Oliva-Moreno, Juan
2015-09-01
To estimate the years of potential life lost, years of potential productive life lost and the labor productivity losses attributable to premature deaths due to traffic injuries between 2002 and 2012 in Spain. Several statistical sources were combined (Spanish Registry of Deaths, Labor Force Survey and Wage Structure Survey) to develop a simulation model based on the human capital approach. This model allowed us to estimate the loss of labor productivity caused by premature deaths following traffic injuries from 2002 to 2012. In addition, mortality tables with life expectancy estimates were used to compute years of potential life lost and years of potential productive life lost. The estimated loss of labour productivity caused by fatal traffic injuries between 2002 and 2012 in Spain amounted to 9,521 million euros (baseline year 2012). The aggregate number of years of potential life lost in the period amounted to 1,433,103, whereas the years of potential productive life lost amounted to 875,729. Throughout the period analyzed, labor productivity losses and years of life lost diminished substantially. Labor productivity losses due to fatal traffic injuries decreased throughout the period analyzed. Nevertheless, the cumulative loss was alarmingly high. Estimation of the economic impact of health problems can complement conventional indicators of distinct dimensions and be used to support public policy making. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.
PM10 source apportionment in Milan (Italy) using time-resolved data.
Bernardoni, Vera; Vecchi, Roberta; Valli, Gianluigi; Piazzalunga, Andrea; Fermo, Paola
2011-10-15
In this work Positive Matrix Factorization (PMF) was applied to 4-hour resolved PM10 data collected in Milan (Italy) during summer and winter 2006. PM10 characterisation included elements (Mg-Pb), main inorganic ions (NH(4)(+), NO(3)(-), SO(4)(2-)), levoglucosan and its isomers (mannosan and galactosan), and organic and elemental carbon (OC and EC). PMF resolved seven factors that were assigned to construction works, re-suspended dust, secondary sulphate, traffic, industry, secondary nitrate, and wood burning. Multi Linear Regression was applied to obtain the PM10 source apportionment. The 4-hour temporal resolution allowed the estimation of the factor contributions during peculiar episodes, which would have not been detected with the traditional 24-hour sampling strategy. Copyright © 2011 Elsevier B.V. All rights reserved.
Effect of geocoding errors on traffic-related air pollutant exposure and concentration estimates
Exposure to traffic-related air pollutants is highest very near roads, and thus exposure estimates are sensitive to positional errors. This study evaluates positional and PM2.5 concentration errors that result from the use of automated geocoding methods and from linearized approx...
NASA Astrophysics Data System (ADS)
Chen, Jingxu; Li, Zhibin; Jiang, Hang; Zhu, Senlai; Wang, Wei
2017-02-01
In recent years, many bicycle lanes on urban streets are replaced with vehicle parking places. Spaces for bicycle riding are reduced, resulting in changes in bicycle and vehicle operational features. The objective of this study is to estimate the impacts of on-street parking on heterogeneous traffic operation on urban streets. A cellular automaton (CA) model is developed and calibrated to simulate bicycle lane-changing on streets with on-street parking. Two types of street segments with different bicycle lane width are considered. From the simulation, two types of conflicts between bicycles and vehicles are identified which are frictional conflicts and blocking conflicts. Factors affecting the frequency of conflicts are also identified. Based on the results, vehicle delay is estimated for various traffic situations considering the range of occupancy levels for on-street parking. Later, a numerical network example is analyzed to estimate the network impact of on-street parking on traffic assignment and operation. Findings of the study are helpful to policies and design regarding on-street vehicle parking to improve the efficiency of traffic operations.
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…
An important factor in evaluating health risk of near-road air pollution is to accurately estimate the traffic-related vehicle emission of air pollutants. Inclusion of traffic parameters such as road length/area, distance to roads, and traffic volume/intensity into models such as...
NASA Astrophysics Data System (ADS)
Gianini, M. F. D.; Fischer, A.; Gehrig, R.; Ulrich, A.; Wichser, A.; Piot, C.; Besombes, J.-L.; Hueglin, C.
2012-07-01
PM10 speciation data from various sites in Switzerland for two time periods (January 1998-March 1999 and August 2008-July 2009) have been analysed for major sources by receptor modelling using Positive Matrix Factorisation (PMF). For the 2008/2009 period, it was found that secondary aerosols (sulphate- and nitrate-rich secondary aerosols, SSA and NSA) are the most abundant components of PM10 at sites north of the Alps. Road traffic and wood combustion were found to be the largest sources of PM10 at these sites. Except at the urban roadside site where road traffic is dominating (40% of PM10 -- including road salt), the annual average contribution of these two sources is of similar importance (17% and 14% of PM10, respectively). At a rural site south of the Alps wood combustion and road traffic contributions to PM10 were higher (31% and 24%, respectively), and the fraction of secondary aerosols lower (29%) than at similar site types north of the Alps. Comparison of PMF analyses for the two time periods (1998/1999 and 2008/2009) revealed decreasing average contributions of road traffic and SSA to PM10 at all sites. This indicates that the measures that were implemented in Switzerland and in neighbouring countries to reduce emissions of sulphur dioxide and PM10 from road traffic were successful. On the other hand, contributions of wood combustion did not change during this ten year period, and the contribution of nitrate-rich secondary aerosols has even increased. It is shown that PMF can be a helpful tool for the assessment of long-term changes of source contributions to ambient particulate matter.
Some Considerations on the Problem of Non-Steady State Traffic Flow Optimization
DOT National Transportation Integrated Search
2007-01-01
Poor traffic signal timing accounts for an estimated 10 percent of all traffic delay about 300 million vehicle-hours on major roadways alone. Americans agree that this is a problem: one U.S. Department of Transportation (DOT) survey found tha...
Economic development, mobility and traffic accidents in Algeria.
Bougueroua, M; Carnis, L
2016-07-01
The aim of this contribution is to estimate the impact of road economic conditions and mobility on traffic accidents for the case of Algeria. Using the cointegration approach and vector error correction model (VECM), we will examine simultaneously short term and long-term impacts between the number of traffic accidents, fuel consumption and gross domestic product (GDP) per capital, over the period 1970-2013. The main results of the estimation show that the number of traffic accidents in Algeria is positively influenced by the GDP per capita in the short and long term. It implies that a higher economic development worsens the road safety situation. However, the new traffic rules adopted in 2009 have an impact on the forecast trend of traffic accidents, meaning efficient public policy could improve the situation. This result calls for a strong political commitment with effective countermeasures for avoiding the further deterioration of road safety record in Algeria. Copyright © 2016 Elsevier Ltd. All rights reserved.
Estimating the harms and costs of cannabis-attributable collisions in the Canadian provinces.
Wettlaufer, Ashley; Florica, Roxana O; Asbridge, Mark; Beirness, Douglas; Brubacher, Jeffrey; Callaghan, Russell; Fischer, Benedikt; Gmel, Gerrit; Imtiaz, Sameer; Mann, Robert E; McKiernan, Anna; Rehm, Jürgen
2017-04-01
In 2012, 10% of Canadians used cannabis and just under half of those who use cannabis were estimated to have driven under the influence of cannabis. Substantial evidence has accumulated to indicate that driving after cannabis use increases collision risk significantly; however, little is known about the extent and costs associated with cannabis-related traffic collisions. This study quantifies the costs of cannabis-related traffic collisions in the Canadian provinces. Province and age specific cannabis-attributable fractions (CAFs) were calculated for traffic collisions of varying severity. The CAFs were applied to traffic collision data in order to estimate the total number of persons involved in cannabis-attributable fatal, injury and property damage only collisions. Social cost values, based on willingness-to-pay and direct costs, were applied to estimate the costs associated with cannabis-related traffic collisions. The 95% confidence intervals were calculated using Monte Carlo methodology. Cannabis-attributable traffic collisions were estimated to have caused 75 deaths (95% CI: 0-213), 4407 injuries (95% CI: 20-11,549) and 7794 people (95% CI: 3107-13,086) were involved in property damage only collisions in Canada in 2012, totalling $1,094,972,062 (95% CI: 37,069,392-2,934,108,175) with costs being highest among younger people. The cannabis-attributable driving harms and costs are substantial. The harm and cost of cannabis-related collisions is an important factor to consider as Canada looks to legalize and regulate the sale of cannabis. This analysis provides evidence to help inform Canadian policy to reduce the human and economic costs of drug-impaired driving. Copyright © 2017 Canadian Centre on Substance Abuse. Published by Elsevier B.V. All rights reserved.
Shekarrizfard, Maryam; Valois, Marie-France; Goldberg, Mark S; Crouse, Dan; Ross, Nancy; Parent, Marie-Elise; Yasmin, Shamsunnahar; Hatzopoulou, Marianne
2015-07-01
In two earlier case-control studies conducted in Montreal, nitrogen dioxide (NO2), a marker for traffic-related air pollution was found to be associated with the incidence of postmenopausal breast cancer and prostate cancer. These studies relied on a land use regression model (LUR) for NO2 that is commonly used in epidemiologic studies for deriving estimates of traffic-related air pollution. Here, we investigate the use of a transportation model developed during the summer season to generate a measure of traffic emissions as an alternative to the LUR model. Our traffic model provides estimates of emissions of nitrogen oxides (NOx) at the level of individual roads, as does the LUR model. Our main objective was to compare the distribution of the spatial estimates of NOx computed from our transportation model to the distribution obtained from the LUR model. A secondary objective was to compare estimates of risk using these two exposure estimates. We observed that the correlation (spearman) between our two measures of exposure (NO2 and NOx) ranged from less than 0.3 to more than 0.9 across Montreal neighborhoods. The most important factor affecting the "agreement" between the two measures in a specific area was found to be the length of roads. Areas affected by a high level of traffic-related air pollution had a far better agreement between the two exposure measures. A comparison of odds ratios (ORs) obtained from NO2 and NOx used in two case-control studies of breast and prostate cancer, showed that the differences between the ORs associated with NO2 exposure vs NOx exposure differed by 5.2-8.8%. Copyright © 2015 Elsevier Inc. All rights reserved.
Valiant load-balanced robust routing under hose model for WDM mesh networks
NASA Astrophysics Data System (ADS)
Zhang, Xiaoning; Li, Lemin; Wang, Sheng
2006-09-01
In this paper, we propose Valiant Load-Balanced robust routing scheme for WDM mesh networks under the model of polyhedral uncertainty (i.e., hose model), and the proposed routing scheme is implemented with traffic grooming approach. Our Objective is to maximize the hose model throughput. A mathematic formulation of Valiant Load-Balanced robust routing is presented and three fast heuristic algorithms are also proposed. When implementing Valiant Load-Balanced robust routing scheme to WDM mesh networks, a novel traffic-grooming algorithm called MHF (minimizing hop first) is proposed. We compare the three heuristic algorithms with the VPN tree under the hose model. Finally we demonstrate in the simulation results that MHF with Valiant Load-Balanced robust routing scheme outperforms the traditional traffic-grooming algorithm in terms of the throughput for the uniform/non-uniform traffic matrix under the hose model.
Wang, Degao; Tian, Fulin; Yang, Meng; Liu, Chenlin; Li, Yi-Fan
2009-05-01
Soil derived sources of polycyclic aromatic hydrocarbons (PAHs) in the region of Dalian, China were investigated using positive matrix factorization (PMF). Three factors were separated based on PMF for the statistical investigation of the datasets both in summer and winter. These factors were dominated by the pattern of single sources or groups of similar sources, showing seasonal and regional variations. The main sources of PAHs in Dalian soil in summer were the emissions from coal combustion average (46%), diesel engine (30%), and gasoline engine (24%). In winter, the main sources were the emissions from coal-fired boiler (72%), traffic average (20%), and gasoline engine (8%). These factors with strong seasonality indicated that coal combustion in winter and traffic exhaust in summer dominated the sources of PAHs in soil. These results suggested that PMF model was a proper approach to identify the sources of PAHs in soil.
[Methodologies for estimating the indirect costs of traffic accidents].
Carozzi, Soledad; Elorza, María Eugenia; Moscoso, Nebel Silvana; Ripari, Nadia Vanina
2017-01-01
Traffic accidents generate multiple costs to society, including those associated with the loss of productivity. However, there is no consensus about the most appropriate methodology for estimating those costs. The aim of this study was to review methods for estimating indirect costs applied in crash cost studies. A thematic review of the literature was carried out between 1995 and 2012 in PubMed with the terms cost of illness, indirect cost, road traffic injuries, productivity loss. For the assessment of costs we used the the human capital method, on the basis of the wage-income lost during the time of treatment and recovery of patients and caregivers. In the case of premature death or total disability, the discount rate was applied to obtain the present value of lost future earnings. The computed years arose by subtracting to life expectancy at birth the average age of those affected who are not incorporated into the economically active life. The interest in minimizing the problem is reflected in the evolution of the implemented methodologies. We expect that this review is useful to estimate efficiently the real indirect costs of traffic accidents.
A method to estimate spatiotemporal air quality in an urban traffic corridor.
Singh, Nongthombam Premananda; Gokhale, Sharad
2015-12-15
Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area. Copyright © 2015 Elsevier B.V. All rights reserved.
Guide to long term pavement performance (LTPP) traffic data collection and processing
DOT National Transportation Integrated Search
2000-04-11
The goal of this report is to document the process and procedures used by LTPP to collect and store the traffic data used to estimate pavement loadings. This first section of this report provides introductory material on the traffic data collection p...
DOT National Transportation Integrated Search
2000-05-01
It has been estimated that 57 percent of the nation?s traffic congestion is due to crashes and other incidents. Organized traffic incident management is the primary tool in mitigating the impact. Traffic incident management involves multi-agency, mul...
Air pollution and health risks due to vehicle traffic.
Zhang, Kai; Batterman, Stuart
2013-04-15
Traffic congestion increases vehicle emissions and degrades ambient air quality, and recent studies have shown excess morbidity and mortality for drivers, commuters and individuals living near major roadways. Presently, our understanding of the air pollution impacts from congestion on roads is very limited. This study demonstrates an approach to characterize risks of traffic for on- and near-road populations. Simulation modeling was used to estimate on- and near-road NO2 concentrations and health risks for freeway and arterial scenarios attributable to traffic for different traffic volumes during rush hour periods. The modeling used emission factors from two different models (Comprehensive Modal Emissions Model and Motor Vehicle Emissions Factor Model version 6.2), an empirical traffic speed-volume relationship, the California Line Source Dispersion Model, an empirical NO2-NOx relationship, estimated travel time changes during congestion, and concentration-response relationships from the literature, which give emergency doctor visits, hospital admissions and mortality attributed to NO2 exposure. An incremental analysis, which expresses the change in health risks for small increases in traffic volume, showed non-linear effects. For a freeway, "U" shaped trends of incremental risks were predicted for on-road populations, and incremental risks are flat at low traffic volumes for near-road populations. For an arterial road, incremental risks increased sharply for both on- and near-road populations as traffic increased. These patterns result from changes in emission factors, the NO2-NOx relationship, the travel delay for the on-road population, and the extended duration of rush hour for the near-road population. This study suggests that health risks from congestion are potentially significant, and that additional traffic can significantly increase risks, depending on the type of road and other factors. Further, evaluations of risk associated with congestion must consider travel time, the duration of rush-hour, congestion-specific emission estimates, and uncertainties. Copyright © 2013 Elsevier B.V. All rights reserved.
Air pollution and health risks due to vehicle traffic
Zhang, Kai; Batterman, Stuart
2014-01-01
Traffic congestion increases vehicle emissions and degrades ambient air quality, and recent studies have shown excess morbidity and mortality for drivers, commuters and individuals living near major roadways. Presently, our understanding of the air pollution impacts from congestion on roads is very limited. This study demonstrates an approach to characterize risks of traffic for on- and near-road populations. Simulation modeling was used to estimate on- and near-road NO2 concentrations and health risks for freeway and arterial scenarios attributable to traffic for different traffic volumes during rush hour periods. The modeling used emission factors from two different models (Comprehensive Modal Emissions Model and Motor Vehicle Emissions Factor Model version 6.2), an empirical traffic speed–volume relationship, the California Line Source Dispersion Model, an empirical NO2–NOx relationship, estimated travel time changes during congestion, and concentration–response relationships from the literature, which give emergency doctor visits, hospital admissions and mortality attributed to NO2 exposure. An incremental analysis, which expresses the change in health risks for small increases in traffic volume, showed non-linear effects. For a freeway, “U” shaped trends of incremental risks were predicted for on-road populations, and incremental risks are flat at low traffic volumes for near-road populations. For an arterial road, incremental risks increased sharply for both on- and near-road populations as traffic increased. These patterns result from changes in emission factors, the NO2–NOx relationship, the travel delay for the on-road population, and the extended duration of rush hour for the near-road population. This study suggests that health risks from congestion are potentially significant, and that additional traffic can significantly increase risks, depending on the type of road and other factors. Further, evaluations of risk associated with congestion must consider travel time, the duration of rush-hour, congestion-specific emission estimates, and uncertainties. PMID:23500830
Short-term and long-term effects of GDP on traffic deaths in 18 OECD countries, 1960-2011.
Dadgar, Iman; Norström, Thor
2017-02-01
Research suggests that increases in gross domestic product (GDP) lead to increases in traffic deaths plausibly due to the increased road traffic induced by an expanding economy. However, there also seems to exist a long-term effect of economic growth that is manifested in improved traffic safety and reduced rates of traffic deaths. Previous studies focus on either the short-term, procyclical effect, or the long-term, protective effect. The aim of the present study is to estimate the short-term and long-term effects jointly in order to assess the net impact of GDP on traffic mortality. We extracted traffic death rates for the period 1960-2011 from the WHO Mortality Database for 18 OECD countries. Data on GDP/capita were obtained from the Maddison Project. We performed error correction modelling to estimate the short-term and long-term effects of GDP on the traffic death rates. The estimates from the error correction modelling for the entire study period suggested that a one-unit increase (US$1000) in GDP/capita yields an instantaneous short-term increase in the traffic death rate by 0.58 (p<0.001), and a long-term decrease equal to -1.59 (p<0.001). However, period-specific analyses revealed a structural break implying that the procyclical effect outweighs the protective effect in the period prior to 1976, whereas the reverse is true for the period 1976-2011. An increase in GDP leads to an immediate increase in traffic deaths. However, after the mid-1970s this short-term effect is more than outweighed by a markedly stronger protective long-term effect, whereas the reverse is true for the period before the mid-1970s. 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/.
Traffic noise reduces foraging efficiency in wild owls
NASA Astrophysics Data System (ADS)
Senzaki, Masayuki; Yamaura, Yuichi; Francis, Clinton D.; Nakamura, Futoshi
2016-08-01
Anthropogenic noise has been increasing globally. Laboratory experiments suggest that noise disrupts foraging behavior across a range of species, but to reveal the full impacts of noise, we must examine the impacts of noise on foraging behavior among species in the wild. Owls are widespread nocturnal top predators and use prey rustling sounds for localizing prey when hunting. We conducted field experiments to examine the effect of traffic noise on owls’ ability to detect prey. Results suggest that foraging efficiency declines with increasing traffic noise levels due to acoustic masking and/or distraction and aversion to traffic noise. Moreover, we estimate that effects of traffic noise on owls’ ability to detect prey reach >120 m from a road, which is larger than the distance estimated from captive studies with bats. Our study provides the first evidence that noise reduces foraging efficiency in wild animals, and highlights the possible pervasive impacts of noise.
Traffic noise reduces foraging efficiency in wild owls.
Senzaki, Masayuki; Yamaura, Yuichi; Francis, Clinton D; Nakamura, Futoshi
2016-08-18
Anthropogenic noise has been increasing globally. Laboratory experiments suggest that noise disrupts foraging behavior across a range of species, but to reveal the full impacts of noise, we must examine the impacts of noise on foraging behavior among species in the wild. Owls are widespread nocturnal top predators and use prey rustling sounds for localizing prey when hunting. We conducted field experiments to examine the effect of traffic noise on owls' ability to detect prey. Results suggest that foraging efficiency declines with increasing traffic noise levels due to acoustic masking and/or distraction and aversion to traffic noise. Moreover, we estimate that effects of traffic noise on owls' ability to detect prey reach >120 m from a road, which is larger than the distance estimated from captive studies with bats. Our study provides the first evidence that noise reduces foraging efficiency in wild animals, and highlights the possible pervasive impacts of noise.
Estimating traffic volumes for signalized intersections using connected vehicle data
Zheng, Jianfeng; Liu, Henry X.
2017-04-17
Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimatemore » traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model in this paper vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Finally, considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.« less
Estimating traffic volumes for signalized intersections using connected vehicle data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zheng, Jianfeng; Liu, Henry X.
Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimatemore » traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model in this paper vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Finally, considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.« less
An investigation of TNAV equipped aircraft in a simulated en route metering environment
NASA Technical Reports Server (NTRS)
Groce, J. L.; Izumi, K. H.; Markham, C. H.; Schwab, R. W.; Taylor, J. A.
1986-01-01
This document presents the results of an effort to estimate how often a TNAV (Time Navigation) equipped aircraft could be given a TNAV clearance in the En Route Metering (ERM) system as a function of the percentage of arriving traffic which is TNAV equipped. A fast-time simulation of Denver Stapleton international arrival traffic in the Denver Air Route Traffic Control Center route structure, including en route metering operations, was used to develop data on estimated conflicts, clearance communications and fuel usage for traffic mixes of 25, 50, 75 and 100% TNAV equipped. This study supports an overall effort by NASA to assess the benefits and required technology for using TNAV-equipped aircraft in the ERM environment.
DOT National Transportation Integrated Search
2009-11-01
One objective of statewide traffic monitoring : programs is to accurately estimate the Annual : Average Daily Traffic (AADT) for many roadway : segments within the state. The majority of the : departments of transportation (DOT) in the United : State...
DOT National Transportation Integrated Search
2017-02-01
This project covered the development and calibration of a Dynamic Traffic Assignment (DTA) model and explained the procedures, constraints, and considerations for usage of this model for the Reno-Sparks area roadway network in Northern Nevada. A lite...
NASA Astrophysics Data System (ADS)
Salameh, Thérèse; Sauvage, Stéphane; Afif, Charbel; Borbon, Agnès; Locoge, Nadine
2016-03-01
We applied the positive matrix factorization model to two large data sets collected during two intensive measurement campaigns (summer 2011 and winter 2012) at a sub-urban site in Beirut, Lebanon, in order to identify NMHC (non-methane hydrocarbons) sources and quantify their contribution to ambient levels. Six factors were identified in winter and five factors in summer. PMF-resolved source profiles were consistent with source profiles established by near-field measurements. The major sources were traffic-related emissions (combustion and gasoline evaporation) in winter and in summer accounting for 51 and 74 wt %, respectively, in agreement with the national emission inventory. The gasoline evaporation related to traffic source had a significant contribution regardless of the season (22 wt % in winter and 30 wt % in summer). The NMHC emissions from road transport are estimated from observations and PMF results, and compared to local and global emission inventories. The PMF analysis finds reasonable differences on emission rates, of 20-39 % higher than the national road transport inventory. However, global inventories (ACCMIP, EDGAR, MACCity) underestimate the emissions up to a factor of 10 for the transportation sector. When combining emission inventory to our results, there is strong evidence that control measures in Lebanon should be targeted on mitigating the NMHC emissions from the traffic-related sources. From a global perspective, an assessment of VOC (volatile organic compounds) anthropogenic emission inventories for the Middle East region as a whole seems necessary as these emissions could be much higher than expected at least from the road transport sector.
Information matrix estimation procedures for cognitive diagnostic models.
Liu, Yanlou; Xin, Tao; Andersson, Björn; Tian, Wei
2018-03-06
Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance. © 2018 The British Psychological Society.
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.
Prospect theory based estimation of drivers' risk attitudes in route choice behaviors.
Zhou, Lizhen; Zhong, Shiquan; Ma, Shoufeng; Jia, Ning
2014-12-01
This paper applied prospect theory (PT) to describe drivers' route choice behavior under Variable Message Sign (VMS), which presented visual traffic information to assist them to make route choice decisions. A quite rich empirical data from questionnaire and field spot was used to estimate parameters of PT. In order to make the parameters more realistic with drivers' attitudes, they were classified into different types by significant factors influencing their behaviors. Based on the travel time distribution of alternative routes and route choice results from questionnaire, the parameterized value function of each category was figured out, which represented drivers' risk attitudes and choice characteristics. The empirical verification showed that the estimates were acceptable and effective. The result showed drivers' risk attitudes and route choice characteristics could be captured by PT under real-time information shown on VMS. For practical application, once drivers' route choice characteristics and parameters were identified, their route choice behavior under different road conditions could be predicted accurately, which was the basis of traffic guidance measures formulation and implementation for targeted traffic management. Moreover, the heterogeneous risk attitudes among drivers should be considered when releasing traffic information and regulating traffic flow. Copyright © 2014 Elsevier Ltd. All rights reserved.
On sequential data assimilation for scalar macroscopic traffic flow models
NASA Astrophysics Data System (ADS)
Blandin, Sébastien; Couque, Adrien; Bayen, Alexandre; Work, Daniel
2012-09-01
We consider the problem of sequential data assimilation for transportation networks using optimal filtering with a scalar macroscopic traffic flow model. Properties of the distribution of the uncertainty on the true state related to the specific nonlinearity and non-differentiability inherent to macroscopic traffic flow models are investigated, derived analytically and analyzed. We show that nonlinear dynamics, by creating discontinuities in the traffic state, affect the performances of classical filters and in particular that the distribution of the uncertainty on the traffic state at shock waves is a mixture distribution. The non-differentiability of traffic dynamics around stationary shock waves is also proved and the resulting optimality loss of the estimates is quantified numerically. The properties of the estimates are explicitly studied for the Godunov scheme (and thus the Cell-Transmission Model), leading to specific conclusions about their use in the context of filtering, which is a significant contribution of this article. Analytical proofs and numerical tests are introduced to support the results presented. A Java implementation of the classical filters used in this work is available on-line at http://traffic.berkeley.edu for facilitating further efforts on this topic and fostering reproducible research.
Setton, Eleanor M; Keller, C Peter; Cloutier-Fisher, Denise; Hystad, Perry W
2008-01-01
Background Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. Results Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 μg/m3 to 35 μg/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported. Conclusion The results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy. PMID:18638398
Influence of mobile phone traffic on base station exposure of the general public.
Joseph, Wout; Verloock, Leen
2010-11-01
The influence of mobile phone traffic on temporal radiofrequency exposure due to base stations during 7 d is compared for five different sites with Erlang data (representing average mobile phone traffic intensity during a period of time). The time periods of high exposure and high traffic during a day are compared and good agreement is obtained. The minimal required measurement periods to obtain accurate estimates for maximal and average long-period exposure (7 d) are determined. It is shown that these periods may be very long, indicating the necessity of new methodologies to estimate maximal and average exposure from short-period measurement data. Therefore, a new method to calculate the fields at a time instant from fields at another time instant using normalized Erlang values is proposed. This enables the estimation of maximal and average exposure during a week from short-period measurements using only Erlang data and avoids the necessity of long measurement times.
Eagle Ford Shale BTEX and NOx concentrations are dominated by oil and gas industry emissions
NASA Astrophysics Data System (ADS)
Schade, G. W.; Roest, G. S.
2017-12-01
US shale oil and gas exploration has been identified as a major source of greenhouse gases and non-methane hydrocarbon (NMHC) emissions to the atmosphere. Here, we present a detailed analysis of 2015 air quality data acquired by the Texas Commission on Environmental Quality (TCEQ) at an air quality monitoring station in Karnes County, TX, central to Texas' Eagle Ford shale area. Data include time series of hourly measured NMHCs, nitrogen oxides (NOx), and hydrogen sulfide (H2S) alongside meteorological measurements. The monitor was located in Karnes City, and thus affected by various anthropogenic emissions, including traffic and oil and gas exploration sources. Highest mixing ratios measured in 2015 included nearly 1 ppm ethane, 0.8 ppm propane, alongside 4 ppb benzene. A least-squares minimization non-negative matrix factorization (NMF) analysis, tested with prior data analyzed using standard PMF-2 software, showed six major emission sources: an evaporative and fugitive source, a flaring source, a traffic source, an oil field source, a diesel source, and an industrial manufacturing source, together accounting for more than 95% of data set variability, and interpreted using NMHC composition and meteorological data. Factor scores strongly suggest that NOx emissions are dominated by flaring and associated sources, such as diesel compressor engines, likely at midstream facilities, while traffic in this rural area is a minor NOx source. The results support, but exceed existing 2012 emission inventories estimating that local traffic emitted seven times fewer NOx than oil and gas exploration sources in the county. Sources of air toxics such as the BTEX compounds are also dominated by oil and gas exploration sources, but are more equally distributed between the associated factors. Benzene abundance is only 20-40% associated with traffic sources, and may thus be 2.5-5 times higher now than prior to the shale boom in this area. Although the monitor was located relatively far from oil and gas exploration sources, these results suggest that exposure to air toxics in this rural population has likely increased manifold since the start of the regional shale boom in 2008.
Adjacency Matrix-Based Transmit Power Allocation Strategies in Wireless Sensor Networks
Consolini, Luca; Medagliani, Paolo; Ferrari, Gianluigi
2009-01-01
In this paper, we present an innovative transmit power control scheme, based on optimization theory, for wireless sensor networks (WSNs) which use carrier sense multiple access (CSMA) with collision avoidance (CA) as medium access control (MAC) protocol. In particular, we focus on schemes where several remote nodes send data directly to a common access point (AP). Under the assumption of finite overall network transmit power and low traffic load, we derive the optimal transmit power allocation strategy that minimizes the packet error rate (PER) at the AP. This approach is based on modeling the CSMA/CA MAC protocol through a finite state machine and takes into account the network adjacency matrix, depending on the transmit power distribution and determining the network connectivity. It will be then shown that the transmit power allocation problem reduces to a convex constrained minimization problem. Our results show that, under the assumption of low traffic load, the power allocation strategy, which guarantees minimal delay, requires the maximization of network connectivity, which can be equivalently interpreted as the maximization of the number of non-zero entries of the adjacency matrix. The obtained theoretical results are confirmed by simulations for unslotted Zigbee WSNs. PMID:22346705
Current state of traffic pollution in Bangladesh and metropolitan Dhaka
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karim, Masud; Matsui, Hiroshi; Ohno, Takashi
1997-12-31
Limited resources, invested for the development of transport facilities, such as infrastructure and vehicles, coupled with the rapid rise in transport demand, existence of a huge number of non-motorized vehicles on roads, lack of application of adequate and proper traffic management schemes are producing severe transport problems in almost all the urban areas of Bangladesh. Worsening situation of traffic congestion in the streets and sufferings of the inhabitants from vehicle emissions demand extensive research in this field. However, no detailed study concerning traffic congestion and pollution problems for urban areas of Bangladesh has yet been done. Therefore, it has becomemore » increasingly important to examine the present state of the problem. This research is a preliminary evaluation of the current situation of traffic pollution problem in Bangladesh. The daily total emissions of NO{sub x}, HC, CO, PM, and SO{sub x} are estimated using the daily fuel consumption and total traffic flows in Dhaka city. Estimated daily emissions are 42, 39, 314, 14, and 42 t/d for NO{sub x}, HC, CO, PM, and SO{sub x}, respectively. The emissions estimated using two different methods revealed good correlation. Daily average concentration of NO{sub x} (NO{sub 2}, NO) were measured at 30 street locations in Dhaka city during September and November, 1996. The results showed extremely high concentrations of NO{sub 2} and NO in these locations.« less
Schram-Bijkerk, D; van Kempen, E; Knol, A B; Kruize, H; Staatsen, B; van Kamp, I
2009-10-01
Few quantitative health impact assessments (HIAs) of transport policies have been published so far and there is a lack of a common methodology for such assessments. To evaluate the usability of existing HIA methodology to quantify health effects of transport policies at the local level. Health impact of two simulated but realistic transport interventions - speed limit reduction and traffic re-allocation - was quantified by selecting traffic-related exposures and health endpoints, modelling of population exposure, selecting exposure-effect relations and estimating the number of local traffic-related cases and disease burden, expressed in disability-adjusted life-years (DALYs), before and after the intervention. Exposure information was difficult to retrieve because of the local scale of the interventions, and exposure-effect relations for subgroups and combined effects were missing. Given uncertainty in the outcomes originating from this kind of missing information, simulated changes in population health by two local traffic interventions were estimated to be small (<5%), except for the estimated reduction in DALYs by less traffic accidents (60%) due to speed limit reduction. Quantitative HIA of transport policies at a local scale is possible, provided that data on exposures, the exposed population and their baseline health status are available. The interpretation of the HIA information should be carried out in the context of the quality of input data and assumptions and uncertainties of the analysis.
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...
TxDOT uses of real-time commercial traffic data : opportunity matrix.
DOT National Transportation Integrated Search
2012-01-01
Based on a TxDOT survey, a review of other state DOTs, and researcher understanding of Intelligent Transportation System (ITS) needs, the Texas Transportation Institute (TTI) team developed a comprehensive list of opportunities for TxDOT to consider ...
Development of a rockfall hazard rating matrix for the State of Ohio.
DOT National Transportation Integrated Search
2005-03-01
Although Ohio is not considered a "mountainous state", it is well documented that rockfalls are prevalent. Rockfalls pose a : considerable risk to traffic safety, create maintenance problems, and exert a strain on limited maintenance funds available ...
Development of a Rockfall Hazard Rating Matrix for the State of Ohio
DOT National Transportation Integrated Search
2005-03-01
Although Ohio is not considered a "mountainous state", it is well documented that rockfalls are prevalent. Rockfalls pose a : considerable risk to traffic safety, create maintenance problems, and exert a strain on limited maintenance funds available ...
Path Flow Estimation Using Time Varying Coefficient State Space Model
NASA Astrophysics Data System (ADS)
Jou, Yow-Jen; Lan, Chien-Lun
2009-08-01
The dynamic path flow information is very crucial in the field of transportation operation and management, i.e., dynamic traffic assignment, scheduling plan, and signal timing. Time-dependent path information, which is important in many aspects, is nearly impossible to be obtained. Consequently, researchers have been seeking estimation methods for deriving valuable path flow information from less expensive traffic data, primarily link traffic counts of surveillance systems. This investigation considers a path flow estimation problem involving the time varying coefficient state space model, Gibbs sampler, and Kalman filter. Numerical examples with part of a real network of the Taipei Mass Rapid Transit with real O-D matrices is demonstrated to address the accuracy of proposed model. Results of this study show that this time-varying coefficient state space model is very effective in the estimation of path flow compared to time-invariant model.
NASA Astrophysics Data System (ADS)
Salameh, T.; Sauvage, S.; Afif, C.; Borbon, A.; Locoge, N.
2015-10-01
We applied the Positive Matrix Factorization model to two large datasets collected during two intensive measurement campaigns (summer 2011 and winter 2012) at a sub-urban site in Beirut, Lebanon, in order to identify NMHC sources and quantify their contribution to ambient levels. Six factors were identified in winter and five factors in summer. PMF-resolved source profiles were consistent with source profiles established by near-field measurements. The major sources were traffic-related emissions (combustion and gasoline evaporation) in winter and in summer accounting for 51 and 74 wt % respectively in agreement with the national emission inventory. The gasoline evaporation related to traffic source had a significant contribution regardless of the season (22 wt % in winter and 30 wt % in summer). The NMHC emissions from road transport are estimated from observations and PMF results, and compared to local and global emission inventories. The national road transport inventory shows lowest emissions than the ones from PMF but with a reasonable difference lower than 50 %. Global inventories show higher discrepancies with lower emissions up to a factor of 10 for the transportation sector. When combining emission inventory to our results, there is a strong evidence that control measures in Lebanon should be targeted on mitigating the NMHC emissions from the traffic-related sources. From a global perspective, an assessment of VOC anthropogenic emission inventories for the Middle East region as a whole seems necessary as these emissions could be much higher than expected at least from the road transport sector. Highlights: - PMF model was applied to identify major NMHC sources and their seasonal variation. - Gasoline evaporation accounts for more than 40 % both in winter and in summer. - NMHC urban emissions are dominated by traffic related sources in both seasons. - Agreement with the emission inventory regarding the relative contribution of the on-road mobile source but disagreement in terms of emission quantities suggesting an underestimation of the inventories.
Batterman, Stuart
2015-01-01
Patterns of traffic activity, including changes in the volume and speed of vehicles, vary over time and across urban areas and can substantially affect vehicle emissions of air pollutants. Time-resolved activity at the street scale typically is derived using temporal allocation factors (TAFs) that allow the development of emissions inventories needed to predict concentrations of traffic-related air pollutants. This study examines the spatial and temporal variation of TAFs, and characterizes prediction errors resulting from their use. Methods are presented to estimate TAFs and their spatial and temporal variability and used to analyze total, commercial and non-commercial traffic in the Detroit, Michigan, U.S. metropolitan area. The variability of total volume estimates, quantified by the coefficient of variation (COV) representing the percentage departure from expected hourly volume, was 21, 33, 24 and 33% for weekdays, Saturdays, Sundays and holidays, respectively. Prediction errors mostly resulted from hour-to-hour variability on weekdays and Saturdays, and from day-to-day variability on Sundays and holidays. Spatial variability was limited across the study roads, most of which were large freeways. Commercial traffic had different temporal patterns and greater variability than noncommercial vehicle traffic, e.g., the weekday variability of hourly commercial volume was 28%. The results indicate that TAFs for a metropolitan region can provide reasonably accurate estimates of hourly vehicle volume on major roads. While vehicle volume is only one of many factors that govern on-road emission rates, air quality analyses would be strengthened by incorporating information regarding the uncertainty and variability of traffic activity. PMID:26688671
Corvalán, Roberto M; Osses, Mauricio; Urrutia, Cristian M
2002-02-01
Depending on the final application, several methodologies for traffic emission estimation have been developed. Emission estimation based on total miles traveled or other average factors is a sufficient approach only for extended areas such as national or worldwide areas. For road emission control and strategies design, microscale analysis based on real-world emission estimations is often required. This involves actual driving behavior and emission factors of the local vehicle fleet under study. This paper reports on a microscale model for hot road emissions and its application to the metropolitan region of the city of Santiago, Chile. The methodology considers the street-by-street hot emission estimation with its temporal and spatial distribution. The input data come from experimental emission factors based on local driving patterns and traffic surveys of traffic flows for different vehicle categories. The methodology developed is able to estimate hourly hot road CO, total unburned hydrocarbons (THCs), particulate matter (PM), and NO(x) emissions for predefined day types and vehicle categories.
Childhood cancer and traffic-related air pollution exposure in pregnancy and early life.
Heck, Julia E; Wu, Jun; Lombardi, Christina; Qiu, Jiaheng; Meyers, Travis J; Wilhelm, Michelle; Cockburn, Myles; Ritz, Beate
2013-01-01
The literature on traffic-related air pollution and childhood cancers is inconclusive, and little is known on rarer cancer types. We sought to examine associations between childhood cancers and traffic-related pollution exposure. The present study included children < 6 years of age identified in the California Cancer Registry (born 1998-2007) who could be linked to a California birth certificate (n = 3,590). Controls were selected at random from California birthrolls (n = 80,224). CAlifornia LINE Source Dispersion Modeling, version 4 (CALINE4) was used to generate estimates of local traffic exposures for each trimester of pregnancy and in the first year of life at the address indicated on the birth certificate. We checked our findings by additionally examining associations with particulate matter (≤ 2.5 μm in aerodynamic diameter; PM2.5) pollution measured by community-based air pollution monitors, and with a simple measure of traffic density. With unconditional logistic regression, a per interquartile range increase in exposure to traffic-related pollution during the first trimester (0.0538 ppm carbon monoxide, estimated using CALINE4) was associated with acute lymphoblastic leukemia [ALL; first trimester odds ratio (OR) = 1.05; 95% CI: 1.01, 1.10]; germ cell tumors (OR = 1.16; 95% CI: 1.04, 1.29), particularly teratomas (OR = 1.26; 95% CI: 1.12, 1.41); and retinoblastoma (OR = 1.11; 95% CI: 1.01, 1.21), particularly bilateral retinoblastoma (OR = 1.16; 95% CI: 1.02, 1.33). Retinoblastoma was also associated with average PM2.5 concentrations during pregnancy, and ALL and teratomas were associated with traffic density near the child's residence at birth. We estimated weak associations between early exposure to traffic pollution and several childhood cancers. Because this is the first study to report on traffic pollution in relation to retinoblastoma or germ cell tumors, and both cancers are rare, these findings require replication in other studies.
Mortality and potential years of life lost by road traffic injuries in Brazil, 2013
Andrade, Silvânia Suely Caribé de Araújo; de Mello-Jorge, Maria Helena Prado
2016-01-01
ABSTRACT OBJECTIVE To estimate the potential years of life lost by road traffic injuries three years after the beginning of the Decade of Action for Traffic Safety. METHODS We analyzed the data of the Sistema de Informações sobre Mortalidade (SIM – Mortality Information System) related to road traffic injuries, in 2013. We estimated the crude and standardized mortality rates for Brazil and geographic regions. We calculated, for the Country, the proportional mortality according to age groups, education level, race/skin color, and type or quality of the victim while user of the public highway. We estimated the potential years of life lost according to sex. RESULTS The mortality rate in 2013 was of 21.0 deaths per 100,000 inhabitants for the Country. The Midwest region presented the highest rate (29.9 deaths per 100,000 inhabitants). Most of the deaths by road traffic injuries took place with males (34.9 deaths per 100,000 males). More than half of the people who have died because of road traffic injuries were of black race/skin color, young adults (24.2%), individuals with low schooling (24.0%), and motorcyclists (28.5%). The mortality rate in the triennium 2011-2013 decreased 4.1%, but increased among motorcyclists. Across the Country, more than a million of potential years of life were lost, in 2013, because of road traffic injuries, especially in the age group of 20 to 29 years. CONCLUSIONS The impact of the high mortality rate is of over a million of potential years of life lost by road traffic injuries, especially among adults in productive age (early mortality), in only one year, representing extreme social cost arising from a cause of death that could be prevented. Despite the reduction of mortality by road traffic injuries from 2011 to 2013, the mortality rates increased among motorcyclists. PMID:27706375
Strobe Traffic Lights Warn of Approaching Emergency Vehicles
NASA Technical Reports Server (NTRS)
Bachelder, Aaron
2004-01-01
Strobe-enhanced traffic signals have been developed to aid in the preemption of road intersections for emergency vehicles. The strobe-enhanced traffic signals can be incorporated into both new and pre-existing traffic-control systems in which the traffic-signal heads are of a relatively new type based on arrays of light-emitting diodes (LEDs). The strobe-enhanced traffic signals offer a less expensive, less complex alternative to a recently developed system of LED-based warning signs placed next to traffic signals. Because of its visual complexity, the combination of traffic signals and warning signs is potentially confusing to motorists. The strobe-enhanced traffic signals present less visual clutter. In a given traffic-signal head, the strobe-enhanced traffic signal is embedded in the red LED array of the stop signal. Two strobe LED strips one horizontal and one vertical are made capable of operating separately from the rest of the red LED matrix. When no emergency vehicle is approaching, the red LED array functions as a normal stop signal: all the red LEDs are turned on and off together. When the intersection is to be preempted for an approaching emergency vehicle, only the LEDs in one of the strobe strips are lit, and are turned on in a sequence that indicates the direction of approach. For example (see figure), if an emergency vehicle approaches from the right, the strobe LEDs are lit in a sequence moving from right to left. Important to the success of strobe-enhanced traffic signals is conformance to city ordinances and close relation to pre-existing traffic standards. For instance, one key restriction is that new icons must not include arrows, so that motorists will not confuse new icons with conventional arrows that indicate allowed directions of movement. It is also critical that new displays like strobe-enhanced traffic signals be similar to displays used in traffic-control systems in large cities. For example, Charleston, South Carolina uses horizontal strobes on red traffic lights to alert motorists and thereby help motorists not to miss red lights. The one significant potential disadvantage of strobe-enhanced traffic lights is initial unfamiliarity on the part of motorists.
Do alcohol excise taxes affect traffic accidents? Evidence from Estonia.
Saar, Indrek
2015-01-01
This article examines the association between alcohol excise tax rates and alcohol-related traffic accidents in Estonia. Monthly time series of traffic accidents involving drunken motor vehicle drivers from 1998 through 2013 were regressed on real average alcohol excise tax rates while controlling for changes in economic conditions and the traffic environment. Specifically, regression models with autoregressive integrated moving average (ARIMA) errors were estimated in order to deal with serial correlation in residuals. Counterfactual models were also estimated in order to check the robustness of the results, using the level of non-alcohol-related traffic accidents as a dependent variable. A statistically significant (P <.01) strong negative relationship between the real average alcohol excise tax rate and alcohol-related traffic accidents was disclosed under alternative model specifications. For instance, the regression model with ARIMA (0, 1, 1)(0, 1, 1) errors revealed that a 1-unit increase in the tax rate is associated with a 1.6% decrease in the level of accidents per 100,000 population involving drunk motor vehicle drivers. No similar association was found in the cases of counterfactual models for non-alcohol-related traffic accidents. This article indicates that the level of alcohol-related traffic accidents in Estonia has been affected by changes in real average alcohol excise taxes during the period 1998-2013. Therefore, in addition to other measures, the use of alcohol taxation is warranted as a policy instrument in tackling alcohol-related traffic accidents.
NASA Astrophysics Data System (ADS)
Ke, Haohao
Receptor models have been widely used in air quality studies to identify pollution sources and estimate their contributions. A common problem for most current receptor models is insufficient consideration of realistic constraints such as can be obtained from emission inventories, chemical composition profiles of the sources, and the physics of plume dispersion. In addition, poor resolving of collinear sources was often found. With the high quality time-, composition-, and size-resolved measurements during the EPA Supersite project, efforts towards resolving nearby industrial sources were made by combinative use of Positive Matrix Factorization (PMF) and the Pseudo-Deterministic Receptor Model (PDRM). The PMF modeling of Baltimore data in September 2001 revealed coal-fired and oil-fired power plants (CFPP and OFPP, respectively) with significant cross contamination, as indicated by the high Se/Ni ratio in the OFPP profile. Nevertheless, the PMF results provided a good estimate of background and the PMF-constrained emission rates well seeded the trajectory-driven PDRM modeling. Using NOx as the tracer gas for chi/Q tuning, ultimately resolved emissions from individual stacks exhibited acceptable tracer ratios and the emission rates of metals generally agreed with the TRI estimates. This approach was later applied to two metal pollution episodes in St. Louis during in November 2001 and March 2002 and met a similar success. As NOx measurements were unavailable at those metal-production facilities, highly-specific tracer metals (i.e., Cd, Zn, and Cu) for the corresponding units were used to tune chi/Qs and their contributions were well resolved with the PMF-seeded PDRM. Opportunistically a PM2.5 excursion during a windless morning in November 2002 allowed the extraction of an in-situ profile of vehicular emissions in Baltimore. The profiles obtained by direct peak observation, windless model linear regression (WMA), PMF, and UNMIX were comparable and the WMA profile showed the best predictions for non-traffic tracers. Besides, an approach to evaluate vehicular emission factors was developed by receptor measurements under windless conditions. Using SVOC tracers, seasonal variations of traffic and other sources including coal burning, heating, biomass burning, and vegetation were investigated by PMF and in particular the November traffic profile was consistent with the WMA profile obtained earlier.
Estimated long-term outdoor air pollution concentrations in a cohort study
NASA Astrophysics Data System (ADS)
Beelen, Rob; Hoek, Gerard; Fischer, Paul; Brandt, Piet A. van den; Brunekreef, Bert
Several recent studies associated long-term exposure to air pollution with increased mortality. An ongoing cohort study, the Netherlands Cohort Study on Diet and Cancer (NLCS), was used to study the association between long-term exposure to traffic-related air pollution and mortality. Following on a previous exposure assessment study in the NLCS, we improved the exposure assessment methods. Long-term exposure to nitrogen dioxide (NO 2), nitrogen oxide (NO), black smoke (BS), and sulphur dioxide (SO 2) was estimated. Exposure at each home address ( N=21 868) was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in a national monitoring network. Regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables were used to estimate the urban component. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and on the nearest major road, and the sum of traffic intensity in a buffer of 100 m around each home address were assessed. Further, a quantitative estimate of the local component was estimated. The regression models to estimate the urban component explained 67%, 46%, 49% and 35% of the variances of NO 2, NO, BS, and SO 2 concentrations, respectively. Overall regression models which incorporated the regional, urban and local component explained 84%, 44%, 59% and 56% of the variability in concentrations for NO 2, NO, BS and SO 2, respectively. We were able to develop an exposure assessment model using GIS methods and traffic intensities that explained a large part of the variations in outdoor air pollution concentrations.
Feasibility of lane closures using probe data.
DOT National Transportation Integrated Search
2017-04-01
To develop an adequate traffic operations management and congestion mitigation plan for every roadway : maintenance and construction project requiring lane closures, transportation agencies need accurate and : reliable estimates of traffic impacts as...
Spatial Resolution Requirements for Traffic-Related Air Pollutant Exposure Evaluations
Batterman, Stuart; Chambliss, Sarah; Isakov, Vlad
2014-01-01
Vehicle emissions represent one of the most important air pollution sources in most urban areas, and elevated concentrations of pollutants found near major roads have been associated with many adverse health impacts. To understand these impacts, exposure estimates should reflect the spatial and temporal patterns observed for traffic-related air pollutants. This paper evaluates the spatial resolution and zonal systems required to estimate accurately intraurban and near-road exposures of traffic-related air pollutants. The analyses use the detailed information assembled for a large (800 km2) area centered on Detroit, Michigan, USA. Concentrations of nitrogen oxides (NOx) due to vehicle emissions were estimated using hourly traffic volumes and speeds on 9,700 links representing all but minor roads in the city, the MOVES2010 emission model, the RLINE dispersion model, local meteorological data, a temporal resolution of 1 hr, and spatial resolution as low as 10 m. Model estimates were joined with the corresponding shape files to estimate residential exposures for 700,000 individuals at property parcel, census block, census tract, and ZIP code levels. We evaluate joining methods, the spatial resolution needed to meet specific error criteria, and the extent of exposure misclassification. To portray traffic-related air pollutant exposure, raster or inverse distance-weighted interpolations are superior to nearest neighbor approaches, and interpolations between receptors and points of interest should not exceed about 40 m near major roads, and 100 m at larger distances. For census tracts and ZIP codes, average exposures are overestimated since few individuals live very near major roads, the range of concentrations is compressed, most exposures are misclassified, and high concentrations near roads are entirely omitted. While smaller zones improve performance considerably, even block-level data can misclassify many individuals. To estimate exposures and impacts of traffic-related pollutants accurately, data should be geocoded or estimated at the most-resolved spatial level; census tract and larger zones have little if any ability to represent intraurban variation in traffic-related air pollutant concentrations. These results are based on one of the most comprehensive intraurban modeling studies in the literature and results are robust. Recommendations address the value of dispersion models to portray spatial and temporal variation of air pollutants in epidemiology and other studies; techniques to improve accuracy and reduce the computational burden in urban scale modeling; the necessary spatial resolution for health surveillance, demographic, and pollution data; and the consequences of low resolution data in terms of exposure misclassification. PMID:25132794
Data traffic reduction schemes for sparse Cholesky factorizations
NASA Technical Reports Server (NTRS)
Naik, Vijay K.; Patrick, Merrell L.
1988-01-01
Load distribution schemes are presented which minimize the total data traffic in the Cholesky factorization of dense and sparse, symmetric, positive definite matrices on multiprocessor systems with local and shared memory. The total data traffic in factoring an n x n sparse, symmetric, positive definite matrix representing an n-vertex regular 2-D grid graph using n (sup alpha), alpha is equal to or less than 1, processors are shown to be O(n(sup 1 + alpha/2)). It is O(n(sup 3/2)), when n (sup alpha), alpha is equal to or greater than 1, processors are used. Under the conditions of uniform load distribution, these results are shown to be asymptotically optimal. The schemes allow efficient use of up to O(n) processors before the total data traffic reaches the maximum value of O(n(sup 3/2)). The partitioning employed within the scheme, allows a better utilization of the data accessed from shared memory than those of previously published methods.
The October 1973 space shuttle traffic model, revision 2
NASA Technical Reports Server (NTRS)
1974-01-01
Traffic model data for the space shuttle for calendar years 1980 through 1991 are presented along with some supporting and summary data. This model was developed from the 1973 NASA Payload Model, dated October 1973, and the NASA estimate of the 1973 Non-NASA/Non-DoD Payload Model. The estimates for the DoD flights included are based on the 1971 DoD Mission Model.
Developing a method for estimating AADT on all Louisiana roads.
DOT National Transportation Integrated Search
2015-07-01
Traffic flow volumes present key information needed for making transportation engineering and planning decisions. : Accurate traffic volume count has many applications including: roadway planning, design, air quality compliance, travel : model valida...
Estimating cost of road traffic injuries in Iran using willingness to pay (WTP) method.
Ainy, Elaheh; Soori, Hamid; Ganjali, Mojtaba; Le, Henry; Baghfalaki, Taban
2014-01-01
We aimed to use the willingness to pay (WTP) method to calculate the cost of traffic injuries in Iran in 2013. We conducted a cross-sectional questionnaire-based study of 846 randomly selected road users. WTP data was collected for four scenarios for vehicle occupants, pedestrians, vehicle drivers, and motorcyclists. Final analysis was carried out using Weibull and maximum likelihood method. Mean WTP was 2,612,050 Iranian rials (IRR). Statistical value of life was estimated according to 20,408 fatalities 402,314,106,073,648 IRR (US$13,410,470,202 based on purchasing power parity at (February 27th, 2014). Injury cost was US$25,637,870,872 (based on 318,802 injured people in 2013, multiple daily traffic volume of 311, and multiple daily payment of 31,030 IRR for 250 working days). The total estimated cost of injury and death cases was 39,048,341,074$. Gross national income of Iran was, US$604,300,000,000 in 2013 and the costs of traffic injuries constituted 6·46% of gross national income. WTP was significantly associated with age, gender, monthly income, daily payment, more payment for time reduction, trip mileage, drivers and occupants from road users. The costs of traffic injuries in Iran in 2013 accounted for 6.64% of gross national income, much higher than the global average. Policymaking and resource allocation to reduce traffic-related death and injury rates have the potential to deliver a huge economic benefit.
Estimating Cost of Road Traffic Injuries in Iran Using Willingness to Pay (WTP) Method
Ainy, Elaheh; Soori, Hamid; Ganjali, Mojtaba; Le, Henry; Baghfalaki, Taban
2014-01-01
We aimed to use the willingness to pay (WTP) method to calculate the cost of traffic injuries in Iran in 2013. We conducted a cross-sectional questionnaire-based study of 846 randomly selected road users. WTP data was collected for four scenarios for vehicle occupants, pedestrians, vehicle drivers, and motorcyclists. Final analysis was carried out using Weibull and maximum likelihood method. Mean WTP was 2,612,050 Iranian rials (IRR). Statistical value of life was estimated according to 20,408 fatalities 402,314,106,073,648 IRR (US$13,410,470,202 based on purchasing power parity at (February 27th, 2014). Injury cost was US$25,637,870,872 (based on 318,802 injured people in 2013, multiple daily traffic volume of 311, and multiple daily payment of 31,030 IRR for 250 working days). The total estimated cost of injury and death cases was 39,048,341,074$. Gross national income of Iran was, US$604,300,000,000 in 2013 and the costs of traffic injuries constituted 6·46% of gross national income. WTP was significantly associated with age, gender, monthly income, daily payment, more payment for time reduction, trip mileage, drivers and occupants from road users. The costs of traffic injuries in Iran in 2013 accounted for 6.64% of gross national income, much higher than the global average. Policymaking and resource allocation to reduce traffic-related death and injury rates have the potential to deliver a huge economic benefit. PMID:25438150
Integrin traffic - the update.
De Franceschi, Nicola; Hamidi, Hellyeh; Alanko, Jonna; Sahgal, Pranshu; Ivaska, Johanna
2015-03-01
Integrins are a family of transmembrane cell surface molecules that constitute the principal adhesion receptors for the extracellular matrix (ECM) and are indispensable for the existence of multicellular organisms. In vertebrates, 24 different integrin heterodimers exist with differing substrate specificity and tissue expression. Integrin-extracellular-ligand interaction provides a physical anchor for the cell and triggers a vast array of intracellular signalling events that determine cell fate. Dynamic remodelling of adhesions, through rapid endocytic and exocytic trafficking of integrin receptors, is an important mechanism employed by cells to regulate integrin-ECM interactions, and thus cellular signalling, during processes such as cell migration, invasion and cytokinesis. The initial concept of integrin traffic as a means to translocate adhesion receptors within the cell has now been expanded with the growing appreciation that traffic is intimately linked to the cell signalling apparatus. Furthermore, endosomal pathways are emerging as crucial regulators of integrin stability and expression in cells. Thus, integrin traffic is relevant in a number of pathological conditions, especially in cancer. Nearly a decade ago we wrote a Commentary in Journal of Cell Science entitled 'Integrin traffic'. With the advances in the field, we felt it would be appropriate to provide the growing number of researchers interested in integrin traffic with an update. © 2015. Published by The Company of Biologists Ltd.
Estimation of the full marginal costs of port related truck traffic.
Berechman, Joseph
2009-11-01
NY region is expected to grow by additional 1 million people by 2020, which translates into roughly 70 million more tons of goods to be delivered annually. Due to lack of rail capacity, mainly trucks will haul this volume of freight, challenging an already much constrained highway network. What are the total costs associated with this additional traffic, in particular, congestion, safety and emission? Since a major source of this expected flow is the Port of New York-New Jersey, this paper focuses on the estimation of the full marginal costs of truck traffic resulting from the further expansion of the port's activities.
Seidler, Andreas; Hegewald, Janice; Seidler, Anna Lene; Schubert, Melanie; Wagner, Mandy; Dröge, Patrik; Haufe, Eva; Schmitt, Jochen; Swart, Enno; Zeeb, Hajo
2017-01-01
Few studies have examined the relationship between traffic noise and depression providing inconclusive results. This large case-control study is the first to assess and directly compare depression risks by aircraft, road traffic and railway noise. The study population included individuals aged ≥40 years that were insured by three large statutory health insurance funds and were living in the region of Frankfurt international airport. Address-specific exposure to aircraft, road and railway traffic noise in 2005 was estimated. Based on insurance claims and prescription data, 77,295 cases with a new clinical depression diagnosis between 2006 and 2010 were compared with 578,246 control subjects. For road traffic noise, a linear exposure-risk relationship was found with an odds ratio (OR) of 1.17 (95% CI=1.10-1.25) for 24-h continuous sound levels ≥70dB. For aircraft noise, the risk estimates reached a maximum OR of 1.23 (95% CI=1.19-1.28) at 50-55dB and decreased at higher exposure categories. For railway noise, risk estimates peaked at 60-65dB (OR=1.15, 95% CI=1.08-1.22). The highest OR of 1.42 (95% CI=1.33-1.52) was found for a combined exposure to noise above 50dB from all three sources. This study indicates that traffic noise exposure might lead to depression. As a potential explanation for the decreasing risks at high traffic noise levels, vulnerable people might actively cope with noise (e.g. insulate or move away). Copyright © 2016 Elsevier Inc. All rights reserved.
Pulido, José; Barrio, Gregorio; Hoyos, Juan; Jiménez-Mejías, Eladio; Martín-Rodríguez, María Del Mar; Houwing, Sjoerd; Lardelli-Claret, Pablo
2016-09-01
Part of the differences by age and gender in driver death rates from traffic injuries depends on the amount of exposure (km/year travelled). Unfortunately, direct indicators of exposure are not available in many countries. Our aim was to compare the age and gender differences in death rates with and without adjustment by exposure using a quasi-induced exposure approach in Spain, during 2004-2012. Crude and adjusted death rate ratios (CDRR and ADRR, respectively) were calculated for each age and gender group. To obtain the latter estimates, in accordance with quasi-exposure reasoning, the number of registered drivers was replaced by the number of non-infractor drivers, passively involved in collisions with another vehicle whose driver committed an infraction. 18-29 years and female drivers were chosen as the reference categories for age and gender. Striking differences were found between CDRR and ADRR estimates. When CDRR were estimated, we found the highest traffic mortality among the youngest drivers, except for females in non-urban roads. ADRR however showed the highest mortality among the oldest groups, especially in females, peaking among drivers >74 years in all types of roads. Regarding differences by gender, both estimates revealed higher traffic mortality in males, although the differences were much smaller when using ADRR. CDRR and ADRR for males tended to converge as age increased. Death risk from traffic injuries among drivers is clearly influenced by the amount of exposure. These findings further emphasize the need to obtain direct traffic exposure estimates by subgroups of drivers. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.
Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun
2017-09-21
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
Capacity planning of link restorable optical networks under dynamic change of traffic
NASA Astrophysics Data System (ADS)
Ho, Kwok Shing; Cheung, Kwok Wai
2005-11-01
Future backbone networks shall require full-survivability and support dynamic changes of traffic demands. The Generalized Survivable Networks (GSN) was proposed to meet these challenges. GSN is fully-survivable under dynamic traffic demand changes, so it offers a practical and guaranteed characterization framework for ASTN / ASON survivable network planning and bandwidth-on-demand resource allocation 4. The basic idea of GSN is to incorporate the non-blocking network concept into the survivable network models. In GSN, each network node must specify its I/O capacity bound which is taken as constraints for any allowable traffic demand matrix. In this paper, we consider the following generic GSN network design problem: Given the I/O bounds of each network node, find a routing scheme (and the corresponding rerouting scheme under failure) and the link capacity assignment (both working and spare) which minimize the cost, such that any traffic matrix consistent with the given I/O bounds can be feasibly routed and it is single-fault tolerant under the link restoration scheme. We first show how the initial, infeasible formal mixed integer programming formulation can be transformed into a more feasible problem using the duality transformation of the linear program. Then we show how the problem can be simplified using the Lagrangian Relaxation approach. Previous work has outlined a two-phase approach for solving this problem where the first phase optimizes the working capacity assignment and the second phase optimizes the spare capacity assignment. In this paper, we present a jointly optimized framework for dimensioning the survivable optical network with the GSN model. Experiment results show that the jointly optimized GSN can bring about on average of 3.8% cost savings when compared with the separate, two-phase approach. Finally, we perform a cost comparison and show that GSN can be deployed with a reasonable cost.
Blais, Etienne; Gagné, Marie-Pier
2010-12-01
To assess the effect on collisions with injuries of a 61% reduction in the number of traffic citations issued by police officers over a 21-month period. Using descriptive analyses as well as ARIMA intervention time-series analyses, this study estimated the impact of this reduction in citations issued for traffic violations on the monthly number of collisions with injuries. Simple descriptive analysis reveals that the 61% reduction in the number of citations issued for traffic violations during the experimental period coincided with an increase in collisions with injuries. Results from the interrupted time-series analyses reveal that, on average, eight additional collisions with injuries occurred every month during which the number of tickets issued for traffic violations was lower than normal. As this pressure tactic was applied for 21 months, it is estimated that this situation was associated with approximately 184 additional collisions with injuries: equivalent to 239 traffic injuries (either deaths, minor or serious injuries). In the province of Quebec, police officers are an important component of road safety policy. Issuing citations prevents drivers from adopting reckless driving habits such as speeding, running red lights and failing to fasten their seat belt.
A hierarchical framework for air traffic control
NASA Astrophysics Data System (ADS)
Roy, Kaushik
Air travel in recent years has been plagued by record delays, with over $8 billion in direct operating costs being attributed to 100 million flight delay minutes in 2007. Major contributing factors to delay include weather, congestion, and aging infrastructure; the Next Generation Air Transportation System (NextGen) aims to alleviate these delays through an upgrade of the air traffic control system. Changes to large-scale networked systems such as air traffic control are complicated by the need for coordinated solutions over disparate temporal and spatial scales. Individual air traffic controllers must ensure aircraft maintain safe separation locally with a time horizon of seconds to minutes, whereas regional plans are formulated to efficiently route flows of aircraft around weather and congestion on the order of every hour. More efficient control algorithms that provide a coordinated solution are required to safely handle a larger number of aircraft in a fixed amount of airspace. Improved estimation algorithms are also needed to provide accurate aircraft state information and situational awareness for human controllers. A hierarchical framework is developed to simultaneously solve the sometimes conflicting goals of regional efficiency and local safety. Careful attention is given in defining the interactions between the layers of this hierarchy. In this way, solutions to individual air traffic problems can be targeted and implemented as needed. First, the regional traffic flow management problem is posed as an optimization problem and shown to be NP-Hard. Approximation methods based on aggregate flow models are developed to enable real-time implementation of algorithms that reduce the impact of congestion and adverse weather. Second, the local trajectory design problem is solved using a novel slot-based sector model. This model is used to analyze sector capacity under varying traffic patterns, providing a more comprehensive understanding of how increased automation in NextGen will affect the overall performance of air traffic control. The dissertation also provides solutions to several key estimation problems that support corresponding control tasks. Throughout the development of these estimation algorithms, aircraft motion is modeled using hybrid systems, which encapsulate both the discrete flight mode of an aircraft and the evolution of continuous states such as position and velocity. The target-tracking problem is posed as one of hybrid state estimation, and two new algorithms are developed to exploit structure specific to aircraft motion, especially near airports. First, discrete mode evolution is modeled using state-dependent transitions, in which the likelihood of changing flight modes is dependent on aircraft state. Second, an estimator is designed for systems with limited mode changes, including arrival aircraft. Improved target tracking facilitates increased safety in collision avoidance and trajectory design problems. A multiple-target tracking and identity management algorithm is developed to improve situational awareness for controllers about multiple maneuvering targets in a congested region. Finally, tracking algorithms are extended to predict aircraft landing times; estimated time of arrival prediction is one example of important decision support information for air traffic control.
Iowa's renewable energy and infrastructure impacts
DOT National Transportation Integrated Search
2010-04-01
Objectives : Estimate traffic growth and pavement deterioration due to Iowas growing renewable energy industries in a multi-county area. : Develop a traffic and fiscal impact model to help assess the impact of additional biofuels plants on...
Estimating Cumulative Traffic Loads, Final Report for Phase 1
DOT National Transportation Integrated Search
2000-07-01
The knowledge of traffic loads is a prerequisite for the pavement analysis process, especially for the development of load-related distress prediction models. Furthermore, the emerging mechanistically based pavement performance models and pavement de...
Airport Surface Traffic Control Systems Deployment Analysis
DOT National Transportation Integrated Search
1974-01-01
The report summarizes the findings of an analysis of ASTC (Airport Surface Traffic Control) system requirements and develops estimates of the deployment potential of proposed system alternatives. The tower control problem areas were investigated by a...
Airport Surface Control Systems Development Analysis Expanded
DOT National Transportation Integrated Search
1990-01-01
A previous MITRE Technical Report, Airport Surface Traffic Control Systems Deployment Analysis, FAA-RD-74-6, presented an analysis of ASTC (Airport Surface Traffic Control) system requirements and developed estimates of the deployment potential of pr...
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)...
Comparison of receptor models for source apportionment of the PM10 in Zaragoza (Spain).
Callén, M S; de la Cruz, M T; López, J M; Navarro, M V; Mastral, A M
2009-08-01
Receptor models are useful to understand the chemical and physical characteristics of air pollutants by identifying their sources and by estimating contributions of each source to receptor concentrations. In this work, three receptor models based on principal component analysis with absolute principal component scores (PCA-APCS), Unmix and positive matrix factorization (PMF) were applied to study for the first time the apportionment of the airborne particulate matter less or equal than 10microm (PM10) in Zaragoza, Spain, during 1year sampling campaign (2003-2004). The PM10 samples were characterized regarding their concentrations in inorganic components: trace elements and ions and also organic components: polycyclic aromatic hydrocarbons (PAH) not only in the solid phase but also in the gas phase. A comparison of the three receptor models was carried out in order to do a more robust characterization of the PM10. The three models predicted that the major sources of PM10 in Zaragoza were related to natural sources (60%, 75% and 47%, respectively, for PCA-APCS, Unmix and PMF) although anthropogenic sources also contributed to PM10 (28%, 25% and 39%). With regard to the anthropogenic sources, while PCA and PMF allowed high discrimination in the sources identification associated with different combustion sources such as traffic and industry, fossil fuel, biomass and fuel-oil combustion, heavy traffic and evaporative emissions, the Unmix model only allowed the identification of industry and traffic emissions, evaporative emissions and heavy-duty vehicles. The three models provided good correlations between the experimental and modelled PM10 concentrations with major precision and the closest agreement between the PMF and PCA models.
NASA Astrophysics Data System (ADS)
Ge, Xinlei; Setyan, Ari; Sun, Yele; Zhang, Qi
2012-10-01
Organic aerosols (OA) were studied in Fresno, California, in winter 2010 with an Aerodyne High Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS). OA dominated the submicron aerosol mass (average = 67%) with an average concentration of 7.9μg m-3 and a nominal formula of C1H1.59N0.014O0.27S0.00008, which corresponds to an average organic mass-to-carbon ratio of 1.50. Three primary OA (POA) factors and one oxygenated OA factor (OOA) representative of secondary OA (SOA) were identified via Positive Matrix Factorization of the high-resolution mass spectra. The three POA factors, which include a traffic-related hydrocarbon-like OA (HOA), a cooking OA (COA), and a biomass burning OA (BBOA) released from residential heating, accounted for an average 57% of the OA mass and up to 80% between 6 - 9 P.M., during which enhanced emissions from evening rush hour traffic, dinner cooking, and residential wood burning were exacerbated by low mixed layer height. The mass-based size distributions of the OA factors were estimated based on multilinear analysis of the size-resolved mass spectra of organics. Both HOA and BBOA peaked at ˜140 nm in vacuum aerodynamic diameter (Dva) while OOA peaked at an accumulation mode of ˜460 nm. COA exhibited a unique size distribution with two size modes centering at ˜200 nm and 450 nm respectively. This study highlights the leading roles played by anthropogenic POA emissions, primarily from traffic, cooking and residential heating, in aerosol pollution in Fresno in wintertime.
Modeling particle number concentrations along Interstate 10 in El Paso, Texas
Olvera, Hector A.; Jimenez, Omar; Provencio-Vasquez, Elias
2014-01-01
Annual average daily particle number concentrations around a highway were estimated with an atmospheric dispersion model and a land use regression model. The dispersion model was used to estimate particle concentrations along Interstate 10 at 98 locations within El Paso, Texas. This model employed annual averaged wind speed and annual average daily traffic counts as inputs. A land use regression model with vehicle kilometers traveled as the predictor variable was used to estimate local background concentrations away from the highway to adjust the near-highway concentration estimates. Estimated particle number concentrations ranged between 9.8 × 103 particles/cc and 1.3 × 105 particles/cc, and averaged 2.5 × 104 particles/cc (SE 421.0). Estimates were compared against values measured at seven sites located along I10 throughout the region. The average fractional error was 6% and ranged between -1% and -13% across sites. The largest bias of -13% was observed at a semi-rural site where traffic was lowest. The average bias amongst urban sites was 5%. The accuracy of the estimates depended primarily on the emission factor and the adjustment to local background conditions. An emission factor of 1.63 × 1014 particles/veh-km was based on a value proposed in the literature and adjusted with local measurements. The integration of the two modeling techniques ensured that the particle number concentrations estimates captured the impact of traffic along both the highway and arterial roadways. The performance and economical aspects of the two modeling techniques used in this study shows that producing particle concentration surfaces along major roadways would be feasible in urban regions where traffic and meteorological data are readily available. PMID:25313294
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.
Doulamis, A D; Doulamis, N D; Kollias, S D
2003-01-01
Multimedia services and especially digital video is expected to be the major traffic component transmitted over communication networks [such as internet protocol (IP)-based networks]. For this reason, traffic characterization and modeling of such services are required for an efficient network operation. The generated models can be used as traffic rate predictors, during the network operation phase (online traffic modeling), or as video generators for estimating the network resources, during the network design phase (offline traffic modeling). In this paper, an adaptable neural-network architecture is proposed covering both cases. The scheme is based on an efficient recursive weight estimation algorithm, which adapts the network response to current conditions. In particular, the algorithm updates the network weights so that 1) the network output, after the adaptation, is approximately equal to current bit rates (current traffic statistics) and 2) a minimal degradation over the obtained network knowledge is provided. It can be shown that the proposed adaptable neural-network architecture simulates a recursive nonlinear autoregressive model (RNAR) similar to the notation used in the linear case. The algorithm presents low computational complexity and high efficiency in tracking traffic rates in contrast to conventional retraining schemes. Furthermore, for the problem of offline traffic modeling, a novel correlation mechanism is proposed for capturing the burstness of the actual MPEG video traffic. The performance of the model is evaluated using several real-life MPEG coded video sources of long duration and compared with other linear/nonlinear techniques used for both cases. The results indicate that the proposed adaptable neural-network architecture presents better performance than other examined techniques.
Fallah Shorshani, Masoud; Bonhomme, Céline; Petrucci, Guido; André, Michel; Seigneur, Christian
2014-04-01
Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.
NASA Astrophysics Data System (ADS)
Ibarra Espinosa, S.; Ynoue, R.; Giannotti, M., , Dr
2017-12-01
It has been shown the importance of emissions inventories for air quality studies and environmental planning at local, regional (REAS), hemispheric (CLRTAP) and global (IPCC) scales. It has been shown also that vehicules are becoming the most important sources in urban centers. Several efforts has been made in order to model vehicular emissions to obtain more accurate emission factors based on Vehicular Specific Power (VPS) with IVE and MOVES based on VSP, MOBILE, VERSIT and COPERT based on average speed, or ARTEMIS and HBEFA based on traffic situations. However, little effort has been made to improve traffic activity data. In this study we are proposing using a novel approach to develop vehicular emissions inventory including point data from MAPLINK a company that feeds with traffic data to Google. This includes working and transforming massive amount of data to generate traffic flow and speeds. The region of study is the south east of Brazil including São Paulo metropolitan areas. To estimate vehicular emissions we are using the open source model VEIN available at https://CRAN.R-project.org/package=vein. We generated hourly traffic between 2010-04-21 and 2010-10-22, totalizing 145 hours. This data consists GPS readings from vehicles with assurance policy, applications and other sources. This type data presents spacial bias meaning that only a part of the vehicles are tracked. We corrected this bias using the calculated speed as proxy of traffic flow using measurements of traffic flow and speed per lane made in São Paulo. Then we calibrated the total traffic estimating Fuel Consumption with VEIN and comparing Fuel Sales for the region. We estimated the hourly vehicular emissions and produced emission maps and data-bases. In addition, we simulated atmospheric simulations using WRF-Chem to identify which inventory produces better agreement with air pollutant observations. New technologies and big data provides opportunities to improve vehicular emissions inventories.
Labib, S M; Neema, Meher Nigar; Rahaman, Zahidur; Patwary, Shahadath Hossain; Shakil, Shahadat Hossain
2018-06-09
CO 2 emissions from urban traffic are a major concern in an era of increasing ecological disequilibrium. Adding to the problem net CO 2 emissions in urban settings are worsened due to the decline of bio-productive areas in many cities. This decline exacerbates the lack of capacity to sequestrate CO 2 at the micro and meso-scales resulting in increased temperatures and decreased air quality within city boundaries. Various transportation and environmental strategies have been implemented to address traffic related CO 2 emissions, however current literature identifies difficulties in pinpointing these critical areas of maximal net emissions in urban transport networks. This study attempts to close this gap in the literature by creating a new lay-person friendly index that combines CO 2 emissions from vehicles and the bio-capacity of specific traffic zones to identify these areas at the meso-scale within four ranges of values with the lowest index values representing the highest net CO 2 levels. The study used traffic volume, fuel types, and vehicular travel distance to estimate CO 2 emissions at major links in Dhaka, Bangladesh's capital city's transportation network. Additionally, using remote-sensing tools, adjacent bio-productive areas were identified and their bio-capacity for CO 2 sequestration estimated. The bio-productive areas were correlated with each traffic zone under study resulting in an Emission Bio-Capacity index (EBI) value estimate for each traffic node. Among the ten studied nodes in Dhaka City, nine had very low EBI values, correlating to very high CO 2 emissions and low bio-capacity. As a result, the study considered these areas unsustainable as traffic nodes going forward. Key reasons for unsustainability included increasing use of motorized traffic, absence of optimized signal systems, inadequate public transit options, disincentives for fuel free transport (FFT), and a decline in bio-productive areas. Copyright © 2018 Elsevier Ltd. All rights reserved.
Jerrett, Michael; McConnell, Rob; Wolch, Jennifer; Chang, Roger; Lam, Claudia; Dunton, Genevieve; Gilliland, Frank; Lurmann, Fred; Islam, Talat; Berhane, Kiros
2014-06-09
Biologically plausible mechanisms link traffic-related air pollution to metabolic disorders and potentially to obesity. Here we sought to determine whether traffic density and traffic-related air pollution were positively associated with growth in body mass index (BMI = kg/m2) in children aged 5-11 years. Participants were drawn from a prospective cohort of children who lived in 13 communities across Southern California (N = 4550). Children were enrolled while attending kindergarten and first grade and followed for 4 years, with height and weight measured annually. Dispersion models were used to estimate exposure to traffic-related air pollution. Multilevel models were used to estimate and test traffic density and traffic pollution related to BMI growth. Data were collected between 2002-2010 and analyzed in 2011-12. Traffic pollution was positively associated with growth in BMI and was robust to adjustment for many confounders. The effect size in the adjusted model indicated about a 13.6% increase in annual BMI growth when comparing the lowest to the highest tenth percentile of air pollution exposure, which resulted in an increase of nearly 0.4 BMI units on attained BMI at age 10. Traffic density also had a positive association with BMI growth, but this effect was less robust in multivariate models. Traffic pollution was positively associated with growth in BMI in children aged 5-11 years. Traffic pollution may be controlled via emission restrictions; changes in land use that promote jobs-housing balance and use of public transit and hence reduce vehicle miles traveled; promotion of zero emissions vehicles; transit and car-sharing programs; or by limiting high pollution traffic, such as diesel trucks, from residential areas or places where children play outdoors, such as schools and parks. These measures may have beneficial effects in terms of reduced obesity formation in children.
Traffic-related air pollution and obesity formation in children: a longitudinal, multilevel analysis
2014-01-01
Background Biologically plausible mechanisms link traffic-related air pollution to metabolic disorders and potentially to obesity. Here we sought to determine whether traffic density and traffic-related air pollution were positively associated with growth in body mass index (BMI = kg/m2) in children aged 5–11 years. Methods Participants were drawn from a prospective cohort of children who lived in 13 communities across Southern California (N = 4550). Children were enrolled while attending kindergarten and first grade and followed for 4 years, with height and weight measured annually. Dispersion models were used to estimate exposure to traffic-related air pollution. Multilevel models were used to estimate and test traffic density and traffic pollution related to BMI growth. Data were collected between 2002–2010 and analyzed in 2011–12. Results Traffic pollution was positively associated with growth in BMI and was robust to adjustment for many confounders. The effect size in the adjusted model indicated about a 13.6% increase in annual BMI growth when comparing the lowest to the highest tenth percentile of air pollution exposure, which resulted in an increase of nearly 0.4 BMI units on attained BMI at age 10. Traffic density also had a positive association with BMI growth, but this effect was less robust in multivariate models. Conclusions Traffic pollution was positively associated with growth in BMI in children aged 5–11 years. Traffic pollution may be controlled via emission restrictions; changes in land use that promote jobs-housing balance and use of public transit and hence reduce vehicle miles traveled; promotion of zero emissions vehicles; transit and car-sharing programs; or by limiting high pollution traffic, such as diesel trucks, from residential areas or places where children play outdoors, such as schools and parks. These measures may have beneficial effects in terms of reduced obesity formation in children. PMID:24913018
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.
National Airspace System Delay Estimation Using Weather Weighted Traffic Counts
NASA Technical Reports Server (NTRS)
Chatterji, Gano B.; Sridhar, Banavar
2004-01-01
Assessment of National Airspace System performance, which is usually measured in terms of delays resulting from the application of traffic flow management initiatives in response to weather conditions, volume, equipment outages and runway conditions, is needed both for guiding flow control decisions during the day of operations and for post operations analysis. Comparison of the actual delay, resulting from the traffic flow management initiatives, with the expected delay, based on traffic demand and other conditions, provides the assessment of the National Airspace System performance. This paper provides a method for estimating delay using the expected traffic demand and weather. In order to identify the cause of delays, 517 days of National Airspace System delay data reported by the Federal Aviation Administration s Operations Network were analyzed. This analysis shows that weather is the most important causal factor for delays followed by equipment and runway delays. Guided by these results, the concept of weather weighted traffic counts as a measure of system delay is described. Examples are given to show the variation of these counts as a function of time of the day. The various datasets, consisting of aircraft position data, enroute severe weather data, surface wind speed and visibility data, reported delay data and number of aircraft handled by the Centers data, and their sources are described. The procedure for selecting reference days on which traffic was minimally impacted by weather is described. Different traffic demand on each reference day of the week, determined by analysis of 42 days of traffic and delay data, was used as the expected traffic demand for each day of the week. Next, the method for computing the weather weighted traffic counts using the expected traffic demand, derived from reference days, and the expanded regions around severe weather cells is discussed. It is shown via a numerical example that this approach improves the dynamic range of the weather weighted traffic counts considerably. Time histories of these new weather weighted traffic counts are used for synthesizing two statistical features, six histogram features and six time domain features. In addition to these enroute weather features, two surface weather features of number of major airports in the United States with high mean winds and low mean visibility are also described. A least squares procedure for establishing a functional relation between the features, using combinations of these features, and system delays is explored using 36 days of data. Best correlations between the estimated delays using the functional relation and the actual delays provided by the Operations Network are obtained with two different combinations of features: 1) six time domain features of weather weighted traffic counts plus two surface weather features, and 2) six histogram features and mean of weather weighted traffic counts along with the two surface weather features. Correlation coefficient values of 0.73 and 0.83 were found in these two instances.
An investigation into incident duration forecasting for FleetForward
DOT National Transportation Integrated Search
2000-08-01
Traffic condition forecasting is the process of estimating future traffic conditions based on current and archived data. Real-time forecasting is becoming an important tool in Intelligent Transportation Systems (ITS). This type of forecasting allows ...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-09
... traffic behaviors and design interventions to reduce speeding and other hazardous traffic actions. Some of... would be voluntary and anonymous. Estimated Total Annual Burden: 2,005 hours (15 pretest interviews...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-03-02
... traffic behaviors and design interventions to reduce speeding and other hazardous traffic actions. Some of... voluntary and anonymous. Estimated Total Annual Burden: 2,005 hours (15 pretest interviews averaging 20...
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...
Roadway Traffic Data Collection from Mobile Platforms, Technical Summary
DOT National Transportation Integrated Search
2017-07-28
This project empirically investigates the traffic flow estimations from different types of data collected from two types of mobile platforms transit buses in service operations and a van driven to emulate bus coverage that repeatedly traverse...
Vecchi, R; Bernardoni, V; Valentini, S; Piazzalunga, A; Fermo, P; Valli, G
2018-02-01
In this paper, results from receptor modelling performed on a well-characterised PM 1 dataset were combined to chemical light extinction data (b ext ) with the aim of assessing the impact of different PM 1 components and sources on light extinction and visibility at a European polluted urban area. It is noteworthy that, at the state of the art, there are still very few papers estimating the impact of different emission sources on light extinction as we present here, although being among the major environmental challenges at many polluted areas. Following the concept of the well-known IMPROVE algorithm, here a tailored site-specific approach (recently developed by our group) was applied to assess chemical light extinction due to PM 1 components and major sources. PM 1 samples collected separately during daytime and nighttime at the urban area of Milan (Italy) were chemically characterised for elements, major ions, elemental and organic carbon, and levoglucosan. Chemical light extinction was estimated and results showed that at the investigated urban site it is heavily impacted by ammonium nitrate and organic matter. Receptor modelling (i.e. Positive Matrix Factorization, EPA-PMF 5.0) was effective to obtain source apportionment; the most reliable solution was found with 7 factors which were tentatively assigned to nitrates, sulphates, wood burning, traffic, industry, fine dust, and a Pb-rich source. The apportionment of aerosol light extinction (b ext,aer ) according to resolved sources showed that considering all samples together nitrate contributed at most (on average 41.6%), followed by sulphate, traffic, and wood burning accounting for 18.3%, 17.8% and 12.4%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Zhang, Kai; Batterman, Stuart
2010-05-01
The contribution of vehicular traffic to air pollutant concentrations is often difficult to establish. This paper utilizes both time-series and simulation models to estimate vehicle contributions to pollutant levels near roadways. The time-series model used generalized additive models (GAMs) and fitted pollutant observations to traffic counts and meteorological variables. A one year period (2004) was analyzed on a seasonal basis using hourly measurements of carbon monoxide (CO) and particulate matter less than 2.5 μm in diameter (PM 2.5) monitored near a major highway in Detroit, Michigan, along with hourly traffic counts and local meteorological data. Traffic counts showed statistically significant and approximately linear relationships with CO concentrations in fall, and piecewise linear relationships in spring, summer and winter. The same period was simulated using emission and dispersion models (Motor Vehicle Emissions Factor Model/MOBILE6.2; California Line Source Dispersion Model/CALINE4). CO emissions derived from the GAM were similar, on average, to those estimated by MOBILE6.2. The same analyses for PM 2.5 showed that GAM emission estimates were much higher (by 4-5 times) than the dispersion model results, and that the traffic-PM 2.5 relationship varied seasonally. This analysis suggests that the simulation model performed reasonably well for CO, but it significantly underestimated PM 2.5 concentrations, a likely result of underestimating PM 2.5 emission factors. Comparisons between statistical and simulation models can help identify model deficiencies and improve estimates of vehicle emissions and near-road air quality.
Li, Run-Kui; Zhao, Tong; Li, Zhi-Peng; Ding, Wen-Jun; Cui, Xiao-Yong; Xu, Qun; Song, Xian-Feng
2014-04-01
On-road vehicle emissions have become the main source of urban air pollution and attracted broad attentions. Vehicle emission factor is a basic parameter to reflect the status of vehicle emissions, but the measured emission factor is difficult to obtain, and the simulated emission factor is not localized in China. Based on the synchronized increments of traffic flow and concentration of air pollutants in the morning rush hour period, while meteorological condition and background air pollution concentration retain relatively stable, the relationship between the increase of traffic and the increase of air pollution concentration close to a road is established. Infinite line source Gaussian dispersion model was transformed for the inversion of average vehicle emission factors. A case study was conducted on a main road in Beijing. Traffic flow, meteorological data and carbon monoxide (CO) concentration were collected to estimate average vehicle emission factors of CO. The results were compared with simulated emission factors of COPERT4 model. Results showed that the average emission factors estimated by the proposed approach and COPERT4 in August were 2.0 g x km(-1) and 1.2 g x km(-1), respectively, and in December were 5.5 g x km(-1) and 5.2 g x km(-1), respectively. The emission factors from the proposed approach and COPERT4 showed close values and similar seasonal trends. The proposed method for average emission factor estimation eliminates the disturbance of background concentrations and potentially provides real-time access to vehicle fleet emission factors.
Wu, Jun; Wilhelm, Michelle; Chung, Judith; Ritz, Beate
2011-01-01
Background Previous studies reported adverse impacts of traffic-related air pollution exposure on pregnancy outcomes. Yet, little information exists on how effect estimates are impacted by the different exposure assessment methods employed in these studies. Objectives To compare effect estimates for traffic-related air pollution exposure and preeclampsia, preterm birth (gestational age less than 37 weeks), and very preterm birth (gestational age less than 30 weeks) based on four commonly-used exposure assessment methods. Methods We identified 81,186 singleton births during 1997–2006 at four hospitals in Los Angeles and Orange Counties, California. Exposures were assigned to individual subjects based on residential address at delivery using the nearest ambient monitoring station data [carbon monoxide (CO), nitrogen dioxide (NO2), nitric oxide (NO), nitrogen oxides (NOx), ozone (O3), and particulate matter less than 2.5 (PM2.5) or less than 10 (PM10) μm in aerodynamic diameter], both unadjusted and temporally-adjusted land-use regression (LUR) model estimates (NO, NO2, and NOx), CALINE4 line-source air dispersion model estimates (NOx and PM2.5), and a simple traffic-density measure. We employed unconditional logistic regression to analyze preeclampsia in our birth cohort, while for gestational age-matched risk sets with preterm and very preterm birth we employed conditional logistic regression. Results We observed elevated risks for preeclampsia, preterm birth, and very preterm birth from maternal exposures to traffic air pollutants measured at ambient stations (CO, NO, NO2, and NOx) and modeled through CALINE4 (NOx and PM2.5) and LUR (NO2 and NOx). Increased risk of preterm birth and very preterm birth were also positively associated with PM10 and PM2.5 air pollution measured at ambient stations. For LUR-modeled NO2 and NOx exposures, elevated risks for all the outcomes were observed in Los Angeles only – the region for which the LUR models were initially developed. Unadjusted LUR models often produced odds ratios somewhat larger in size than temporally-adjusted models. The size of effect estimates was smaller for exposures based on simpler traffic density measures than the other exposure assessment methods. Conclusion We generally confirmed that traffic-related air pollution was associated with adverse reproductive outcomes regardless of the exposure assessment method employed, yet the size of the estimated effect depended on how both temporal and spatial variations were incorporated into exposure assessment. The LUR model was not transferable even between two contiguous areas within the same large metropolitan area in Southern California. PMID:21453913
Customer premises services market demand assessment 1980 - 2000. Volume 1: Executive summary
NASA Technical Reports Server (NTRS)
Gamble, R. B.; Saporta, L.; Heidenrich, G. A.
1983-01-01
Estimates of market demand for domestic civilian telecommunications services for the years 1980 to 2000 are provided. Overall demand, demand or satellite services, demand for satellite delivered Customer Premises Service (CPS), and demand for 30/20 GHz Customer Premises Services are covered. Emphasis is placed on the CPS market and demand is segmented by market, by service, by user class and by geographic region. Prices for competing services are discussed and the distribution of traffic with respect to distance is estimated. A nationwide traffic distribution model for CPS in terms of demand for CPS traffic and earth stations for each of the major SMSAs in the United States are provided.
A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure
Fontaine, Michael D.
2013-01-01
Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing. PMID:23766690
A Cyber-ITS framework for massive traffic data analysis using cyber infrastructure.
Xia, Yingjie; Hu, Jia; Fontaine, Michael D
2013-01-01
Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing.
Modeling the Mechanical Behavior of Ceramic Matrix Composite Materials
NASA Technical Reports Server (NTRS)
Jordan, William
1998-01-01
Ceramic matrix composites are ceramic materials, such as SiC, that have been reinforced by high strength fibers, such as carbon. Designers are interested in using ceramic matrix composites because they have the capability of withstanding significant loads while at relatively high temperatures (in excess of 1,000 C). Ceramic matrix composites retain the ceramic materials ability to withstand high temperatures, but also possess a much greater ductility and toughness. Their high strength and medium toughness is what makes them of so much interest to the aerospace community. This work concentrated on two different tasks. The first task was to do an extensive literature search into the mechanical behavior of ceramic matrix composite materials. This report contains the results of this task. The second task was to use this understanding to help interpret the ceramic matrix composite mechanical test results that had already been obtained by NASA. Since the specific details of these test results are subject to the International Traffic in Arms Regulations (ITAR), they are reported in a separate document (Jordan, 1997).
NASA Astrophysics Data System (ADS)
Powell, James Eckhardt
Emissions inventories are an important tool, often built by governments, and used to manage emissions. To build an inventory of urban CO2 emissions and other fossil fuel combustion products in the urban atmosphere, an inventory of on-road traffic is required. In particular, a high resolution inventory is necessary to capture the local characteristics of transport emissions. These emissions vary widely due to the local nature of the fleet, fuel, and roads. Here we show a new model of ADT for the Portland, OR metropolitan region. The backbone is traffic counter recordings made by the Portland Bureau of Transportation at 7,767 sites over 21 years (1986-2006), augmented with PORTAL (The Portland Regional Transportation Archive Listing) freeway traffic count data. We constructed a regression model to fill in traffic network gaps using GIS data such as road class and population density. An EPA-supplied emissions factor was used to estimate transportation CO2 emissions, which is compared to several other estimates for the city's CO2 footprint.
NASA Astrophysics Data System (ADS)
Zhu, Zhen; Vana, Sudha; Bhattacharya, Sumit; Uijt de Haag, Maarten
2009-05-01
This paper discusses the integration of Forward-looking Infrared (FLIR) and traffic information from, for example, the Automatic Dependent Surveillance - Broadcast (ADS-B) or the Traffic Information Service-Broadcast (TIS-B). The goal of this integration method is to obtain an improved state estimate of a moving obstacle within the Field-of-View of the FLIR with added integrity. The focus of the paper will be on the approach phase of the flight. The paper will address methods to extract moving objects from the FLIR imagery and geo-reference these objects using outputs of both the onboard Global Positioning System (GPS) and the Inertial Navigation System (INS). The proposed extraction method uses a priori airport information and terrain databases. Furthermore, state information from the traffic information sources will be extracted and integrated with the state estimates from the FLIR. Finally, a method will be addressed that performs a consistency check between both sources of traffic information. The methods discussed in this paper will be evaluated using flight test data collected with a Gulfstream V in Reno, NV (GVSITE) and simulated ADS-B.
Traffic effects on bird counts on North American Breeding Bird Survey routes
Griffith, Emily H.; Sauer, John R.; Royle, J. Andrew
2010-01-01
The North American Breeding Bird Survey (BBS) is an annual roadside survey used to estimate population change in >420 species of birds that breed in North America. Roadside sampling has been criticized, in part because traffic noise can interfere with bird counts. Since 1997, data have been collected on the numbers of vehicles that pass during counts at each stop. We assessed the effect of traffic by modeling total vehicles as a covariate of counts in hierarchical Poisson regression models used to estimate population change. We selected species for analysis that represent birds detected at low and high abundance and birds with songs of low and high frequencies. Increases in vehicle counts were associated with decreases in bird counts in most of the species examined. The size and direction of these effects remained relatively constant between two alternative models that we analyzed. Although this analysis indicated only a small effect of incorporating traffic effects when modeling roadside counts of birds, we suggest that continued evaluation of changes in traffic at BBS stops should be a component of future BBS analyses.
NASA Astrophysics Data System (ADS)
Sagnotti, Leonardo; Winkler, Aldo
2012-11-01
The magnetic properties of traffic-related airborne particulate matter (PM) in the city of Rome, Italy, have been previously analyzed and interpreted as suitable proxies to discriminate between different vehicular sources. In this study, we carried out a new set of measurements and analyses specifically devoted to the identification and evaluation of the contribution of ultrafine superparamagnetic (SP) particles to the overall magnetic assemblage of traffic-related PM in Rome. In particular, the presence and the concentration of SP particles have been estimated on powders collected from disk brakes and gasoline exhaust pipes of circulating vehicles and from Quercus ilex leaves grown along high-traffic roads, measuring their hysteresis parameters in a range of temperatures from 293 K to 10 K and measuring the time decay of their saturation remanent magnetization (MRS) at room temperature. The SP fraction contributes for the 10-15% to the overall room temperature MRS and causes the observed changes in the hysteresis properties measured upon cooling down to 10 K. In all the analyzed samples the SP fraction is associated to a generally prevailing population of larger ferrimagnetic multidomain (MD) particles and we suppose that in traffic-related PM the SP fraction mainly occurs as coating of MD particles and originated by localized stress in the oxidized outer shell surrounding the unoxidized core of magnetite-like grains. Under this hypothesis, the estimate of SP content in traffic-related PM cannot be considered a robust proxy to estimate the overall concentration of nanometric particles.
Road traffic accidents: Global Burden of Disease study, Brazil and federated units, 1990 and 2015.
Ladeira, Roberto Marini; Malta, Deborah Carvalho; Morais, Otaliba Libânio de; Montenegro, Marli de Mesquita Silva; Soares, Adauto Martins; Vasconcelos, Cíntia Honório; Mooney, Meghan; Naghavi, Mohsen
2017-05-01
To describe the global burden of disease due to road traffic accidents in Brazil and federated units in 1990 and 2015. This is an analysis of secondary data from the 2015 Global Burden of Disease study estimates. The following estimates were used: standardized mortality rates and years of life lost by death or disability, potential years of life lost due to premature death, and years of unhealthy living conditions. The Mortality Information System was the main source of death data. Underreporting and redistribution of ill-defined causes and nonspecific codes were corrected. Around 52,326 deaths due to road traffic accidents were estimated in Brazil in 2015. From 1990 to 2015, mortality rates decreased from 36.9 to 24.8/100 thousand people, a reduction of 32.8%. Tocantins and Piauí have the highest mortality risks among the federated units (FU), with 41.7/100 and 33.1/100 thousand people, respectively. They both present the highest rates of potential years of life lost due to premature deaths. Road traffic accidents are a public health problem. Using death- or disability-adjusted life years in studies of these causes is important because there are still no sources to know the magnitude of sequelae, as well as the weight of early deaths. Since its data are updated every year, the Global Burden of Disease study may provide evidence to formulate traffic security and health attention policies, which are guided to the needs of the federated units and of different groups of traffic users.
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.
Data traffic reduction schemes for Cholesky factorization on asynchronous multiprocessor systems
NASA Technical Reports Server (NTRS)
Naik, Vijay K.; Patrick, Merrell L.
1989-01-01
Communication requirements of Cholesky factorization of dense and sparse symmetric, positive definite matrices are analyzed. The communication requirement is characterized by the data traffic generated on multiprocessor systems with local and shared memory. Lower bound proofs are given to show that when the load is uniformly distributed the data traffic associated with factoring an n x n dense matrix using n to the alpha power (alpha less than or equal 2) processors is omega(n to the 2 + alpha/2 power). For n x n sparse matrices representing a square root of n x square root of n regular grid graph the data traffic is shown to be omega(n to the 1 + alpha/2 power), alpha less than or equal 1. Partitioning schemes that are variations of block assignment scheme are described and it is shown that the data traffic generated by these schemes are asymptotically optimal. The schemes allow efficient use of up to O(n to the 2nd power) processors in the dense case and up to O(n) processors in the sparse case before the total data traffic reaches the maximum value of O(n to the 3rd power) and O(n to the 3/2 power), respectively. It is shown that the block based partitioning schemes allow a better utilization of the data accessed from shared memory and thus reduce the data traffic than those based on column-wise wrap around assignment schemes.
Traffic speed data imputation method based on tensor completion.
Ran, Bin; Tan, Huachun; Feng, Jianshuai; Liu, Ying; Wang, Wuhong
2015-01-01
Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.
Traffic Speed Data Imputation Method Based on Tensor Completion
Ran, Bin; Feng, Jianshuai; Liu, Ying; Wang, Wuhong
2015-01-01
Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches. PMID:25866501
Liu, Hai-Ying; Skjetne, Erik; Kobernus, Mike
2013-11-04
We propose a new approach to assess the impact of traffic-related air pollution on public health by mapping personal trajectories using mobile phone tracking technology in an urban environment. Although this approach is not based on any empirical studies, we believe that this method has great potential and deserves serious attention. Mobile phone tracking technology makes it feasible to generate millions of personal trajectories and thereby cover a large fraction of an urban population. Through analysis, personal trajectories are not only associated to persons, but it can also be associated with vehicles, vehicle type, vehicle speed, vehicle emission rates, and sources of vehicle emissions. Pollution levels can be estimated by dispersion models from calculated traffic emissions. Traffic pollution exposure to individuals can be estimated based on the exposure along the individual human trajectories in the estimated pollution concentration fields by utilizing modelling tools. By data integration, one may identify trajectory patterns of particularly exposed human groups. The approach of personal trajectories may open a new paradigm in understanding urban dynamics and new perspectives in population-wide empirical public health research. This new approach can be further applied to individual commuter route planning, land use planning, urban traffic network planning, and used by authorities to formulate air pollution mitigation policies and regulations.
2013-01-01
We propose a new approach to assess the impact of traffic-related air pollution on public health by mapping personal trajectories using mobile phone tracking technology in an urban environment. Although this approach is not based on any empirical studies, we believe that this method has great potential and deserves serious attention. Mobile phone tracking technology makes it feasible to generate millions of personal trajectories and thereby cover a large fraction of an urban population. Through analysis, personal trajectories are not only associated to persons, but it can also be associated with vehicles, vehicle type, vehicle speed, vehicle emission rates, and sources of vehicle emissions. Pollution levels can be estimated by dispersion models from calculated traffic emissions. Traffic pollution exposure to individuals can be estimated based on the exposure along the individual human trajectories in the estimated pollution concentration fields by utilizing modelling tools. By data integration, one may identify trajectory patterns of particularly exposed human groups. The approach of personal trajectories may open a new paradigm in understanding urban dynamics and new perspectives in population-wide empirical public health research. This new approach can be further applied to individual commuter route planning, land use planning, urban traffic network planning, and used by authorities to formulate air pollution mitigation policies and regulations. PMID:24188173
Large scale systems : a study of computer organizations for air traffic control applications.
DOT National Transportation Integrated Search
1971-06-01
Based on current sizing estimates and tracking algorithms, some computer organizations applicable to future air traffic control computing systems are described and assessed. Hardware and software problem areas are defined and solutions are outlined.
Holiday effect on traffic fatalities
DOT National Transportation Integrated Search
1987-04-01
The report identifies those holidays that show an increase in traffic fatalities and estimates the size of the increase for each national holiday. A procedure is presented that can be used to forecast the expected fatality count for each upcoming hol...
An external logic architecture for implementing traffic signal system control strategies.
DOT National Transportation Integrated Search
2011-09-01
The built-in logic functions in traffic controllers have very limited capability to store information, to analyze input data, to estimate performance measures, and to adopt control strategy decisions. These capabilities are imperative to support traf...
DOT National Transportation Integrated Search
2017-03-01
This project explores the possibility of using high-resolution traffic signal data to evaluate intersection safety. : Traditional methods using historical crash data collected from infrequently and randomly occurring vehicle : collisions can require ...
Traffic signal operations and maintenance staffing guidelines.
DOT National Transportation Integrated Search
2009-03-01
This report provides a guideline to estimate the staffing and resource needs required to effectively : operate and maintain traffic signal systems. The results of a survey performed under this project, as : well as a review of the literature and othe...
1986 traffic fatalities, preliminary report
DOT National Transportation Integrated Search
1987-04-01
This report provides a number of preliminary estimate of traffic fatalities and fatal accidents for 1986. Trend data are presented for both the long and short term. Some summary statistics are provided at the State and Regional level. The national es...
Airport capacity : representation, estimation, optimization
DOT National Transportation Integrated Search
1993-09-01
A major goal of air traffic management is to strategically control the flow of traffic so that the demand at an airport meets but does not exceed the operational capacity. This paper considers the major aspects of airport operational capacities relev...
Estimate benefits of crowdsourced data from social media.
DOT National Transportation Integrated Search
2014-12-01
Traffic Management Centers (TMCs) acquire, process, and integrate data in a variety of ways to support real-time operations. Crowdsourcing has been identified as one of the top trends and technologies that traffic management agencies can adapt and ta...
Supersonic market and economic analyses
NASA Technical Reports Server (NTRS)
Rochte, L. S.
1980-01-01
Advanced supersonic transport markets of the free world were projected for the period 1985 to 2004. Passenger traffic volume and airplane range and seat capacity requirements were estimated for Mach 2.2 service by international regional area market areas and by city pairs within and between these areas. Market factors and traffic factors examined include variable loads, growth rates, supersonic transport market shares, and schedule frequencies considering the different makeup of passenger traffic and individual city pairs. Direct, indirect, and total operating costs and yield levels were economically analyzed for first class and full fare economy class traffic.
DOT National Transportation Integrated Search
2017-12-01
For the incident response operations to be appreciated by the general public, it is essential that responsible highway agencies be capable of providing the estimated clearance duration of a detected incident at the level sufficiently reliable for mot...
Sensitivity analysis of the near-road dispersion model RLINE - An evaluation at Detroit, Michigan
NASA Astrophysics Data System (ADS)
Milando, Chad W.; Batterman, Stuart A.
2018-05-01
The development of accurate and appropriate exposure metrics for health effect studies of traffic-related air pollutants (TRAPs) remains challenging and important given that traffic has become the dominant urban exposure source and that exposure estimates can affect estimates of associated health risk. Exposure estimates obtained using dispersion models can overcome many of the limitations of monitoring data, and such estimates have been used in several recent health studies. This study examines the sensitivity of exposure estimates produced by dispersion models to meteorological, emission and traffic allocation inputs, focusing on applications to health studies examining near-road exposures to TRAP. Daily average concentrations of CO and NOx predicted using the Research Line source model (RLINE) and a spatially and temporally resolved mobile source emissions inventory are compared to ambient measurements at near-road monitoring sites in Detroit, MI, and are used to assess the potential for exposure measurement error in cohort and population-based studies. Sensitivity of exposure estimates is assessed by comparing nominal and alternative model inputs using statistical performance evaluation metrics and three sets of receptors. The analysis shows considerable sensitivity to meteorological inputs; generally the best performance was obtained using data specific to each monitoring site. An updated emission factor database provided some improvement, particularly at near-road sites, while the use of site-specific diurnal traffic allocations did not improve performance compared to simpler default profiles. Overall, this study highlights the need for appropriate inputs, especially meteorological inputs, to dispersion models aimed at estimating near-road concentrations of TRAPs. It also highlights the potential for systematic biases that might affect analyses that use concentration predictions as exposure measures in health studies.
DOT National Transportation Integrated Search
2001-06-30
Freight movements within large metropolitan areas are much less studied and analyzed than personal travel. This casts doubt on the results of much conventional travel demand modeling and planning. With so much traffic overlooked, how plausible are th...
Yao, Zhiliang; Zhang, Yingzhi; Shen, Xianbao; Wang, Xintong; Wu, Ye; He, Kebin
2013-01-01
To guarantee good traffic and air quality during the 16th Asian Games in Guangzhou, China, the government carried out two traffic control Drills before the Games and adopted traffic control measures during the Games. Vehicle activities before and during the first and second Drills, and during the Games, were surveyed. Based on the data under investigation, the impacts of control measures on traffic volumes and driving characteristics were analyzed during the first and second Drills, and the Games. The emission reduction of traffic control measures was also evaluated during the three stages using the MOBILE-China model. The results show that there were significant effects of implementing temporary traffic control measures on transportation activity and vehicular emissions. During the first and second Drills, and the Games, the average traffic volumes in monitored roads decreased, and the average speed of vehicles increased significantly The co-effects of traffic flow reduction, traffic congestion improvement, and the banning of high-emitting vehicles helped to greatly reduce the estimated emissions from motor vehicles in Guangzhou during the first and second Drills, and the Games. Estimated vehicular emissions were reduced by 38-52% during the first Drill and 28-36% for the second Drill. During the Asian Games, vehicular emissions of carbon monoxide (CO), hydrocarbon (HC), oxides of nitrogen (NO), and particulate matter with an aerodynamic diameter < 10 microm (PM10) reduced by an estimated 42%, 46%, 26%, and 30%, respectively, compared with those before the Games. Both the banning of high-emitting vehicles and the travel restrictions imposed by use of odd-even licenses had significant effects on the reduction of vehicular emissions of CO, HC, NOx, and PM10. Motor vehicles have become the most prevalent source of emissions and subsequently air pollution within Chinese cities. Understanding the impacts that different control measures have on vehicular emissions is very important in order to be able to control vehicle emissions. The results of this study will be very helpful for the further control of vehicle emissions in Guangzhou in the future. In addition, the effects of temporary transportation control measures will provide important awareness to other cities that will be hosting large-scale activities similar to the Asian Games.
Road traffic and childhood leukemia: the ESCALE study (SFCE).
Amigou, Alicia; Sermage-Faure, Claire; Orsi, Laurent; Leverger, Guy; Baruchel, André; Bertrand, Yves; Nelken, Brigitte; Robert, Alain; Michel, Gérard; Margueritte, Geneviève; Perel, Yves; Mechinaud, Françoise; Bordigoni, Pierre; Hémon, Denis; Clavel, Jacqueline
2011-04-01
Traffic is a source of environmental exposures, including benzene, which may be related to childhood leukemia. A national registry-based case-control study [ESCALE (Etude Sur les Cancers et les Leucémies de l'Enfant, Study on Environmental and Genetic Risk Factors of Childhood Cancers and Leukemia)] carried out in France was used to assess the effect of exposure to road traffic exhaust fumes on the risk of childhood leukemia. Over the study period, 2003-2004, 763 cases and 1,681 controls < 15 years old were included, and the controls were frequency matched with the cases on age and sex. The ESCALE data were collected by a standardized telephone interview of the mothers. Various indicators of exposure to traffic and pollution were determined using the geocoded addresses at the time of diagnosis for the cases and of interview for the controls. Indicators of the distance from, and density of, main roads and traffic nitrogen dioxide (NO(2)) concentrations derived from traffic emission data were used. Odds ratios (ORs) were estimated using unconditional regression models adjusted for potential confounders. Acute leukemia (AL) was significantly associated with estimates of traffic NO(2) concentration at the place of residence > 27.7 µg/m(3) compared with NO(2) concentration < 21.9 µg/m(3) [OR=1.2; confidence interval (CI), 1.0-1.5] and with the presence of a heavy-traffic road within 500 m compared with the absence of a heavy-traffic road in the same area (OR=2.0; 95% CI, 1.0-3.6). There was a significant association between AL and a high density of heavy-traffic roads within 500 m compared with the reference category with no heavy-traffic road within 500 m (OR=2.2; 95% CI, 1.1-4.2), with a significant positive linear trend of the association of AL with the total length of heavy-traffic road within 500 m. This study supports the hypothesis that living close to heavy-traffic roads may increase the risk of childhood leukemia.
Zhang, Kai; Batterman, Stuart A
2009-10-15
Traffic congestion increases air pollutant exposures of commuters and urban populations due to the increased time spent in traffic and the increased vehicular emissions that occur in congestion, especially "stop-and-go" traffic. Increased time in traffic also decreases time in other microenvironments, a trade-off that has not been considered in previous time activity pattern (TAP) analyses conducted for exposure assessment purposes. This research investigates changes in time allocations and exposures that result from traffic congestion. Time shifts were derived using data from the National Human Activity Pattern Survey (NHAPS), which was aggregated to nine microenvironments (six indoor locations, two outdoor locations and one transport location). After imputing missing values, handling outliers, and conducting other quality checks, these data were stratified by respondent age, employment status and period (weekday/weekend). Trade-offs or time-shift coefficients between time spent in vehicles and the eight other microenvironments were then estimated using robust regression. For children and retirees, congestion primarily reduced the time spent at home; for older children and working adults, congestion shifted the time spent at home as well as time in schools, public buildings, and other indoor environments. Changes in benzene and PM(2.5) exposure were estimated for the current average travel delay in the U.S. (9 min day(-1)) and other scenarios using the estimated time shifts coefficients, concentrations in key microenvironments derived from the literature, and a probabilistic analysis. Changes in exposures depended on the duration of the congestion and the pollutant. For example, a 30 min day(-1) travel delay was determined to account for 21+/-12% of current exposure to benzene and 14+/-8% of PM(2.5) exposure. The time allocation shifts and the dynamic approach to TAPs improve estimates of exposure impacts from congestion and other recurring events.
[Evidence-based effectiveness of road safety interventions: a literature review].
Novoa, Ana M; Pérez, Katherine; Borrell, Carme
2009-01-01
Only road safety interventions with scientific evidence supporting their effectiveness should be implemented. The objective of this study was to identify and summarize the available evidence on the effectiveness of road safety interventions in reducing road traffic collisions, injuries and deaths. All literature reviews published in scientific journals that assessed the effectiveness of one or more road safety interventions and whose outcome measure was road traffic crashes, injuries or fatalities were included. An exhaustive search was performed in scientific literature databases. The interventions were classified according to the evidence of their effectiveness in reducing road traffic injuries (effective interventions, insufficient evidence of effectiveness, ineffective interventions) following the structure of the Haddon matrix. Fifty-four reviews were included. Effective interventions were found before, during and after the collision, and across all factors: a) the individual: the graduated licensing system (31% road traffic injury reduction); b) the vehicle: electronic stability control system (2 to 41% reduction); c) the infrastructure: area-wide traffic calming (0 to 20%), and d) the social environment: speed cameras (7 to 30%). Certain road safety interventions are ineffective, mostly road safety education, and others require further investigation. The most successful interventions are those that reduce or eliminate the hazard and do not depend on changes in road users' behavior or on their knowledge of road safety issues. Interventions based exclusively on education are ineffective in reducing road traffic injuries.
Capacity Estimation Model for Signalized Intersections under the Impact of Access Point
Zhao, Jing; Li, Peng; Zhou, Xizhao
2016-01-01
Highway Capacity Manual 2010 provides various factors to adjust the base saturation flow rate for the capacity analysis of signalized intersections. No factors, however, is considered for the potential change of signalized intersections capacity caused by the access point closeing to the signalized intersection. This paper presented a theoretical model to estimate the lane group capacity at signalized intersections with the consideration of the effects of access points. Two scenarios of access point locations, upstream or downstream of the signalized intersection, and impacts of six types of access traffic flow are taken into account. The proposed capacity model was validated based on VISSIM simulation. Results of extensive numerical analysis reveal the substantial impact of access point on the capacity, which has an inverse correlation with both the number of major street lanes and the distance between the intersection and access point. Moreover, among the six types of access traffic flows, the access traffic flow 1 (right-turning traffic from major street), flow 4 (left-turning traffic from access point), and flow 5 (left-turning traffic from major street) cause a more significant effect on lane group capacity than others. Some guidance on the mitigation of the negative effect is provided for practitioners. PMID:26726998
DOT National Transportation Integrated Search
2012-12-01
Development and validation of a biographical data (biodata) instrument for selection into the Air Traffic : Control Specialist occupation is described. Bootstrapping was used to estimate correlations between item : responses to the Applicant Ba...
Measuring the effects of aborted takeoffs and landings on traffic flow at JFK
DOT National Transportation Integrated Search
2012-10-14
The FAA Office of Accident Investigation and Prevention (AVP) supports research, analysis and demonstration of quantitative air traffic analyses to estimate safety performance and benefits of the Next Generation Air Transportation System (NextGen). T...
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...
Information on estimating local government highway bonds
DOT National Transportation Integrated Search
1973-06-01
The theory of traffic flow following a lane blockage on a multi-lane freeway has been developed. Numerical results have been obtained and are presented both for the steady state case where the traffic density remains constant and the non-steady state...
Traffic signal operations and maintenance staffing guidelines
DOT National Transportation Integrated Search
2009-03-01
This report provides a guideline to estimate the staffing and resource needs required to effectively operate and maintain traffic signal systems. The results of a survey performed under this project, as well as a review of the literature and other su...
A framework for the nationwide multimode transportation demand analysis.
DOT National Transportation Integrated Search
2010-09-01
This study attempts to analyze the impact of traffic on the US highway system considering both passenger vehicles and : trucks. For the analysis, a pseudo-dynamic traffic assignment model is proposed to estimate the time-dependent link flow : from th...
Han, Fang; Liu, Han
2017-02-01
Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.
Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.
Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush
2016-08-01
This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.
The Loss of Efficiency Caused by Agents’ Uncoordinated Routing in Transport Networks
Wang, Junjie; Wang, Pu
2014-01-01
Large-scale daily commuting data were combined with detailed geographical information system (GIS) data to analyze the loss of transport efficiency caused by drivers’ uncoordinated routing in urban road networks. We used Price of Anarchy (POA) to quantify the loss of transport efficiency and found that both volume and distribution of human mobility demand determine the POA. In order to reduce POA, a small number of highways require considerable decreases in traffic, and their neighboring arterial roads need to attract more traffic. The magnitude of the adjustment in traffic flow can be estimated using the fundamental measure traffic flow only, which is widely available and easy to collect. Surprisingly, the most congested roads or the roads with largest traffic flow were not those requiring the most reduction of traffic. This study can offer guidance for the optimal control of urban traffic and facilitate improvements in the efficiency of transport networks. PMID:25349995
Ozaki, N; Tokumitsu, H; Kojima, K; Kindaichi, T
2007-01-01
In order to consider the total atmospheric loadings of the PAHs (polycyclic aromatic hydrocarbons) from traffic activities, the emission factors of PAHs were estimated and from the obtained emission factors and vehicle transportation statistics, total atmospheric loadings were integrated and the loadings into the water body were estimated on a regional scale. The atmospheric concentration of PAHs was measured at the roadside of a road with heavy traffic in the Hiroshima area in Japan. The samplings were conducted in summer and winter. Atmospheric particulate matters (fine particle, 0.6-7 microm; coarse particle, over 7 microm) and their PAH concentration were measured. Also, four major emission sources (gasoline and diesel vehicle emissions, tire and asphalt debris) were assumed for vehicle transportation activities, the chemical mass balance method was applied and the source partitioning at the roadside was estimated. Furthermore, the dispersion of atmospheric particles from the vehicles was modelled and the emission factors of the sources were determined by the comparison to the chemical mass balance results. Based on emission factors derived from the modelling, an atmospheric dispersion model of nationwide scale (National Institute of Advanced Industrial Science and Technology - Atmospheric Dispersion Model for Exposure and Risk assessment) was applied, and the atmospheric concentration and loading to the ground were calculated for the Hiroshima Bay watershed area.
Analysis of estimation algorithms for CDTI and CAS applications
NASA Technical Reports Server (NTRS)
Goka, T.
1985-01-01
Estimation algorithms for Cockpit Display of Traffic Information (CDTI) and Collision Avoidance System (CAS) applications were analyzed and/or developed. The algorithms are based on actual or projected operational and performance characteristics of an Enhanced TCAS II traffic sensor developed by Bendix and the Federal Aviation Administration. Three algorithm areas are examined and discussed. These are horizontal x and y, range and altitude estimation algorithms. Raw estimation errors are quantified using Monte Carlo simulations developed for each application; the raw errors are then used to infer impacts on the CDTI and CAS applications. Applications of smoothing algorithms to CDTI problems are also discussed briefly. Technical conclusions are summarized based on the analysis of simulation results.
Full-chain health impact assessment of traffic-related air pollution and childhood asthma.
Khreis, Haneen; de Hoogh, Kees; Nieuwenhuijsen, Mark J
2018-05-01
Asthma is the most common chronic disease in children. Traffic-related air pollution (TRAP) may be an important exposure contributing to its development. In the UK, Bradford is a deprived city suffering from childhood asthma rates higher than national and regional averages and TRAP is of particular concern to the local communities. We estimated the burden of childhood asthma attributable to air pollution and specifically TRAP in Bradford. Air pollution exposures were estimated using a newly developed full-chain exposure assessment model and an existing land-use regression model (LUR). We estimated childhood population exposure to NO x and, by conversion, NO 2 at the smallest census area level using a newly developed full-chain model knitting together distinct traffic (SATURN), vehicle emission (COPERT) and atmospheric dispersion (ADMS-Urban) models. We compared these estimates with measurements and estimates from ESCAPE's LUR model. Using the UK incidence rate for childhood asthma, meta-analytical exposure-response functions, and estimates from the two exposure models, we estimated annual number of asthma cases attributable to NO 2 and NO x in Bradford, and annual number of asthma cases specifically attributable to traffic. The annual average census tract levels of NO 2 and NO x estimated using the full-chain model were 15.41 and 25.68 μg/m 3 , respectively. On average, 2.75 μg/m 3 NO 2 and 4.59 μg/m 3 NO x were specifically contributed by traffic, without minor roads and cold starts. The annual average census tract levels of NO 2 and NO x estimated using the LUR model were 21.93 and 35.60 μg/m 3 , respectively. The results indicated that up to 687 (or 38% of all) annual childhood asthma cases in Bradford may be attributable to air pollution. Up to 109 cases (6%) and 219 cases (12%) may be specifically attributable to TRAP, with and without minor roads and cold starts, respectively. This is the first study undertaking full-chain health impact assessment of TRAP and childhood asthma in a disadvantaged population with public concern about TRAP. It further adds to scarce literature exploring the impact of different exposure assessments. In conservative estimates, air pollution and TRAP are estimated to cause a large, but largely preventable, childhood asthma burden. Future progress with childhood asthma requires a move beyond the prevalent disease control-based approach toward asthma prevention. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Yan, Ying; Zhang, Shen; Tang, Jinjun; Wang, Xiaofei
2017-07-01
Discovering dynamic characteristics in traffic flow is the significant step to design effective traffic managing and controlling strategy for relieving traffic congestion in urban cities. A new method based on complex network theory is proposed to study multivariate traffic flow time series. The data were collected from loop detectors on freeway during a year. In order to construct complex network from original traffic flow, a weighted Froenius norm is adopt to estimate similarity between multivariate time series, and Principal Component Analysis is implemented to determine the weights. We discuss how to select optimal critical threshold for networks at different hour in term of cumulative probability distribution of degree. Furthermore, two statistical properties of networks: normalized network structure entropy and cumulative probability of degree, are utilized to explore hourly variation in traffic flow. The results demonstrate these two statistical quantities express similar pattern to traffic flow parameters with morning and evening peak hours. Accordingly, we detect three traffic states: trough, peak and transitional hours, according to the correlation between two aforementioned properties. The classifying results of states can actually represent hourly fluctuation in traffic flow by analyzing annual average hourly values of traffic volume, occupancy and speed in corresponding hours.
NASA Astrophysics Data System (ADS)
Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.
2011-06-01
For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.
Development of a guideline for work zone diversion rate and capacity reduction.
DOT National Transportation Integrated Search
2016-03-01
This study develops a comprehensive guideline to estimate the traffic diversion rates and capacity reduction for : work zones. The analysis of the traffic diversion patterns with data from past work zones in the metro freeway : network in Minnesota r...
Older drivers, the age factor in traffic safety
DOT National Transportation Integrated Search
1989-02-01
The report presents an overview of the traffic safety problem in relation to the age of the driver. Emphasis is placed on the older drivers. Crash involvement rates are developed for each age group of drivers based on their estimated annual travel. T...
Freeway travel time estimation using existing fixed traffic sensors : phase 1.
DOT National Transportation Integrated Search
2013-08-01
Freeway travel time is one of the most useful pieces of information for road users and an : important measure of effectiveness (MOE) for traffic engineers and policy makers. In the Greater : St. Louis area, Gateway Guide, the St. Louis Transportation...
Generic Vehicle Speed Models Based On Traffic Simulation: Development and Application (Revision #1)
DOT National Transportation Integrated Search
1994-12-15
The findings of a research project to develop new methods of estimating speeds for inclusion in the Highway Performance Monitoring System (HPMS) Analytical Process are summarized. The paper focuses on the effects of traffic conditions excluding incid...
NASA Astrophysics Data System (ADS)
Kuik, Friderike; Lauer, Axel; von Schneidemesser, Erika; Butler, Tim
2017-04-01
Many European cities continue to struggle with meeting the European air quality limits for NO2. In Berlin, Germany, most of the exceedances in NO2 recorded at monitoring sites near busy roads can be largely attributed to emissions from traffic. In order to assess the impact of changes in traffic emissions on air quality at policy relevant scales, we combine the regional atmosphere-chemistry transport model WRF-Chem at a resolution of 1kmx1km with a statistical downscaling approach. Here, we build on the recently published study evaluating the performance of a WRF-Chem setup in representing observed urban background NO2 concentrations from Kuik et al. (2016) and extend this setup by developing and testing an approach to statistically downscale simulated urban background NO2 concentrations to street level. The approach uses a multilinear regression model to relate roadside NO2 concentrations observed with the municipal monitoring network with observed NO2 concentrations at urban background sites and observed traffic counts. For this, the urban background NO2 concentrations are decomposed into a long term, a synoptic and a diurnal component using the Kolmogorov-Zurbenko filtering method. We estimate the coefficients of the regression model for five different roadside stations in Berlin representing different street types. In a next step we combine the coefficients with simulated urban background concentrations and observed traffic counts, in order to estimate roadside NO2 concentrations based on the results obtained with WRF-Chem at the five selected stations. In a third step, we extrapolate the NO2 concentrations to all major roads in Berlin. The latter is based on available data for Berlin of daily mean traffic counts, diurnal and weekly cycles of traffic as well as simulated urban background NO2 concentrations. We evaluate the NO2 concentrations estimated with this method at street level for Berlin with additional observational data from stationary measurements and mobile measurements conducted during a campaign in summer 2014. The results show that this approach allows us to estimate NO2 concentrations at roadside reasonably well. The approach can be applied when observations show a strong correlation between roadside NO2 concentrations and traffic emissions from a single type of road. The method, however, shows weaknesses for intersections where observed NO2 concentrations are influenced by traffic on several different roads. We then apply this downscaling approach to estimate the impact of different traffic emission scenarios both on urban background and street level NO2 concentrations. References Kuik, F., Lauer, A., Churkina, G., Denier van der Gon, H. A. C., Fenner, D., Mar, K. A., and Butler, T. M.: Air quality modelling in the Berlin-Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data, Geosci. Model Dev., 9, 4339-4363, doi:10.5194/gmd-9-4339-2016, 2016.
NASA Technical Reports Server (NTRS)
Consiglio, Maria C.; Hoadley, Sherwood T.; Allen, B. Danette
2009-01-01
Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.
NASA Astrophysics Data System (ADS)
Laña, Ibai; Del Ser, Javier; Padró, Ales; Vélez, Manuel; Casanova-Mateo, Carlos
2016-11-01
Urban air pollution is a matter of growing concern for both public administrations and citizens. Road traffic is one of the main sources of air pollutants, though topography characteristics and meteorological conditions can make pollution levels increase or diminish dramatically. In this context an upsurge of research has been conducted towards functionally linking variables of such domains to measured pollution data, with studies dealing with up to one-hour resolution meteorological data. However, the majority of such reported contributions do not deal with traffic data or, at most, simulate traffic conditions jointly with the consideration of different topographical features. The aim of this study is to further explore this relationship by using high-resolution real traffic data. This paper describes a methodology based on the construction of regression models to predict levels of different pollutants (i.e. CO, NO, NO2, O3 and PM10) based on traffic data and meteorological conditions, from which an estimation of the predictive relevance (importance) of each utilized feature can be estimated by virtue of their particular training procedure. The study was made with one hour resolution meteorological, traffic and pollution historic data in roadside and background locations of the city of Madrid (Spain) captured over 2015. The obtained results reveal that the impact of vehicular emissions on the pollution levels is overshadowed by the effects of stable meteorological conditions of this city.
Eriksson, Charlotta; Bodin, Theo; Selander, Jenny
2017-11-01
Objectives National quantifications of the health burden related to traffic noise are still rare. In this study, we use disability-adjusted life-years (DALY) measure to assess the burden of disease from road traffic and railway noise in Sweden. Methods The number of DALY was assessed for annoyance, sleep disturbance, hypertension, myocardial infarction (MI) and stroke using a method previously implemented by the World Health Organization (WHO). Population exposure to noise was obtained from the Swedish Environmental Protection Agency and the Swedish Transport Administration. Data on disease occurrence were gathered from registers held by the National Board of Health and Welfare and Statistics Sweden. Disability weights (DW) and duration were based on WHO definitions. Finally, we used research-based exposure-response functions or relative risks to estimate disease attributable to noise in each exposure category. Results The number of DALY attributed to traffic noise in Sweden was estimated to be 41 033 years; 36 711 (90%) related to road traffic and 4322 (10%) related to railway traffic. The most important contributor to the disease burden was sleep disturbances, accounting for 22 218 DALY (54%), followed by annoyance, 12 090 DALY (30%), and cardiovascular diseases, 6725 DALY (16%). Conclusions Road traffic and railway noise contribute significantly to the burden of disease in Sweden each year. The total number of DALY should, however, be interpreted with caution due to limitations in data quality.
Prediction of Traffic Complexity and Controller Workload in Mixed Equipage NextGen Environments
NASA Technical Reports Server (NTRS)
Lee, Paul U.; Prevot, Thomas
2012-01-01
Controller workload is a key factor in limiting en route air traffic capacity. Past efforts to quantify and predict workload have resulted in identifying objective metrics that correlate well with subjective workload ratings during current air traffic control operations. Although these metrics provide a reasonable statistical fit to existing data, they do not provide a good mechanism for estimating controller workload for future air traffic concepts and environments that make different assumptions about automation, enabling technologies, and controller tasks. One such future environment is characterized by en route airspace with a mixture of aircraft equipped with and without Data Communications (Data Comm). In this environment, aircraft with Data Comm will impact controller workload less than aircraft requiring voice communication, altering the close correlation between aircraft count and controller workload that exists in current air traffic operations. This paper outlines a new trajectory-based complexity (TBX) calculation that was presented to controllers during a human-in-the-loop simulation. The results showed that TBX accurately estimated the workload in a mixed Data Comm equipage environment and the resulting complexity values were understood and readily interpreted by the controllers. The complexity was represented as a "modified aircraft account" that weighted different complexity factors and summed them in such a way that the controllers could effectively treat them as aircraft count. The factors were also relatively easy to tune without an extensive data set. The results showed that the TBX approach is well suited for presenting traffic complexity in future air traffic environments.
Modeling of road traffic noise and estimated human exposure in Fulton County, Georgia, USA.
Seong, Jeong C; Park, Tae H; Ko, Joon H; Chang, Seo I; Kim, Minho; Holt, James B; Mehdi, Mohammed R
2011-11-01
Environmental noise is a major source of public complaints. Noise in the community causes physical and socio-economic effects and has been shown to be related to adverse health impacts. Noise, however, has not been actively researched in the United States compared with the European Union countries in recent years. In this research, we aimed at modeling road traffic noise and analyzing human exposure in Fulton County, Georgia, United States. We modeled road traffic noise levels using the United States Department of Transportation Federal Highway Administration Traffic Noise Model implemented in SoundPLAN®. After analyzing noise levels with raster, vector and façade maps, we estimated human exposure to high noise levels. Accurate digital elevation models and building heights were derived from Light Detection And Ranging survey datasets and building footprint boundaries. Traffic datasets were collected from the Georgia Department of Transportation and the Atlanta Regional Commission. Noise level simulation was performed with 62 computers in a distributed computing environment. Finally, the noise-exposed population was calculated using geographic information system techniques. Results show that 48% of the total county population [N=870,166 residents] is potentially exposed to 55 dB(A) or higher noise levels during daytime. About 9% of the population is potentially exposed to 67 dB(A) or higher noises. At nighttime, 32% of the population is expected to be exposed to noise levels higher than 50 dB(A). This research shows that large-scale traffic noise estimation is possible with the help of various organizations. We believe that this research is a significant stepping stone for analyzing community health associated with noise exposures in the United States. Copyright © 2011 Elsevier Ltd. All rights reserved.
Méline, Julie; Van Hulst, Andraea; Thomas, Frederique; Chaix, Basile
2015-01-01
Associations between road traffic noise and hypertension have been repeatedly documented, whereas associations with rail or total road, rail, and air (RRA) traffic noise have rarely been investigated. Moreover, most studies of noise in the environment have only taken into account the residential neighborhood. Finally, few studies have taken into account individual/neighborhood confounders in the relationship between noise and hypertension. We performed adjusted multilevel regression analyses using data from the 7,290 participants of the RECORD Study to investigate the associations of outdoor road, rail, air, and RRA traffic noise estimated at the place of residence, at the workplace, and in the neighborhoods around the residence and workplace with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension. Associations were documented between higher outdoor RRA and road traffic noise estimated at the workplace and a higher SBP [+1.36 mm of mercury, 95% confidence interval (CI): +0.12, +2.60 for 65-80 dB(A) vs 30-45 dB(A)] and DBP [+1.07 (95% CI: +0.28, +1.86)], after adjustment for individual/neighborhood confounders. These associations remained after adjustment for risk factors of hypertension. Associations were documented neither with rail traffic noise nor for hypertension. Associations between transportation noise at the workplace and blood pressure (BP) may be attributable to the higher levels of road traffic noise at the workplace than at the residence. To better understand why only noise estimated at the workplace was associated with BP, our future work will combine Global Positioning System (GPS) tracking, assessment of noise levels with sensors, and ambulatory monitoring of BP. PMID:26356373
Méline, Julie; Van Hulst, Andraea; Thomas, Frederique; Chaix, Basile
2015-01-01
Associations between road traffic noise and hypertension have been repeatedly documented, whereas associations with rail or total road, rail, and air (RRA) traffic noise have rarely been investigated. Moreover, most studies of noise in the environment have only taken into account the residential neighborhood. Finally, few studies have taken into account individual/neighborhood confounders in the relationship between noise and hypertension. We performed adjusted multilevel regression analyses using data from the 7,290 participants of the RECORD Study to investigate the associations of outdoor road, rail, air, and RRA traffic noise estimated at the place of residence, at the workplace, and in the neighborhoods around the residence and workplace with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension. Associations were documented between higher outdoor RRA and road traffic noise estimated at the workplace and a higher SBP [+1.36 mm of mercury, 95% confidence interval (CI): +0.12, +2.60 for 65-80 dB(A) vs 30-45 dB(A)] and DBP [+1.07 (95% CI: +0.28, +1.86)], after adjustment for individual/neighborhood confounders. These associations remained after adjustment for risk factors of hypertension. Associations were documented neither with rail traffic noise nor for hypertension. Associations between transportation noise at the workplace and blood pressure (BP) may be attributable to the higher levels of road traffic noise at the workplace than at the residence. To better understand why only noise estimated at the workplace was associated with BP, our future work will combine Global Positioning System (GPS) tracking, assessment of noise levels with sensors, and ambulatory monitoring of BP.
Transportation noise and annoyance related to road traffic in the French RECORD study
2013-01-01
Road traffic and related noise is a major source of annoyance and impairment to health in urban areas. Many areas exposed to road traffic noise are also exposed to rail and air traffic noise. The resulting annoyance may depend on individual/neighborhood socio-demographic factors. Nevertheless, few studies have taken into account the confounding or modifying factors in the relationship between transportation noise and annoyance due to road traffic. In this study, we address these issues by combining Geographic Information Systems and epidemiologic methods. Street network buffers with a radius of 500 m were defined around the place of residence of the 7290 participants of the RECORD Cohort in Ile-de-France. Estimated outdoor traffic noise levels (road, rail, and air separately) were assessed at each place of residence and in each of these buffers. Higher levels of exposure to noise were documented in low educated neighborhoods. Multilevel logistic regression models documented positive associations between road traffic noise and annoyance due to road traffic, after adjusting for individual/neighborhood socioeconomic conditions. There was no evidence that the association was of different magnitude when noise was measured at the place of residence or in the residential neighborhood. However, the strength of the association between neighborhood noise exposure and annoyance increased when considering a higher percentile in the distribution of noise in each neighborhood. Road traffic noise estimated at the place of residence and road traffic noise in the residential neighborhood (75th percentile) were independently associated with annoyance, when adjusted for each other. Interactions of effects indicated that the relationship between road traffic noise exposure in the residential neighborhood and annoyance was stronger in affluent and high educated neighborhoods. Overall, our findings suggest that it is useful to take into account (i) the exposure to transportation noise in the residential neighborhood rather than only at the residence, (ii) different percentiles of noise exposure in the residential neighborhood, and (iii) the socioeconomic characteristics of the residential neighborhood to explain variations in annoyance due to road traffic in the neighborhood. PMID:24088229
Urban scale air quality modelling using detailed traffic emissions estimates
NASA Astrophysics Data System (ADS)
Borrego, C.; Amorim, J. H.; Tchepel, O.; Dias, D.; Rafael, S.; Sá, E.; Pimentel, C.; Fontes, T.; Fernandes, P.; Pereira, S. R.; Bandeira, J. M.; Coelho, M. C.
2016-04-01
The atmospheric dispersion of NOx and PM10 was simulated with a second generation Gaussian model over a medium-size south-European city. Microscopic traffic models calibrated with GPS data were used to derive typical driving cycles for each road link, while instantaneous emissions were estimated applying a combined Vehicle Specific Power/Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (VSP/EMEP) methodology. Site-specific background concentrations were estimated using time series analysis and a low-pass filter applied to local observations. Air quality modelling results are compared against measurements at two locations for a 1 week period. 78% of the results are within a factor of two of the observations for 1-h average concentrations, increasing to 94% for daily averages. Correlation significantly improves when background is added, with an average of 0.89 for the 24 h record. The results highlight the potential of detailed traffic and instantaneous exhaust emissions estimates, together with filtered urban background, to provide accurate input data to Gaussian models applied at the urban scale.
Liu, Shi V; Chen, Fu-Lin; Xue, Jianping
2017-12-15
An important factor in evaluating health risk of near-road air pollution is to accurately estimate the traffic-related vehicle emission of air pollutants. Inclusion of traffic parameters such as road length/area, distance to roads, and traffic volume/intensity into models such as land use regression (LUR) models has improved exposure estimation. To better understand the relationship between vehicle emissions and near-road air pollution, we evaluated three traffic density-based indices: Major-Road Density (MRD), All-Traffic Density (ATD) and Heavy-Traffic Density (HTD) which represent the proportions of major roads, major road with annual average daily traffic (AADT), and major road with commercial annual average daily traffic (CAADT) in a buffered area, respectively. We evaluated the potential of these indices as vehicle emission-specific near-road air pollutant indicators by analyzing their correlation with black carbon (BC), a marker for mobile source air pollutants, using measurement data obtained from the Near-road Exposures and Effects of Urban Air Pollutants Study (NEXUS). The average BC concentrations during a day showed variations consistent with changes in traffic volume which were classified into high, medium, and low for the morning rush hours, the evening rush hours, and the rest of the day, respectively. The average correlation coefficients between BC concentrations and MRD, ATD, and HTD, were 0.26, 0.18, and 0.48, respectively, as compared with -0.31 and 0.25 for two commonly used traffic indicators: nearest distance to a major road and total length of the major road. HTD, which includes only heavy-duty diesel vehicles in its traffic count, gives statistically significant correlation coefficients for all near-road distances (50, 100, 150, 200, 250, and 300 m) that were analyzed. Generalized linear model (GLM) analyses show that season, traffic volume, HTD, and distance from major roads are highly related to BC measurements. Our analyses indicate that traffic density parameters may be more specific indicators of near-road BC concentrations for health risk studies. HTD is the best index for reflecting near-road BC concentrations which are influenced mainly by the emissions of heavy-duty diesel engines.
Chen, Fu-Lin; Xue, Jianping
2017-01-01
An important factor in evaluating health risk of near-road air pollution is to accurately estimate the traffic-related vehicle emission of air pollutants. Inclusion of traffic parameters such as road length/area, distance to roads, and traffic volume/intensity into models such as land use regression (LUR) models has improved exposure estimation. To better understand the relationship between vehicle emissions and near-road air pollution, we evaluated three traffic density-based indices: Major-Road Density (MRD), All-Traffic Density (ATD) and Heavy-Traffic Density (HTD) which represent the proportions of major roads, major road with annual average daily traffic (AADT), and major road with commercial annual average daily traffic (CAADT) in a buffered area, respectively. We evaluated the potential of these indices as vehicle emission-specific near-road air pollutant indicators by analyzing their correlation with black carbon (BC), a marker for mobile source air pollutants, using measurement data obtained from the Near-road Exposures and Effects of Urban Air Pollutants Study (NEXUS). The average BC concentrations during a day showed variations consistent with changes in traffic volume which were classified into high, medium, and low for the morning rush hours, the evening rush hours, and the rest of the day, respectively. The average correlation coefficients between BC concentrations and MRD, ATD, and HTD, were 0.26, 0.18, and 0.48, respectively, as compared with −0.31 and 0.25 for two commonly used traffic indicators: nearest distance to a major road and total length of the major road. HTD, which includes only heavy-duty diesel vehicles in its traffic count, gives statistically significant correlation coefficients for all near-road distances (50, 100, 150, 200, 250, and 300 m) that were analyzed. Generalized linear model (GLM) analyses show that season, traffic volume, HTD, and distance from major roads are highly related to BC measurements. Our analyses indicate that traffic density parameters may be more specific indicators of near-road BC concentrations for health risk studies. HTD is the best index for reflecting near-road BC concentrations which are influenced mainly by the emissions of heavy-duty diesel engines. PMID:29244754
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.
Sacks, G; Veerman, J L; Moodie, M; Swinburn, B
2011-07-01
Cost-effectiveness analyses are important tools in efforts to prioritise interventions for obesity prevention. Modelling facilitates evaluation of multiple scenarios with varying assumptions. This study compares the cost-effectiveness of conservative scenarios for two commonly proposed policy-based interventions: front-of-pack 'traffic-light' nutrition labelling (traffic-light labelling) and a tax on unhealthy foods ('junk-food' tax). For traffic-light labelling, estimates of changes in energy intake were based on an assumed 10% shift in consumption towards healthier options in four food categories (breakfast cereals, pastries, sausages and preprepared meals) in 10% of adults. For the 'junk-food' tax, price elasticities were used to estimate a change in energy intake in response to a 10% price increase in seven food categories (including soft drinks, confectionery and snack foods). Changes in population weight and body mass index by sex were then estimated based on these changes in population energy intake, along with subsequent impacts on disability-adjusted life years (DALYs). Associated resource use was measured and costed using pathway analysis, based on a health sector perspective (with some industry costs included). Costs and health outcomes were discounted at 3%. The cost-effectiveness of each intervention was modelled for the 2003 Australian adult population. Both interventions resulted in reduced mean weight (traffic-light labelling: 1.3 kg (95% uncertainty interval (UI): 1.2; 1.4); 'junk-food' tax: 1.6 kg (95% UI: 1.5; 1.7)); and DALYs averted (traffic-light labelling: 45,100 (95% UI: 37,700; 60,100); 'junk-food' tax: 559,000 (95% UI: 459,500; 676,000)). Cost outlays were AUD81 million (95% UI: 44.7; 108.0) for traffic-light labelling and AUD18 million (95% UI: 14.4; 21.6) for 'junk-food' tax. Cost-effectiveness analysis showed both interventions were 'dominant' (effective and cost-saving). Policy-based population-wide interventions such as traffic-light nutrition labelling and taxes on unhealthy foods are likely to offer excellent 'value for money' as obesity prevention measures.
Han, Fang; Liu, Han
2016-01-01
Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson’s sample correlation matrix. Although Pearson’s sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall’s tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall’s tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall’s tau correlation matrix and the latent Pearson’s correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of “effective rank” in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a “sign subgaussian condition” which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition. PMID:28337068
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.
Introduction: Traffic-related air pollution has been associated with numerous adverse outcomes. However, community health studies of traffic-related air pollution have been hampered by the cost and participant burden associated with estimating household-level exposure through te...
Air Quality Modeling of Traffic-related Air Pollutants for the NEXUS Study
The paper presents the results of the model applications to estimate exposure metrics in support of an epidemiologic study in Detroit, Michigan. A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characteriz...
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...
Training of U.S. Air Traffic Controllers. (IDA Report No. R-206).
ERIC Educational Resources Information Center
Henry, James H.; And Others
The report reviews the evolution of existing national programs for air traffic controller training, estimates the number of persons requiring developmental and supplementary training, examines present controller selection and training programs, investigates performance measurement methods, considers standardization and quality control, discusses…
Analysis of Air Traffic Track Data with the AutoBayes Synthesis System
NASA Technical Reports Server (NTRS)
Schumann, Johann Martin Philip; Cate, Karen; Lee, Alan G.
2010-01-01
The Next Generation Air Traffic System (NGATS) is aiming to provide substantial computer support for the air traffic controllers. Algorithms for the accurate prediction of aircraft movements are of central importance for such software systems but trajectory prediction has to work reliably in the presence of unknown parameters and uncertainties. We are using the AutoBayes program synthesis system to generate customized data analysis algorithms that process large sets of aircraft radar track data in order to estimate parameters and uncertainties. In this paper, we present, how the tasks of finding structure in track data, estimation of important parameters in climb trajectories, and the detection of continuous descent approaches can be accomplished with compact task-specific AutoBayes specifications. We present an overview of the AutoBayes architecture and describe, how its schema-based approach generates customized analysis algorithms, documented C/C++ code, and detailed mathematical derivations. Results of experiments with actual air traffic control data are discussed.
Collarile, Paolo; Gobbino, Iliana; Tripani, Nicola; Zeriali, Luca; Dimai, Matteo; Valent, Francesca
2014-01-01
to estimate the health impact of road traffic accidents in the Friuli Venezia Giulia Region, Northeastern Italy. burden of disease (BoD) study. we used data on road traffic accidents collected by the Police in the Friuli Venezia Giulia in 2010 and health data regarding Emergency Room visits, hospital admissions, and deaths. we calculated the Disability Adjusted Life Years (DALY) lost because of road traffic accidents. The kernel density of the DALYs in the region was analyzed and mapped. it was estimated that 3,861 DALYs were lost in 2010. Years lost because of premature deaths outnumbered those lost because of disability. The highest number of DALYs was lost among 15-44-year-old males. Of 14,361 injured persons included in the analysis, only 4,357 were found in the Police database. However, these injuries accounted for 95% of all the DALYs. the present study identified population subgroups with a particularly high impact of road traffic accidents. Educational and Police interventions to prevent accidents should be addressed to those subgroups. In the future, repeating this analysis will allow an evaluation of the effectiveness of preventive interventions in terms of health gains.
A preliminary estimate of future communications traffic for the electric power system
NASA Technical Reports Server (NTRS)
Barnett, R. M.
1981-01-01
Diverse new generator technologies using renewable energy, and to improve operational efficiency throughout the existing electric power systems are presented. A description of a model utility and the information transfer requirements imposed by incorporation of dispersed storage and generation technologies and implementation of more extensive energy management are estimated. An example of possible traffic for an assumed system, and an approach that can be applied to other systems, control configurations, or dispersed storage and generation penetrations is provided.
NASA Astrophysics Data System (ADS)
Brewick, P. T.; Smyth, A. W.
2014-12-01
The accurate and reliable estimation of modal damping from output-only vibration measurements of structural systems is a continuing challenge in the fields of operational modal analysis (OMA) and system identification. In this paper a modified version of the blind source separation (BSS)-based Second-Order Blind Identification (SOBI) method was used to perform modal damping identification on a model bridge structure under varying loading conditions. The bridge model was created with finite elements and consisted of a series of stringer beams supported by a larger girder. The excitation was separated into two categories: ambient noise and traffic loads with noise modeled with random forcing vectors and traffic simulated with moving loads for cars and partially distributed moving masses for trains. The acceleration responses were treated as the mixed output signals for the BSS algorithm. The modified SOBI method used a windowing technique to maximize the amount of information used for blind identification from the responses. The modified SOBI method successfully found the mode shapes for both types of excitation with strong accuracy, but power spectral densities (PSDs) of the recovered modal responses showed signs of distortion for the traffic simulations. The distortion had an adverse affect on the damping ratio estimates for some of the modes but no correlation could be found between the accuracy of the damping estimates and the accuracy of the recovered mode shapes. The responses and their PSDs were compared to real-world collected data and patterns similar to distortion were observed implying that this issue likely affects real-world estimates.
Wu, Jun; Wilhelm, Michelle; Chung, Judith; Ritz, Beate
2011-07-01
Previous studies reported adverse impacts of traffic-related air pollution exposure on pregnancy outcomes. Yet, little information exists on how effect estimates are impacted by the different exposure assessment methods employed in these studies. To compare effect estimates for traffic-related air pollution exposure and preeclampsia, preterm birth (gestational age less than 37 weeks), and very preterm birth (gestational age less than 30 weeks) based on four commonly used exposure assessment methods. We identified 81,186 singleton births during 1997-2006 at four hospitals in Los Angeles and Orange Counties, California. Exposures were assigned to individual subjects based on residential address at delivery using the nearest ambient monitoring station data [carbon monoxide (CO), nitrogen dioxide (NO(2)), nitric oxide (NO), nitrogen oxides (NO(x)), ozone (O(3)), and particulate matter less than 2.5 (PM(2.5)) or less than 10 (PM(10))μm in aerodynamic diameter], both unadjusted and temporally adjusted land-use regression (LUR) model estimates (NO, NO(2), and NO(x)), CALINE4 line-source air dispersion model estimates (NO(x) and PM(2.5)), and a simple traffic-density measure. We employed unconditional logistic regression to analyze preeclampsia in our birth cohort, while for gestational age-matched risk sets with preterm and very preterm birth we employed conditional logistic regression. We observed elevated risks for preeclampsia, preterm birth, and very preterm birth from maternal exposures to traffic air pollutants measured at ambient stations (CO, NO, NO(2), and NO(x)) and modeled through CALINE4 (NO(x) and PM(2.5)) and LUR (NO(2) and NO(x)). Increased risk of preterm birth and very preterm birth were also positively associated with PM(10) and PM(2.5) air pollution measured at ambient stations. For LUR-modeled NO(2) and NO(x) exposures, elevated risks for all the outcomes were observed in Los Angeles only--the region for which the LUR models were initially developed. Unadjusted LUR models often produced odds ratios somewhat larger in size than temporally adjusted models. The size of effect estimates was smaller for exposures based on simpler traffic density measures than the other exposure assessment methods. We generally confirmed that traffic-related air pollution was associated with adverse reproductive outcomes regardless of the exposure assessment method employed, yet the size of the estimated effect depended on how both temporal and spatial variations were incorporated into exposure assessment. The LUR model was not transferable even between two contiguous areas within the same large metropolitan area in Southern California. Copyright © 2011 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Kim, Eugene; Hopke, Philip K.; Edgerton, Eric S.
Daily integrated PM 2.5 (particulate matter ⩽2.5 μm in aerodynamic diameter) composition data including eight individual carbon fractions collected at the Jefferson Street monitoring site in Atlanta were analyzed with positive matrix factorization (PMF). Particulate carbon was analyzed using the thermal optical reflectance method that divides carbon into four organic carbon (OC), pyrolized organic carbon (OP), and three elemental carbon (EC) fractions. A total of 529 samples and 28 variables were measured between August 1998 and August 2000. PMF identified 11 sources in this study: sulfate-rich secondary aerosol I (50%), on-road diesel emissions (11%), nitrate-rich secondary aerosol (9%), wood smoke (7%), gasoline vehicle (6%), sulfate-rich secondary aerosol II (6%), metal processing (3%), airborne soil (3%), railroad traffic (3%), cement kiln/carbon-rich (2%), and bus maintenance facility/highway traffic (2%). Differences from previous studies using only the traditional OC and EC data (J. Air Waste Manag. Assoc. 53(2003a)731; Atmos Environ. (2003b)) include four traffic-related combustion sources (gasoline vehicle, on-road diesel, railroad, and bus maintenance facility) containing carbon fractions whose abundances were different between the various sources. This study indicates that the temperature resolved fractional carbon data can be utilized to enhance source apportionment study, especially with respect to the separation of diesel emissions from gasoline vehicle sources. Conditional probability functions using surface wind data and identified source contributions aid the identifications of local point sources.
Dzhambov, Angel M; Dimitrova, Donka D
2015-03-01
Road traffic noise is a widely studied environmental risk factor for ischaemic heart disease and myocardial infarction in particular. Given that myocardial infarction is a leading disability and mortality cause in Bulgaria and that a significant proportion of the urban population is exposed to high noise levels, quantification of the burden of disease attributable to traffic noise is essential for environmental health policy making and noise control engineering. This study aimed at estimating the burden of the myocardial infarction cases attributable to road traffic noise in the Bulgarian urban population. We used the methodology for estimating the burden of disease attributable to environmental noise outlined by the World Health Organization. Risk data were extracted from a recently published meta-analysis providing updated exposure-response relationship between traffic noise and the risk for myocardial infarction. Based on these data we calculated the fraction of myocardial infarction cases attributable to traffic noise, loss of quality-adjusted life-years (QALYs), and the economic burden, assuming € 12,000 per QALY. About 2.9 % or 101 of all myocardial infarction cases could be attributed to road traffic noise. Fifty-five of these were fatal. Nine hundred and sixty-eight QALYs were lost to these cases. The monetary value of these QALYs was about € 11.6 million. Although the measures used in this study are crude and give only an approximation of the real burden of disease from road traffic noise, they are indicative of the important social and economic aspect of noise pollution in Bulgaria. Hopefully, these results will direct the attention of epidemiologists, environmental hygienists, and health economists to this pivotal environmental issue.
Delfino, Ralph J; Wu, Jun; Tjoa, Thomas; Gullesserian, Sevan K; Nickerson, Bruce; Gillen, Daniel L
2014-01-01
Ambient air pollution has been associated with asthma-related hospital admissions and emergency department visits (hospital encounters). We hypothesized that higher individual exposure to residential traffic-related air pollutants would enhance these associations. We studied 11,390 asthma-related hospital encounters among 7492 subjects 0-18 years of age living in Orange County, California. Ambient exposures were measured at regional air monitoring stations. Seasonal average traffic-related exposures (PM2.5, ultrafine particles, NOx, and CO) were estimated near subjects' geocoded residences for 6-month warm and cool seasonal periods, using dispersion models based on local traffic within 500 m radii. Associations were tested in case-crossover conditional logistic regression models adjusted for temperature and humidity. We assessed effect modification by seasonal residential traffic-related air pollution exposures above and below median dispersion-modeled exposures. Secondary analyses considered effect modification by traffic exposures within race/ethnicity and insurance group strata. Asthma morbidity was positively associated with daily ambient O3 and PM2.5 in warm seasons and with CO, NOx, and PM2.5 in cool seasons. Associations with CO, NOx, and PM2.5 were stronger among subjects living at residences with above-median traffic-related exposures, especially in cool seasons. Secondary analyses showed no consistent differences in association, and 95% confidence intervals were wide, indicating a lack of precision for estimating these highly stratified associations. Associations of asthma with ambient air pollution were enhanced among subjects living in homes with high traffic-related air pollution. This may be because of increased susceptibility (greater asthma severity) or increased vulnerability (meteorologic amplification of local vs. correlated ambient exposures).
NASA Astrophysics Data System (ADS)
Ngan, Henry Y. T.; Yung, Nelson H. C.; Yeh, Anthony G. O.
2015-02-01
This paper aims at presenting a comparative study of outlier detection (OD) for large-scale traffic data. The traffic data nowadays are massive in scale and collected in every second throughout any modern city. In this research, the traffic flow dynamic is collected from one of the busiest 4-armed junction in Hong Kong in a 31-day sampling period (with 764,027 vehicles in total). The traffic flow dynamic is expressed in a high dimension spatial-temporal (ST) signal format (i.e. 80 cycles) which has a high degree of similarities among the same signal and across different signals in one direction. A total of 19 traffic directions are identified in this junction and lots of ST signals are collected in the 31-day period (i.e. 874 signals). In order to reduce its dimension, the ST signals are firstly undergone a principal component analysis (PCA) to represent as (x,y)-coordinates. Then, these PCA (x,y)-coordinates are assumed to be conformed as Gaussian distributed. With this assumption, the data points are further to be evaluated by (a) a correlation study with three variant coefficients, (b) one-class support vector machine (SVM) and (c) kernel density estimation (KDE). The correlation study could not give any explicit OD result while the one-class SVM and KDE provide average 59.61% and 95.20% DSRs, respectively.
MOBILE Model and Transportation Planning : A Brief Overview
DOT National Transportation Integrated Search
2007-01-01
Americans lose 3.7 billion hours and 2.3 billion gallons of fuel every year sitting in traffic. In 2004, trucks idling in traffic are estimated to have cost the trucking industry some 243 million hours, the equivalent of 17,000 work years, with a cos...
DOT National Transportation Integrated Search
1989-05-01
State-trait anxiety scores were used prior to the 1981 strike of air traffic control specialists (ATCSs) to estimate perceived levels of job stress in field studies of this occupational group. The present study assessed the relationship between anxie...
A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related a...
DOT National Transportation Integrated Search
2008-08-01
Freeway congestion is a major problem in many urban areas. It has been estimated that freeway incidents (events that impede the flow of traffic: accidents, disabled vehicles, etc.) account for one-half to three-fourths of the total congestion on metr...
A modeling framework for characterizing near-road air pollutant concentration at community scales
In this study, we combine information from transportation network, traffic emissions, and dispersion model to develop a framework to inform exposure estimates for traffic-related air pollutants (TRAPs) with a high spatial resolution. A Research LINE source dispersion model (R-LIN...
Modeling and Impacts of Traffic Emissions on Air Toxics Concentrations near Roadways
The dispersion formulation incorporated in the U.S. Environmental Protection Agency’s AERMOD regulatory dispersion model is used to estimate the contribution of traffic-generated emissions of select VOCs – benzene, 1,3-butadiene, toluene – to ambient air concentrations at downwin...
DOT National Transportation Integrated Search
2000-04-01
Satellite imagery could conceivably be added to data traditionally collected in traffic monitoring programs to allow wide spatial coverage unobtainable from ground-based sensors in a safe, off-the-road environment. Previously, we estimated that 1-m r...
DOT National Transportation Integrated Search
2000-04-01
Satellite imagery could conceivably be added to data traditionally collected in traffic monitoring programs to allow wide spatial coverage unobtainable from ground-based sensors in a safe, off-the-road environment. Previously, we estimated that 1-m r...
Spectral Analysis of the Effects of Daylight Saving Time on Motor Vehicle Fatal Traffic Accidents
DOT National Transportation Integrated Search
1977-04-01
This report shows that Daylight Saving Time (DST) reduces the number of persons killed in motor vehicle fatal traffic accidents by about one percent. This estimate is based on a spectral (Fourier) analysis of these fatalities which utilizes a filteri...
NASA Technical Reports Server (NTRS)
Lee, David; Long, Dou; Etheridge, Mel; Plugge, Joana; Johnson, Jesse; Kostiuk, Peter
1998-01-01
We present a general method for making cross comparable estimates of the benefits of NASA-developed decision support technologies for air traffic management, and we apply a specific implementation of the method to estimate benefits of three decision support tools (DSTs) under development in NASA's advanced Air Transportation Technologies Program: Active Final Approach Spacing Tool (A-FAST), Expedite Departure Path (EDP), and Conflict Probe and Trial Planning Tool (CPTP). The report also reviews data about the present operation of the national airspace system (NAS) to identify opportunities for DST's to reduce delays and inefficiencies.
Three methods for estimating a range of vehicular interactions
NASA Astrophysics Data System (ADS)
Krbálek, Milan; Apeltauer, Jiří; Apeltauer, Tomáš; Szabová, Zuzana
2018-02-01
We present three different approaches how to estimate the number of preceding cars influencing a decision-making procedure of a given driver moving in saturated traffic flows. The first method is based on correlation analysis, the second one evaluates (quantitatively) deviations from the main assumption in the convolution theorem for probability, and the third one operates with advanced instruments of the theory of counting processes (statistical rigidity). We demonstrate that universally-accepted premise on short-ranged traffic interactions may not be correct. All methods introduced have revealed that minimum number of actively-followed vehicles is two. It supports an actual idea that vehicular interactions are, in fact, middle-ranged. Furthermore, consistency between the estimations used is surprisingly credible. In all cases we have found that the interaction range (the number of actively-followed vehicles) drops with traffic density. Whereas drivers moving in congested regimes with lower density (around 30 vehicles per kilometer) react on four or five neighbors, drivers moving in high-density flows respond to two predecessors only.
Preventing child pedestrian injury: pedestrian education or traffic calming?
Roberts, I; Ashton, T; Dunn, R; Lee-Joe, T
1994-06-01
The traditional approach to the prevention of child pedestrian injuries in New Zealand is pedestrian education. However, none of the programs currently being implemented in New Zealand have ever been shown to reduce injury rates. The allocation of scarce resources to pedestrian education must therefore be questioned. In this paper we estimate the number of serious child pedestrian injuries which might be prevented if the resources allocated to pedestrian education were allocated instead to environmental approaches, in particular, to traffic calming. It is estimated that approximately 18 hospitalisations of child pedestrians could be prevented each year under this alternative resource allocation, disregarding any other benefits of traffic calming. These results emphasise the need to consider the potential sacrifices involved in the allocation of scarce resources to child pedestrian education.
Reliability verification of vehicle speed estimate method in forensic videos.
Kim, Jong-Hyuk; Oh, Won-Taek; Choi, Ji-Hun; Park, Jong-Chan
2018-06-01
In various types of traffic accidents, including car-to-car crash, vehicle-pedestrian collision, and hit-and-run accident, driver overspeed is one of the critical issues of traffic accident analysis. Hence, analysis of vehicle speed at the moment of accident is necessary. The present article proposes a vehicle speed estimate method (VSEM) applying a virtual plane and a virtual reference line to a forensic video. The reliability of the VSEM was verified by comparing the results obtained by applying the VSEM to videos from a test vehicle driving with a global positioning system (GPS)-based Vbox speed. The VSEM verified by these procedures was applied to real traffic accident examples to evaluate the usability of the VSEM. Copyright © 2018 Elsevier B.V. All rights reserved.
Designing Two-Layer Optical Networks with Statistical Multiplexing
NASA Astrophysics Data System (ADS)
Addis, B.; Capone, A.; Carello, G.; Malucelli, F.; Fumagalli, M.; Pedrin Elli, E.
The possibility of adding multi-protocol label switching (MPLS) support to transport networks is considered an important opportunity by telecom carriers that want to add packet services and applications to their networks. However, the question that arises is whether it is suitable to have MPLS nodes just at the edge of the network to collect packet traffic from users, or also to introduce MPLS facilities on a subset of the core nodes in order to exploit packet switching flexibility and multiplexing, thus providing induction of a better bandwidth allocation. In this article, we address this complex decisional problem with the support of a mathematical programming approach. We consider two-layer networks where MPLS is overlaid on top of transport networks-synchronous digital hierarchy (SDH) or wavelength division multiplexing (WDM)-depending on the required link speed. The discussions' decisions take into account the trade-off between the cost of adding MPLS support in the core nodes and the savings in the link bandwidth allocation due to the statistical multiplexing and the traffic grooming effects induced by MPLS nodes. The traffic matrix specifies for each point-to-point request a pair of values: a mean traffic value and an additional one. Using this traffic model, the effect of statistical multiplexing on a link allows the allocation of a capacity equal to the sum of all the mean values of the traffic demands routed on the link and only the highest additional one. The proposed approach is suitable to solve real instances in reasonable time.
Fushiki, Tadayoshi
2009-07-01
The correlation matrix is a fundamental statistic that is used in many fields. For example, GroupLens, a collaborative filtering system, uses the correlation between users for predictive purposes. Since the correlation is a natural similarity measure between users, the correlation matrix may be used in the Gram matrix in kernel methods. However, the estimated correlation matrix sometimes has a serious defect: although the correlation matrix is originally positive semidefinite, the estimated one may not be positive semidefinite when not all ratings are observed. To obtain a positive semidefinite correlation matrix, the nearest correlation matrix problem has recently been studied in the fields of numerical analysis and optimization. However, statistical properties are not explicitly used in such studies. To obtain a positive semidefinite correlation matrix, we assume the approximate model. By using the model, an estimate is obtained as the optimal point of an optimization problem formulated with information on the variances of the estimated correlation coefficients. The problem is solved by a convex quadratic semidefinite program. A penalized likelihood approach is also examined. The MovieLens data set is used to test our approach.
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.
Son, Sanghyun; Baek, Yunju
2015-01-01
As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%. PMID:26295230
Son, Sanghyun; Baek, Yunju
2015-08-18
As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.
The Community Line Source (C-LINE) modeling system estimates emissions and dispersion of toxic air pollutants for roadways within the continental United States. It accesses publicly available traffic and meteorological datasets, and is optimized for use on community-sized areas (...
DOT National Transportation Integrated Search
2014-07-01
The overall goal of this project is to integrate and operationalize weather-sensitive TrEPS models calibrated for the Salt Lake City region to support weather-responsive traffic signal timing implementation and evaluation in the Riverdale corridor in...
Code of Federal Regulations, 2010 CFR
2010-04-01
... OF HIGHWAY TRAFFIC NOISE AND CONSTRUCTION NOISE § 772.5 Definitions. (a) Design year. The future year used to estimate the probable traffic volume for which a highway is designed. A time, 10 to 20 years... the natural and mechanical sources and human activity, considered to be usually present in a...
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...
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.
NASA Astrophysics Data System (ADS)
Zwack, Leonard M.; Paciorek, Christopher J.; Spengler, John D.; Levy, Jonathan I.
2011-05-01
Traffic within urban street canyons can contribute significantly to ambient concentrations of particulate air pollution. In these settings, it is challenging to separate within-canyon source contributions from urban and regional background concentrations given the highly variable and complex emissions and dispersion characteristics. In this study, we used continuous mobile monitoring of traffic-related particulate air pollutants to assess the contribution to concentrations, above background, of traffic in the street canyons of midtown Manhattan. Concentrations of both ultrafine particles (UFP) and fine particles (PM 2.5) were measured at street level using portable instruments. Statistical modeling techniques accounting for autocorrelation were used to investigate the presence of spatial heterogeneity of pollutant concentrations as well as to quantify the contribution of within-canyon traffic sources. Measurements were also made within Central Park, to examine the impact of offsets from major roadways in this urban environment. On average, an approximate 11% increase in concentrations of UFP and 8% increase in concentrations of PM 2.5 over urban background was estimated during high-traffic periods in street canyons as opposed to low traffic periods. Estimates were 8% and 5%, respectively, after accounting for temporal autocorrelation. Within Central Park, concentrations were 40% higher than background (5% after accounting for temporal autocorrelation) within the first 100 m from the nearest roadway for UFP, with a smaller but statistically significant increase for PM 2.5. Our findings demonstrate the viability of a mobile monitoring protocol coupled with spatiotemporal modeling techniques in characterizing local source contributions in a setting with street canyons.
Estimating the causes of traffic accidents using logistic regression and discriminant analysis.
Karacasu, Murat; Ergül, Barış; Altin Yavuz, Arzu
2014-01-01
Factors that affect traffic accidents have been analysed in various ways. In this study, we use the methods of logistic regression and discriminant analysis to determine the damages due to injury and non-injury accidents in the Eskisehir Province. Data were obtained from the accident reports of the General Directorate of Security in Eskisehir; 2552 traffic accidents between January and December 2009 were investigated regarding whether they resulted in injury. According to the results, the effects of traffic accidents were reflected in the variables. These results provide a wealth of information that may aid future measures toward the prevention of undesired results.
NASA Technical Reports Server (NTRS)
Idris, Husni; Vivona, Robert A.; Al-Wakil, Tarek
2009-01-01
This document describes exploratory research on a distributed, trajectory oriented approach for traffic complexity management. The approach is to manage traffic complexity based on preserving trajectory flexibility and minimizing constraints. In particular, the document presents metrics for trajectory flexibility; a method for estimating these metrics based on discrete time and degree of freedom assumptions; a planning algorithm using these metrics to preserve flexibility; and preliminary experiments testing the impact of preserving trajectory flexibility on traffic complexity. The document also describes an early demonstration capability of the trajectory flexibility preservation function in the NASA Autonomous Operations Planner (AOP) platform.
3D Markov Process for Traffic Flow Prediction in Real-Time.
Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi
2016-01-25
Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further.
3D Markov Process for Traffic Flow Prediction in Real-Time
Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi
2016-01-01
Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further. PMID:26821025
Xu, Junshi; Wang, Jonathan; Hilker, Nathan; Fallah-Shorshani, Masoud; Saleh, Marc; Tu, Ran; Wang, An; Minet, Laura; Stogios, Christos; Evans, Greg; Hatzopoulou, Marianne
2018-06-05
This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to carbon monoxide (CO), nitrogen oxides (NO x ), and elemental carbon (EC) along an urban corridor. To this end, a field campaign was conducted over one week in June 2016 on an arterial road in Toronto, Canada. Traffic data were collected using a traffic camera and a radar, while air quality was characterized using two monitoring stations: one located at ground-level and another at the rooftop of a four-storey building. A traffic simulation model was calibrated and validated and sec-by-sec speed profiles for all vehicle trajectories were extracted to model emissions. In addition, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. Our results indicate that modelled EFs for CO and NO x are twice as high as plume-based EFs. Besides, modelled results indicate that transit bus emissions accounted for 60% and 70% of the total emissions of NO x and EC. Transit bus emission rates in g/passenger.km for NO x and EC were up to 8 and 22 times the emission rates of passenger cars. In contrast, the Toronto streetcars, which are electrically fuelled, were found to improve near-road air quality despite their negative impact on traffic speeds. Finally, we observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background given that the study network is located in a busy downtown area. Implications This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to various pollutants. Besides, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. We observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background as the study network is located in a busy downtown area.
Brunekreef, Bert; Beelen, Rob; Hoek, Gerard; Schouten, Leo; Bausch-Goldbohm, Sandra; Fischer, Paul; Armstrong, Ben; Hughes, Edward; Jerrett, Michael; van den Brandt, Piet
2009-03-01
Evidence is increasing that long-term exposure to ambient air pollution is associated with deaths from cardiopulmonary diseases. In a 2002 pilot study, we reported clear indications that traffic-related air pollution, especially at the local scale, was related to cardiopulmonary mortality in a randomly selected subcohort of 5000 older adults participating in the ongoing Netherlands Cohort Study (NLCS) on diet and cancer. In the current study, referred to as NLCS-AIR, our objective was to obtain more precise estimates of the effects of traffic-related air pollution by analyzing associations with cause-specific mortality, as well as lung cancer incidence, in the full cohort of approximately 120,000 subjects. Cohort members were 55 to 69 years of age at enrollment in 1986. Follow-up was from 1987 through 1996 for mortality (17,674 deaths) and from late 1986 through 1997 for lung cancer incidence (2234 cases). Information about potential confounding variables and effect modifiers was available from the questionnaire that subjects completed at enrollment and from publicly available data (including neighborhood-scale information such as income distributions). The NLCS was designed for a case-cohort approach, which makes use of all the cases in the full cohort, while data for the random subcohort are used to estimate person-time experience in the study. Full information on confounders was available for the subjects in the random subcohort and for the emerging cases of mortality and lung cancer incidence during the follow-up period, and in NLCS-AIR we used the case-cohort approach to examine the relation between exposure to air pollution and cause-specific mortality and lung cancer. We also specified a standard Cox proportional hazards model within the full cohort, for which information on potential confounding variables was much more limited. Exposure to air pollution was estimated for the subjects' home addresses at baseline in 1986. Concentrations were estimated for black smoke (a simple marker for soot) and nitrogen dioxide (NO2) as indicators of traffic-related air pollution, as well as nitric oxide (NO), sulfur dioxide (SO2), and particulate matter with aerodynamic diameter < or = 2.5 microm (PM2.5), as estimated from measurements of particulate matter with aerodynamic diameter < or = 10 microm (PM10). Overall long-term exposure concentrations were considered to be a function of air pollution contributions at regional, urban, and local scales. We used interpolation from data obtained routinely at regional stations of the National Air Quality Monitoring Network (NAQMN) to estimate the regional component of exposure at the home address. Average pollutant concentrations were estimated from NAQMN measurements for the period 1976 through 1996. Land-use regression methods were used to estimate the urban exposure component. For the local exposure component, geographic information systems (GISs) were used to generate indicators of traffic exposure that included traffic intensity on and distance to nearby roads. A major effort was made to collect traffic intensity data from individual municipalities. The exposure variables were refined considerably from those used in the pilot study, but we also analyzed the data for the full cohort in the current study using the exposure indicators of the pilot study. We analyzed the data in models with the estimated overall pollutant concentration as a single variable and with the background concentration (the sum of regional and urban components) and the local exposure estimate from traffic indicators as separate variables. In the full-cohort analyses adjusted for the limited set of confounders, estimated overall exposure concentrations of black smoke, NO2, NO, and PM2.5 were associated with mortality. For a 10-microg/m3 increase in the black smoke concentration, the relative risk (RR) (95% confidence interval [CI]) was 1.05 (1.00-1.11) for natural-cause (nonaccidental) mortality, 1.04 (0.95-1.13) for cardiovascular mortality, 1.22 (0.99-1.50) for respiratory mortality, 1.03 (0.88-1.20) for lung cancer mortality, and 1.04 (0.97-1.12) for noncardiopulmonary, non-lung cancer mortality. Results were similar for NO2, NO, and PM2.5. For a 10-microg/m3 increase in PM2.5 concentration, the RR for natural-cause mortality was 1.06 (95% CI, 0.97-1.16), the same as in the results of the American Cancer Society Study reported by Pope and colleagues in 2002. The highest relative risks were found for respiratory mortality, though confidence intervals were wider for this less-frequent cause of death. No associations with mortality were found for SO2. Some of the associations between the traffic indicator variables used to assess traffic intensity near the home and mortality reached statistical significance in the full cohort. For an increase in traffic intensity of 10,000 motor vehicles in 24 hours (motor vehicles/day) on the road nearest a subject's residence, the RR was 1.03 (95% CI, 1.00-1.08) for natural-cause mortality, 1.05 (0.99-1.12) for cardiovascular mortality, 1.10 (0.95-1.26) for respiratory mortality, 1.07 (0.96-1.19) for lung cancer mortality, and 1.00 (0.94-1.06) for noncardiopulmonary, non-lung cancer mortality. Results were similar for traffic intensity in a 100-m buffer around the subject's residence and living near a major road (a road with more than 10,000 motor vehicles/day). Distance in meters to the nearest major road and traffic intensity on the nearest major road were not associated with any of the mortality outcomes. We did not find an association between cardiopulmonary mortality and living near a major road as defined using the methods of the pilot study. In the case-cohort analyses adjusted for all potential confounders, we found no associations between background air pollution and mortality. The associations between traffic intensity and mortality were weaker than in the full cohort, and confidence intervals were wider, consistent with the smaller number of subjects. The lower relative risks of mortality associated with traffic variables in the case-cohort study population could be related to the particular subcohort that was randomly selected from the full cohort, as the risks estimated with the actual subcohort were well below the average estimates obtained for 100 new case-cohort analyses with 100 alternative subcohorts of 5000 subjects each that we randomly selected from the full cohort. Differences in adjusted relative risks between the full-cohort and the case-cohort analyses could be explained by random error introduced by sampling from the full cohort and by a selection effect resulting from the relatively large number of missing data for variables in the extensive confounder model used in the case-cohort analyses. More complete control for confounding probably did not contribute much to the lower relative risks in the case-cohort analyses, especially for the traffic variables, as results were similar when the limited confounder model for the full cohort was used in analyses of the subjects in the case-cohort study population. In additional analyses using black smoke concentrations as the exposure variables, we found that the association between overall black smoke and cardiopulmonary mortality was somewhat stronger for case-cohort subjects who did not change residence during follow-up, and in the full cohort, there was a tendency for relative risks to be higher for subjects living in the three major cities included in the study. Adjustment for estimated exposure to traffic noise did not affect the associations of background black smoke and traffic intensity with cardiovascular mortality. There was some indication of an association between traffic noise and cardiovascular mortality only for the 1.6% of the subjects in the full cohort who were exposed to traffic noise in the highest category of > 65 A-weighted decibels (dB(A); decibels with the sound pressure scale adjusted to conform with the frequency response of the human ear). Examination of sex, smoking status, educational level, and vegetable and fruit intake as possible effect modifiers showed that for overall black smoke concentrations, associations with mortality tended to be stronger in case-cohort subjects with lower levels of education and those with low fruit intake, but differences between strata were not statistically significant. For lung cancer incidence, we found essentially no relation to exposure to NO2, black smoke, PM2.5, SO2, or several traffic indicators. Associations of overall air pollution concentrations and traffic indicator variables with lung cancer incidence were, however, found in subjects who had never smoked, with an RR of 1.47 (95% CI, 1.01-2.16) for a 10-microg/m3 increase in overall black smoke concentration. In the current study, the mortality risks associated with both background air pollution and traffic exposure variables were much smaller than the estimate previously reported in the pilot study for risk of cardiopulmonary mortality associated with living near a major road (RR, 1.95; 95% CI, 1.09-3.51). The differences are most likely due to the extension of the follow-up period in the current study and to random error in the pilot study related to sampling from the full cohort. Though relative risks were generally small in the current study, long-term average concentrations of black smoke, NO2, and PM2.5 were related to mortality, and associations of black smoke and NO2 exposure with natural-cause and respiratory mortality were statistically significant. Traffic intensity near the home was also related to natural-cause mortality. The highest relative risks associated with background air pollution and traffic variables were for respiratory mortality, though the number of deaths was smaller than for the other mortality categories. (ABSTRACT TRUNCATED)
Vineis, Paolo; Hoek, Gerard; Krzyzanowski, Michal; Vigna-Taglianti, Federica; Veglia, Fabrizio; Airoldi, Luisa; Overvad, Kim; Raaschou-Nielsen, Ole; Clavel-Chapelon, Francoise; Linseisen, Jacob; Boeing, Heiner; Trichopoulou, Antonia; Palli, Domenico; Krogh, Vittorio; Tumino, Rosario; Panico, Salvatore; Bueno-De-Mesquita, H Bas; Peeters, Petra H; Lund E, Eiliv; Agudo, Antonio; Martinez, Carmen; Dorronsoro, Miren; Barricarte, Aurelio; Cirera, Lluis; Quiros, J Ramon; Berglund, Goran; Manjer, Jonas; Forsberg, Bertil; Day, Nicholas E; Key, Tim J; Kaaks, Rudolf; Saracci, Rodolfo; Riboli, Elio
2007-01-01
Background Several countries are discussing new legislation on the ban of smoking in public places, and on the acceptable levels of traffic-related air pollutants. It is therefore useful to estimate the burden of disease associated with indoor and outdoor air pollution. Methods We have estimated exposure to Environmental Tobacco Smoke (ETS) and to air pollution in never smokers and ex-smokers in a large prospective study in 10 European countries (European Prospective Investigation into Cancer and Nutrition)(N = 520,000). We report estimates of the proportion of lung cancers attributable to ETS and air pollution in this population. Results The proportion of lung cancers in never- and ex-smokers attributable to ETS was estimated as between 16 and 24%, mainly due to the contribution of work-related exposure. We have also estimated that 5–7% of lung cancers in European never smokers and ex-smokers are attributable to high levels of air pollution, as expressed by NO2 or proximity to heavy traffic roads. NO2 is the expression of a mixture of combustion (traffic-related) particles and gases, and is also related to power plants and waste incinerator emissions. Discussion We have estimated risks of lung cancer attributable to ETS and traffic-related air pollution in a large prospective study in Europe. Information bias can be ruled out due to the prospective design, and we have thoroughly controlled for potential confounders, including restriction to never smokers and long-term ex-smokers. Concerning traffic-related air pollution, the thresholds for indicators of exposure we have used are rather strict, i.e. they correspond to the high levels of exposure that characterize mainly Southern European countries (levels of NO2 in Denmark and Sweden are closer to 10–20 ug/m3, whereas levels in Italy are around 30 or 40, or higher). Therefore, further reduction in exposure levels below 30 ug/m3 would correspond to additional lung cancer cases prevented, and our estimate of 5–7% is likely to be an underestimate. Overall, our prospective study draws attention to the need for strict legislation concerning the quality of air in Europe. PMID:17302981
A novel multisensor traffic state assessment system based on incomplete data.
Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang
2014-01-01
A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.
Traffic mortality and the role of minor roads.
van Langevelde, Frank; van Dooremalen, Coby; Jaarsma, Catharinus F
2009-01-01
Roads have large impacts on wildlife, as they form one of the principal causes of mortality, and disturbance and fragmentation of habitat. These impacts are mainly studied and mitigated on major roads. It is, however, a widespread misconception that most animals are killed on major roads. In this paper, we argue that minor roads have a larger impact on wildlife with respect to habitat destruction, noise load and traffic mortality. We use data on traffic related deaths in badgers (Meles meles) in The Netherlands to illustrate that traffic mortality is higher on minor roads. We ask for a more extensive investigation of the environmental impacts of minor roads. Moreover, we argue that the success of mitigation on roads drastically increases when both major and minor roads are integrated in the planning of traffic flows. Therefore, we propose a strategy based on the concept of a "traffic-calmed area". Traffic-calmed areas create opportunities for wildlife by decreasing limitations for animal movement. We ask for further studies to estimate what size traffic-calmed areas should be to maintain minimum viable animal populations.
Impact of traffic composition on accessibility as indicator of transport sustainability
NASA Astrophysics Data System (ADS)
Nahdalina; Hadiwardoyo, S. P.; Nahry
2017-05-01
Sustainable transport is closely related to quality of life in the community at present and in the future. Some indicators of transport sustainability are accessibility measurement of origin/destination, the operating costs of transport (vehicle operating cost or VOC) and external transportation costs (emission cost). The indicators could be combined into accessibility measurement model. In other case, almost traffic congestion occurred on the condition of mixed traffic. This paper aimed to analyse the indicator of transport sustainability through simulation under condition of various traffic composition. Various composition of truck to total traffic flow are 0%, 10% and 20%. Speed and V/C are calculated from traffic flow to estimate the VOC and emission cost. 5 VOC components and 3 types of emission cost (CO2, CH4 and N2O) are counted to be a travel cost. Accessibility measurement was calculated using travel cost and gravity model approaches. Result of the research shows that the total traffic flow has indirect impact on accessibility measurement if using travel cost approach. Meanwhile, the composition of traffic flow has an affect on accessibility measurement if using gravity model approach.
A Novel Multisensor Traffic State Assessment System Based on Incomplete Data
Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang
2014-01-01
A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system. PMID:25162055
Effects of urban sprawl and vehicle miles traveled on traffic fatalities.
Yeo, Jiho; Park, Sungjin; Jang, Kitae
2015-01-01
Previous research suggests that urban sprawl increases auto-dependency and that excessive auto use increases the risk of traffic fatalities. This indirect effect of urban sprawl on traffic fatalities is compared to non-vehicle miles traveled (VMT)-related direct effect of sprawl on fatalities. We conducted a path analysis to examine the causal linkages among urban sprawl, VMT, traffic fatalities, income, and fuel cost. The path diagram includes 2 major linkages: the direct relationship between urban sprawl and traffic fatalities and the indirect effect on fatalities through increased VMT in sprawling urban areas. To measure the relative strength of these causal linkages, path coefficients are estimated using data collected nationally from 147 urbanized areas in the United States. Through both direct and indirect paths, urban sprawl is associated with greater numbers of traffic fatalities, but the direct effect of sprawl on fatalities is more influential than the indirect effect. Enhancing traffic safety can be achieved by impeding urban sprawl and encouraging compact development. On the other hand, policy tools reducing VMT may be less effective than anticipated for traffic safety.
Finding Cardinality Heavy-Hitters in Massive Traffic Data and Its Application to Anomaly Detection
NASA Astrophysics Data System (ADS)
Ishibashi, Keisuke; Mori, Tatsuya; Kawahara, Ryoichi; Hirokawa, Yutaka; Kobayashi, Atsushi; Yamamoto, Kimihiro; Sakamoto, Hitoaki; Asano, Shoichiro
We propose an algorithm for finding heavy hitters in terms of cardinality (the number of distinct items in a set) in massive traffic data using a small amount of memory. Examples of such cardinality heavy-hitters are hosts that send large numbers of flows, or hosts that communicate with large numbers of other hosts. Finding these hosts is crucial to the provision of good communication quality because they significantly affect the communications of other hosts via either malicious activities such as worm scans, spam distribution, or botnet control or normal activities such as being a member of a flash crowd or performing peer-to-peer (P2P) communication. To precisely determine the cardinality of a host we need tables of previously seen items for each host (e. g., flow tables for every host) and this may infeasible for a high-speed environment with a massive amount of traffic. In this paper, we use a cardinality estimation algorithm that does not require these tables but needs only a little information called the cardinality summary. This is made possible by relaxing the goal from exact counting to estimation of cardinality. In addition, we propose an algorithm that does not need to maintain the cardinality summary for each host, but only for partitioned addresses of a host. As a result, the required number of tables can be significantly decreased. We evaluated our algorithm using actual backbone traffic data to find the heavy-hitters in the number of flows and estimate the number of these flows. We found that while the accuracy degraded when estimating for hosts with few flows, the algorithm could accurately find the top-100 hosts in terms of the number of flows using a limited-sized memory. In addition, we found that the number of tables required to achieve a pre-defined accuracy increased logarithmically with respect to the total number of hosts, which indicates that our method is applicable for large traffic data for a very large number of hosts. We also introduce an application of our algorithm to anomaly detection. With actual traffic data, our method could successfully detect a sudden network scan.
Using bayesian model to estimate the cost of traffic injuries in Iran in 2013
Ainy, Elaheh; Soori, Hamid; Ganjali, Mojtaba; Bahadorimonfared, Ayad
2017-01-01
Background and Aim: A significant social and economic burden inflicts by road traffic injuries (RTIs). We aimed to use Bayesian model, to present the precise method, and to estimate the cost of RTIs in Iran in 2013. Materials and Methods: In a cross-sectional study on costs resulting from traffic injuries, 846 people per road user were randomly selected and investigated during 3 months (1st September–1st December) in 2013. The research questionnaire was prepared based on the standard for willingness to pay (WTP) method considering perceived risks, especially in Iran. Data were collected along with four scenarios for occupants, pedestrians, vehicle drivers, and motorcyclists. Inclusion criterion was having at least high school education and being in the age range of 18–65 years old; risk perception was an important factor to the study and measured by visual tool. Samples who did not have risk perception were excluded from the study. Main outcome measure was cost estimation of traffic injuries using WTP method. Results: Mean WTP was 2,612,050 internal rate of return (IRR) among these road users. Statistical value of life was estimated according to 20,408 death cases 402,314,106,073,648 IRR, equivalent to 13,410,470,202$ based on the dollar free market rate of 30,000 IRR (purchase power parity). In sum, injury and death cases came to 1,171,450,232,238,648 IRR equivalents to 39,048,341,074$. Moreover, in 2013, costs of traffic accident constituted 6.46% of gross national income, which was 604,300,000,000$. WTP had a significant relationship with age, middle and high income, daily payment to injury reduction, more payment to time reduction, trip mileage, private cars drivers, bus, minibus vehicles, and occupants (P < 0.01). Conclusion: Costs of traffic injuries included noticeable portion of gross national income. If policy-making and resource allocation are made based on the scientific pieces of evidence, an enormous amount of capital can be saved through reducing death and injury rates. PMID:28971031
Convex Banding of the Covariance Matrix
Bien, Jacob; Bunea, Florentina; Xiao, Luo
2016-01-01
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which tapers the sample covariance matrix by a Toeplitz, sparsely-banded, data-adaptive matrix. As a result of this adaptivity, the convex banding estimator enjoys theoretical optimality properties not attained by previous banding or tapered estimators. In particular, our convex banding estimator is minimax rate adaptive in Frobenius and operator norms, up to log factors, over commonly-studied classes of covariance matrices, and over more general classes. Furthermore, it correctly recovers the bandwidth when the true covariance is exactly banded. Our convex formulation admits a simple and efficient algorithm. Empirical studies demonstrate its practical effectiveness and illustrate that our exactly-banded estimator works well even when the true covariance matrix is only close to a banded matrix, confirming our theoretical results. Our method compares favorably with all existing methods, in terms of accuracy and speed. We illustrate the practical merits of the convex banding estimator by showing that it can be used to improve the performance of discriminant analysis for classifying sound recordings. PMID:28042189
Convex Banding of the Covariance Matrix.
Bien, Jacob; Bunea, Florentina; Xiao, Luo
2016-01-01
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which tapers the sample covariance matrix by a Toeplitz, sparsely-banded, data-adaptive matrix. As a result of this adaptivity, the convex banding estimator enjoys theoretical optimality properties not attained by previous banding or tapered estimators. In particular, our convex banding estimator is minimax rate adaptive in Frobenius and operator norms, up to log factors, over commonly-studied classes of covariance matrices, and over more general classes. Furthermore, it correctly recovers the bandwidth when the true covariance is exactly banded. Our convex formulation admits a simple and efficient algorithm. Empirical studies demonstrate its practical effectiveness and illustrate that our exactly-banded estimator works well even when the true covariance matrix is only close to a banded matrix, confirming our theoretical results. Our method compares favorably with all existing methods, in terms of accuracy and speed. We illustrate the practical merits of the convex banding estimator by showing that it can be used to improve the performance of discriminant analysis for classifying sound recordings.
Nazif-Munoz, José Ignacio; Quesnel-Vallée, Amélie; van den Berg, Axel
2015-06-01
The objective of the current study is to determine to what extent the reduction of Chile's traffic fatalities and injuries during 2000-2012 was related to the police traffic enforcement increment registered after the introduction of its 2005 traffic law reform. A unique dataset with assembled information from public institutions and analyses based on ordinary least square and robust random effects models was carried out. Dependent variables were traffic fatality and severe injury rates per population and vehicle fleet. Independent variables were: (1) presence of new national traffic law; (2) police officers per population; (3) number of traffic tickets per police officer; and (4) interaction effect of number of traffic tickets per police officer with traffic law reform. Oil prices, alcohol consumption, proportion of male population 15-24 years old, unemployment, road infrastructure investment, years' effects and regions' effects represented control variables. Empirical estimates from instrumental variables suggest that the enactment of the traffic law reform in interaction with number of traffic tickets per police officer is significantly associated with a decrease of 8% in traffic fatalities and 7% in severe injuries. Piecewise regression model results for the 2007-2012 period suggest that police traffic enforcement reduced traffic fatalities by 59% and severe injuries by 37%. Findings suggest that traffic law reforms in order to have an effect on both traffic fatality and injury rates reduction require changes in police enforcement practices. Last, this case also illustrates how the diffusion of successful road safety practices globally promoted by WHO and World Bank can be an important influence for enhancing national road safety practices. 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.
Real-time video analysis for retail stores
NASA Astrophysics Data System (ADS)
Hassan, Ehtesham; Maurya, Avinash K.
2015-03-01
With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.
Technical and economic feasibility of integrated video service by satellite
NASA Technical Reports Server (NTRS)
Price, Kent M.; Garlow, R. K.; Henderson, T. R.; Kwan, Robert K.; White, L. W.
1992-01-01
The trends and roles of satellite based video services in the year 2010 time frame are examined based on an overall network and service model for that period. Emphasis is placed on point to point and multipoint service, but broadcast could also be accommodated. An estimate of the video traffic is made and the service and general network requirements are identified. User charges are then estimated based on several usage scenarios. In order to accommodate these traffic needs, a 28 spot beam satellite architecture with on-board processing and signal mixing is suggested.
Matz, Carlyn J; Stieb, David M; Egyed, Marika; Brion, Orly; Johnson, Markey
2018-01-01
Exposure to traffic and traffic-related air pollution is associated with a wide array of health effects. Time spent in a vehicle, in active transportation, along roadsides, and in close proximity to traffic can substantially contribute to daily exposure to air pollutants. For this study, we evaluated daily time spent in transportation and traffic-influenced microenvironments by urban Canadians using the Canadian Human Activity Pattern Survey (CHAPS) 2 results. Approximately 4-7% of daily time was spent in on- or near-road locations, mainly associated with being in a vehicle and smaller contributions from active transportation. Indoor microenvironments can be impacted by traffic emissions, especially when located near major roadways. Over 60% of the target population reported living within one block of a roadway with moderate to heavy traffic, which was variable with income level and city, and confirmed based on elevated NO 2 exposure estimated using land use regression. Furthermore, over 55% of the target population ≤ 18 years reported attending a school or daycare in close proximity to moderate to heavy traffic, and little variation was observed based on income or city. The results underline the importance of traffic emissions as a major source of exposure in Canadian urban centers, given the time spent in traffic-influenced microenvironments.
Methods to improve traffic flow and noise exposure estimation on minor roads.
Morley, David W; Gulliver, John
2016-09-01
Address-level estimates of exposure to road traffic noise for epidemiological studies are dependent on obtaining data on annual average daily traffic (AADT) flows that is both accurate and with good geographical coverage. National agencies often have reliable traffic count data for major roads, but for residential areas served by minor roads, especially at national scale, such information is often not available or incomplete. Here we present a method to predict AADT at the national scale for minor roads, using a routing algorithm within a geographical information system (GIS) to rank roads by importance based on simulated journeys through the road network. From a training set of known minor road AADT, routing importance is used to predict AADT on all UK minor roads in a regression model along with the road class, urban or rural location and AADT on the nearest major road. Validation with both independent traffic counts and noise measurements show that this method gives a considerable improvement in noise prediction capability when compared to models that do not give adequate consideration to minor road variability (Spearman's rho. increases from 0.46 to 0.72). This has significance for epidemiological cohort studies attempting to link noise exposure to adverse health outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.
Impact of road traffic emissions on ambient air quality in an industrialized area.
Garcia, Sílvia M; Domingues, Gonçalo; Gomes, Carla; Silva, Alexandra V; Almeida, S Marta
2013-01-01
Several epidemiological studies showed a correlation between airborne particulate matter(PM) and the incidence of several diseases in exposed populations. Consequently, the European Commission reinforced the need and obligation of member-states to monitor exposure levels of PM and adopt measures to reduce this exposure. However, in order to plan appropriate actions, it is necessary to understand the main sources of air pollution and their relative contributions to the formation of the ambient aerosol. The aim of this study was to develop a methodology to assess the contribution of vehicles to the atmospheric aerosol,which may constitute a useful tool to assess the effectiveness of planned mitigation actions.This methodology is based on three main steps: (1) estimation of traffic emissions provided from the vehicles exhaust and resuspension; (2) use of the dispersion model TAPM (“The Air Pollution Model”) to estimate the contribution of traffic for the atmospheric aerosol; and(3) use of geographic information system (GIS) tools to map the PM10 concentrations provided from traffic in the surroundings of a target area. The methodology was applied to an industrial area, and results showed that the highest contribution of traffic for the PM10 concentrations resulted from dust resuspension and that heavy vehicles were the type that most contributed to the PM10 concentration.
PM10 source apportionment in a Swiss Alpine valley impacted by highway traffic.
Ducret-Stich, Regina E; Tsai, Ming-Yi; Thimmaiah, Devraj; Künzli, Nino; Hopke, Philip K; Phuleria, Harish C
2013-09-01
Although trans-Alpine highway traffic exhaust is one of the major sources of air pollution along the highway valleys of the Alpine regions, little is known about its contribution to residential exposure and impact on respiratory health. In this paper, source-specific contributions to particulate matter with an aerodynamic diameter < 10 μm (PM10) and their spatio-temporal distribution were determined for later use in a pediatric asthma panel study in an Alpine village. PM10 sources were identified by positive matrix factorization using chemical trace elements, elemental, and organic carbon from daily PM10 filters collected between November 2007 and June 2009 at seven locations within the village. Of the nine sources identified, four were directly road traffic-related: traffic exhaust, road dust, tire and brake wear, and road salt contributing 16 %, 8 %, 1 %, and 2 % to annual PM10 concentrations, respectively. They showed a clear dependence with distance to highway. Additional contributions were identified from secondary particles (27 %), biomass burning (18 %), railway (11 %), and mineral dust including a local construction site (13 %). Comparing these source contributions with known source-specific biomarkers (e.g., levoglucosan, nitro-polycyclic aromatic hydrocarbons) showed high agreement with biomass burning, moderate with secondary particles (in winter), and lowest agreement with traffic exhaust.
DOT National Transportation Integrated Search
2014-01-01
This research project investigated the potential for using advanced features of traffic signal system software platforms : (ATMS.now), prevalent in Florida, to alleviate safety and mobility problems at highway-railroad at-grade crossings and : adjace...
NASA Astrophysics Data System (ADS)
Curran, Jason
Traffic-related air pollution (TRAP) has been linked with several adverse health effects. We investigated hopanes, markers of primary particle emissions from gasoline and diesel engines, in house dust as an alternative approach for assessing exposure to TRAP in Windsor, Ontario. Settled house dust was collected from the homes of 28 study participants (10 -- 13 yrs). The dust was then analyzed for a suite of hopanes by gas chromatography-mass spectrometry. We calculated correlations between dust hopane concentrations and estimates of annual average NO2 concentrations derived from an existing LUR model. Hopanes were consistently present in detectable quantities in house dust. Annual average outdoor NO2 estimated was moderately correlated with hopanes in house dust (r = 0.46; p<0.05). The correlations did not vary by infiltration efficiency or the presence of an attached garage. Hopanes measured in settled house dust show promise as an indicator of long-term exposure to traffic-related air pollution. Keywords: hopane; air pollution; traffic; dust; exposure; TRAP.
Cloud-based large-scale air traffic flow optimization
NASA Astrophysics Data System (ADS)
Cao, Yi
The ever-increasing traffic demand makes the efficient use of airspace an imperative mission, and this paper presents an effort in response to this call. Firstly, a new aggregate model, called Link Transmission Model (LTM), is proposed, which models the nationwide traffic as a network of flight routes identified by origin-destination pairs. The traversal time of a flight route is assumed to be the mode of distribution of historical flight records, and the mode is estimated by using Kernel Density Estimation. As this simplification abstracts away physical trajectory details, the complexity of modeling is drastically decreased, resulting in efficient traffic forecasting. The predicative capability of LTM is validated against recorded traffic data. Secondly, a nationwide traffic flow optimization problem with airport and en route capacity constraints is formulated based on LTM. The optimization problem aims at alleviating traffic congestions with minimal global delays. This problem is intractable due to millions of variables. A dual decomposition method is applied to decompose the large-scale problem such that the subproblems are solvable. However, the whole problem is still computational expensive to solve since each subproblem is an smaller integer programming problem that pursues integer solutions. Solving an integer programing problem is known to be far more time-consuming than solving its linear relaxation. In addition, sequential execution on a standalone computer leads to linear runtime increase when the problem size increases. To address the computational efficiency problem, a parallel computing framework is designed which accommodates concurrent executions via multithreading programming. The multithreaded version is compared with its monolithic version to show decreased runtime. Finally, an open-source cloud computing framework, Hadoop MapReduce, is employed for better scalability and reliability. This framework is an "off-the-shelf" parallel computing model that can be used for both offline historical traffic data analysis and online traffic flow optimization. It provides an efficient and robust platform for easy deployment and implementation. A small cloud consisting of five workstations was configured and used to demonstrate the advantages of cloud computing in dealing with large-scale parallelizable traffic problems.
NASA Astrophysics Data System (ADS)
Brandt, J.; Silver, J. D.; Christensen, J. H.; Andersen, M. S.; Bønløkke, J. H.; Sigsgaard, T.; Geels, C.; Gross, A.; Hansen, A. B.; Hansen, K. M.; Hedegaard, G. B.; Kaas, E.; Frohn, L. M.
2013-03-01
An integrated model system, EVA (Economic Valuation of Air pollution), based on the impact-pathway chain has been developed, to assess the health-related economic externalities of air pollution resulting from specific emission sources or sectors. The model system can be used to support policy-making with respect to emission control. In this study, we apply the EVA system to Europe, and perform a more detailed assessment of past, present, and future health-cost externalities of the total air pollution levels in Europe (including both natural and anthropogenic sources), represented by the years 2000, 2007, 2011, and 2020. We also assess the contribution to the health-related external costs from international ship traffic with special attention to the international ship traffic in the Baltic and North Seas, since special regulatory actions on sulphur emissions, called SECA (sulphur emission control area), have been introduced in these areas,. We conclude that despite efficient regulatory actions in Europe in recent decades, air pollution still constitutes a serious problem to human health, hence the related external costs are considerable. The total health-related external costs for the whole of Europe is estimated at 803 bn Euro yr-1 for the year 2000, decreasing to 537 bn Euro yr-1 in the year 2020. We estimate the total number of premature deaths in Europe in the year 2000 due to air pollution to be around 680 000 yr-1, decreasing to approximately 450 000 in the year 2020. The contribution from international ship traffic in the Northern Hemisphere was estimated to 7% of the total health-related external costs in Europe in the year 2000, increasing to 12% in the year 2020. In contrast, the contribution from international ship traffic in the Baltic Sea and the North Sea decreases 36% due to the regulatory efforts of reducing sulphur emissions from ship traffic in SECA. Introducing this regulatory instrument for all international ship traffic in the Northern Hemisphere, or at least in areas close to Europe, would have a significant positive impact on human health in Europe.
NASA Astrophysics Data System (ADS)
Brandt, J.; Silver, J. D.; Christensen, J. H.; Andersen, M. S.; Bønløkke, J. H.; Sigsgaard, T.; Geels, C.; Gross, A.; Hansen, A. B.; Hansen, K. M.; Hedegaard, G. B.; Kaas, E.; Frohn, L. M.
2013-08-01
An integrated model system, EVA (Economic Valuation of Air pollution), based on the impact-pathway chain has been developed to assess the health-related economic externalities of air pollution resulting from specific emission sources or sectors. The model system can be used to support policy-making with respect to emission control. In this study, we apply the EVA system to Europe, and perform a more detailed assessment of past, present, and future health-cost externalities of the total air pollution levels in Europe (including both natural and anthropogenic sources), represented by the years 2000, 2007, 2011, and 2020. We also assess the contribution to the health-related external costs from international ship traffic with special attention to the international ship traffic in the Baltic and North seas, since special regulatory actions on sulfur emissions, called SECA (sulfur emission control area), have been introduced in these areas. We conclude that, despite efficient regulatory actions in Europe in recent decades, air pollution still constitutes a serious problem for human health. Hence the related external costs are considerable. The total health-related external costs for the whole of Europe are estimated at 803 bn euros yr-1 for the year 2000, decreasing to 537 bn euros yr-1 in the year 2020. We estimate the total number of premature deaths in Europe in the year 2000 due to air pollution to be around 680 000 yr-1, decreasing to approximately 450 000 in the year 2020. The contribution from international ship traffic in the Northern Hemisphere was estimated to 7% of the total health-related external costs in Europe in the year 2000, increasing to 12% in the year 2020. In contrast, the contribution from international ship traffic in the Baltic Sea and the North Sea decreases 36% due to the regulatory efforts of reducing sulfur emissions from ship traffic in SECA. Introducing this regulatory instrument for all international ship traffic in the Northern Hemisphere, or at least in areas close to Europe, would have a significant positive impact on human health in Europe.
NASA Astrophysics Data System (ADS)
Brandt, Jørgen; Silver, Jeremy D.; Christensen, Jesper H.; Andersen, Mikael S.; Bønløkke, Jakob H.; Sigsgaard, Torben; Geels, Camilla; Gross, Allan; Hansen, Ayoe B.; Hansen, Kaj M.; Hedegaard, Gitte B.; Kaas, Eigil; Frohn, Lise M.
2013-04-01
An integrated model system, EVA (Economic Valuation of Air pollution), based on the impact-pathway chain has been developed, to assess the health-related economic externalities of air pollution resulting from specific emission sources or sectors. The model system can be used to support policy-making with respect to emission control. In this study, we apply the EVA system to Europe, and perform a more detailed assessment of past, present, and future health-cost externalities of the total air pollution levels in Europe (including both natural and anthropogenic sources), represented by the years 2000, 2007, 2011, and 2020. We also assess the contribution to the health-related external costs from international ship traffic with special attention to the international ship traffic in the Baltic and North Seas, since special regulatory actions on sulphur emissions, called SECA (sulphur emission control area), have been intro-duced in these areas,. We conclude that despite efficient regulatory actions in Europe in recent decades, air pollution still constitutes a serious problem to human health, hence the related external costs are considerable. The total health-related external costs for the whole of Europe is estimated at 803 bn Euro/year for the year 2000, decreasing to 537 bn Euro/year in the year 2020. We estimate the total number of premature deaths in Europe in the year 2000 due to air pollution to be around 680,000/year, decreasing to approximately 450,000 in the year 2020. The contribution from international ship traffic in the Northern Hemisphere was estimated to 7% of the total health-related external costs in Europe in the year 2000, increasing to 12% in the year 2020. In contrast, the contribution from international ship traffic in the Baltic Sea and the North Sea decreases 36% due to the regulatory efforts of reducing sulphur emissions from ship traffic in SECA. Introducing this regulatory instrument for all international ship traffic in the Northern Hemisphere, or at least in areas close to Europe, would have a significant posi-tive impact on human health in Europe.
Spatially- explicit Fossil Fuel Carbon Dioxide Inventories for Transportation in the U.S.
NASA Astrophysics Data System (ADS)
Hutchins, M.; Gurney, K. R.
2016-12-01
The transportation sector is the second largest source of Fossil Fuel CO2 (FFCO2) emissions, and is unique in that federal, state, and municipal levels of government are all able to enact transportation policy. However, since data related to transportation activities are reported by multiple different government agencies, the data are not always consistent. As a result, the methods and data used to inventory and account for transportation related FFCO2 emissions have important implications for both science and policy. Aggregate estimates of transportation related FFCO2 emissions can be spatially distributed using traffic data, such as the Highway Performance Monitoring System (HPMS) Average Annual Daily Traffic (AADT). There are currently two datasets that estimate the spatial distribution of transportation related FFCO2 in the United States- Vulcan 3.0 and the Database of Road Transportation Emissions (DARTE). Both datasets are at 1 km resolution, for the year 2011, and utilize HPMS AADT traffic data. However, Vulcan 3.0 and DARTE spatially distribute emissions using different methods and inputs, resulting in a number of differences. Vulcan 3.0 and DARTE estimate national transportation related FFCO2 emissions within 2.5% of each other, with more significant differences at the county and state level. The differences are most notable in urban versus rural regions, and for specific road classes. The origin of these differences are explored in depth to understand the implication of using specific data sources, such as the National Emissions Inventory and other aggregate transportation statistics from the Federal Highway Administration (FHWA). In addition to comparing Vulcan 3.0 and DARTE to each other, the results from both data sets are compared to independent traffic volume measurements acquired from the FHWA Continuous Count Station (CCS) network. The CCS records hourly traffic counts at fixed locations in space throughout the U.S. We calculate transportation related FFCO2 emissions at a CCS stations using fuel specific emissions factors combined with the raw traffic counts. The CCS network provides a unique opportunity to compare spatially explicit, "bottom-up" models of transportation related FFCO2 emissions to measured traffic volume at over 300 specific locations.
Brown, Alan Lex; Lam, Kin Che; van Kamp, Irene
2015-03-07
Particularly in Asia, dense, traffic-intense, and usually high-rise cities are increasingly the norm. Is existing knowledge on exposure to road traffic noise, and on people's response to such exposure, garnered primarily from western cities, equally applicable in these? Hong Kong has high population and traffic density and a high-rise building form. Road traffic noise exposure was estimated, and residents' responses to traffic noise measured, for a sample of 10,077 dwellings. Noise level estimates were based on three-dimensional modelling. Best international survey practice measured self-reported annoyance and sleep-disturbance. Benchmark estimates of exposure, and of annoyance and self-reported sleep disturbance, are provided. We compare Hong Kong exposure with those of European cities, and the exposure-response relationship for annoyance in Hong Kong to those reported from elsewhere - based on the tolerance limits of previous syntheses. Exposure-response for self-reported sleep disturbance is also compared. The distribution of exposures of dwellings in high-rise, high-density, Hong Kong is different from those reported from Europe, but not at the higher noise levels. The exposure-annoyance relationship for road traffic noise was from the same population of exposure-response relationships, being well within the tolerance limits, of studies used to generate the synthesized Miedema and Oudshoorn curves. The exposure-response curve for self-reported sleep disturbance was parallel to that of Miedema and Vos but slightly lower. The proportion of the Hong Kong population exposed to high levels (>70 dB) is similar to that found in Europe. However, a much higher proportion, compared to European cities, is exposed to Lden levels of 60-64 dB, and a much lower proportion to lower levels (<55 dB). There is no evidence that the exposure-response relationships for annoyance and self-reported sleep disturbance in Hong Kong are different from relationships synthesized from earlier studies - despite the western bias and temperate-climate bias in the studies available in the syntheses. This is an important finding for urban planning and traffic noise management of the growing mega-cities in the world whose built forms can be expected to reflect that of Hong Kong more than of cities in the west.
Traffic safety facts 1996 : state alcohol estimates
DOT National Transportation Integrated Search
1998-01-01
The following data provide estimates of alcohol involvement in fatal crashes for the United States and individually for the 50 state, the District of Columbia, and Puerto Rico (not included in the national totals). These estimates are based on data f...
Automated delay estimation at signalized intersections : phase I concept and algorithm development.
DOT National Transportation Integrated Search
2011-07-01
Currently there are several methods to measure the performance of surface streets, but their capabilities in dynamically estimating vehicle delay are limited. The objective of this research is to develop a method to automate traffic delay estimation ...
NASA Astrophysics Data System (ADS)
Mu, Tingkui; Bao, Donghao; Zhang, Chunmin; Chen, Zeyu; Song, Jionghui
2018-07-01
During the calibration of the system matrix of a Stokes polarimeter using reference polarization states (RPSs) and pseudo-inversion estimation method, the measurement intensities are usually noised by the signal-independent additive Gaussian noise or signal-dependent Poisson shot noise, the precision of the estimated system matrix is degraded. In this paper, we present a paradigm for selecting RPSs to improve the precision of the estimated system matrix in the presence of both types of noise. The analytical solution of the precision of the system matrix estimated with the RPSs are derived. Experimental measurements from a general Stokes polarimeter show that accurate system matrix is estimated with the optimal RPSs, which are generated using two rotating quarter-wave plates. The advantage of using optimal RPSs is a reduction in measurement time with high calibration precision.
Istamto, Tifanny; Houthuijs, Danny; Lebret, Erik
2014-11-01
We conducted a multi-country study to estimate the perceived economic values of traffic-related air pollution and noise health risks within the framework of a large European project. We used contingent valuation as a method to assess the willingness-to-pay (WTP) for both types of pollutants simultaneously. We asked respondents how much they would be willing to pay annually to avoid certain health risks from specific pollutants. Three sets of vignettes with different levels of information were provided prior to the WTP questions. These vignettes described qualitative general health risks, a quantitative single health risk related to a pollutant, and a quantitative scenario of combined health risks related to a pollutant. The mean WTP estimates to avoid road-traffic air pollution effects for the three vignettes were: €130 per person per year (pp/y) for general health risks, €80 pp/y for a half year shorter in life expectancy, and €330 pp/y to a 50% decrease in road-traffic air pollution. Their medians were €40 pp/y, €10 pp/y and €50 pp/y, respectively. The mean WTP estimates to avoid road-traffic noise effects for the three vignettes were: €90 pp/y for general health risks, €100 pp/y for a 13% increase in severe annoyance, and €320 pp/y for a combined-risk scenario related to an increase of a noise level from 50 dB to 65 dB. Their medians were €20 pp/y, €20 pp/y and €50 pp/y, respectively. Risk perceptions and attitudes as well as environmental and pollutant concerns significantly affected WTP estimates. The observed differences in crude WTP estimates between countries changed considerably when perception-related variables were included in the WTP regression models. For this reason, great care should be taken when performing benefit transfer from studies in one country to another. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
Measurements of particles in the 5-1000 nm range close to road level in an urban street canyon.
Kumar, Prashant; Fennell, Paul; Britter, Rex
2008-02-15
A newly developed instrument, the 'fast response differential mobility spectrometer (DMS500)', was deployed to measure the particles in the 5-1000 nm range in a Cambridge (UK) street canyon. Measurements were taken for 7 weekdays (from 09:00 to 19:00 h) between 8 and 21 June 2006 at three heights close to the road level (i.e. 0.20 m, 1.0 m and 2.60 m). The main aims of the measurements were to investigate the dependence of particle number distributions (PNDs) and concentrations (PNCs) and their vertical variations on wind speed, wind direction, traffic volume, and to estimate the particle number flux (PNF) and the particle number emission factors (PNEF) for typical urban streets and driving conditions. Traffic was the main source of particles at the measurement site. Measured PNCs were inversely proportional to the reference wind speed and directly proportional to the traffic volume. During the periods of cross-canyon flow the PNCs were larger on the leeward side than the windward side of the street canyon showing a possible effect of the vortex circulation. The largest PNCs were unsurprisingly near to road level and the pollution sources. The PNCs measured at 0.20 m and 1.0 m were the same to within 0.5-12.5% indicating a well-mixed region and this was presumably due to the enhanced mixing from traffic produced turbulence. The PNCs at 2.60 m were lower by 10-40% than those at 0.20 m and 1.0 m, suggesting a possible concentration gradient in the upper part of the canyon. The PNFs were estimated using an idealised and an operational approach; they were directly proportional to the traffic volume confirming the traffic to be the main source of particles. The PNEF were estimated using an inverse modelling technique; the reported values were within a factor of 3 of those published in similar studies.
Park, Seungshik; Cho, Sung Yong; Bae, Min-Suk
2015-11-15
Daily PM2.5 measurements were carried out at a local roadway every sixth day from May 2011 to August 2013 to obtain seasonal quantitative information on the primary and secondary sources of two water-soluble organic carbon (WSOC) fractions. Filter samples were analyzed for OC, elemental carbon (EC), WSOC, hydrophilic and hydrophobic WSOC fractions (WSOC(HPI) and WSOC(HPO)), and ionic species. An XAD solid phase extraction method and a total organic carbon analyzer were used to isolate the two WSOC fractions and determine their amounts, respectively. The WSOC/OC and WSOC(HPI)/WSOC ratios were 0.62±0.13 and 0.47±0.14, respectively. Similar seasonal profiles in EC, OC, and WSOC concentrations were observed, with higher concentrations occurring in the cold season and lower concentrations in the warm season. However, opposite results were obtained in WSOC/OC and WSOC(HPI)/WSOC ratios, with the higher in the warm season and the lower in the cold season. Correlation analyses indicated that two WSOC fractions in winter were likely attributed to secondary formation processes, biomass burning (BB), and traffic emissions, while WSOC(HPI) observed in other seasons were associated with secondary formation processes similar to those of oxalate and secondary inorganic species. A positive matrix factorization (PMF) model was employed to investigate the sources of two WSOC fractions. PMF indicated that concentrations of WSOC fractions were affected by five sources: secondary NO3(-) related, secondary SO4(2-) and oxalate related, traffic emissions, BB emissions, and sea-salt. Throughout the study period, secondary organic aerosols were estimated to be the most dominant contributor of WSOC fractions, with higher contributions occurring in the warm seasons. The contribution of secondary aerosol formation processes (NO3(-) related+SO4(2-) and oxalate related) to WSOC(HPI) and WSOC(HPO) was on an average 56.2% (45.0-73.8%) and 47.7% (39.6-52.1%), respectively. The seasonal average contribution of WSOC(HPI) and WSOC(HPO) attributed to BB was 19.0% (14.3-25.3%) and 14.8% (7.2-19.5%), respectively, with higher fractions occurring in the fall and winter. Traffic sources contributed to WSOC(HPI) and WSOC(HPO) from 4.2 to 21.0% (an average of 11.6%) and from 7.9 to 32.3% (an average of 19.9%), respectively, with higher fractions in the fall and winter compared with the other seasons. During the study period, for an episode associated with high local O3 level (~110 ppbv) and high WSOC(HPI)/WSOC (0.80), secondary formation processes contributed 67.1% to WSOCHPI, and 72.6% to WSOC(HPO), respectively. However, for an episode associated with local and severe regional haze pollutions, contributions of secondary formation processes to WSOC fractions were observed to be low (32.4-43.1%), while traffic and BB emissions contributed 16.8% and 24.3% to WSOC(HPI), respectively, and 18.3% and 18.7% to WSOC(HPO), respectively. The PMF results suggest that the contribution of traffic emissions to concentrations of two WSOC fractions cannot be neglected at the studied roadway site. Copyright © 2015 Elsevier B.V. All rights reserved.
Socioeconomic position and low birth weight among mothers exposed to traffic-related air pollution.
Habermann, Mateus; Gouveia, Nelson
2014-01-01
Atmospheric pollution is a major public health concern. It can affect placental function and restricts fetal growth. However, scientific knowledge remains too limited to make inferences regarding causal associations between maternal exposure to air pollution and adverse effects on pregnancy. This study evaluated the association between low birth weight (LBW) and maternal exposure during pregnancy to traffic related air pollutants (TRAP) in São Paulo, Brazil. Analysis included 5,772 cases of term-LBW (<2,500 g) and 5,814 controls matched by sex and month of birth selected from the birth registration system. Mothers' addresses were geocoded to estimate exposure according to 3 indicators: distance from home to heavy traffic roads, distance-weighted traffic density (DWTD) and levels of particulate matter ≤10 µg/m3 estimated through land use regression (LUR-PM10). Final models were evaluated using multiple logistic regression adjusting for birth, maternal and pregnancy characteristics. We found decreased odds in the risk of LBW associated with DWTD and LUR-PM10 in the highest quartiles of exposure with a significant linear trend of decrease in risk. The analysis with distance from heavy traffic roads was less consistent. It was also observed that mothers with higher education and neighborhood-level income were potentially more exposed to TRAP. This study found an unexpected decreased risk of LBW associated with traffic related air pollution. Mothers with advantaged socioeconomic position (SEP) although residing in areas of higher vehicular traffic might not in fact be more expose to air pollution. It can also be that the protection against LBW arising from a better SEP is stronger than the effect of exposure to air pollution, and this exposure may not be sufficient to increase the risk of LBW for these mothers.
The Traffic Adaptive Data Dissemination (TrAD) Protocol for both Urban and Highway Scenarios.
Tian, Bin; Hou, Kun Mean; Zhou, Haiying
2016-06-21
The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs) are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC) protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD) protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination.
Bayes classifiers for imbalanced traffic accidents datasets.
Mujalli, Randa Oqab; López, Griselda; Garach, Laura
2016-03-01
Traffic accidents data sets are usually imbalanced, where the number of instances classified under the killed or severe injuries class (minority) is much lower than those classified under the slight injuries class (majority). This, however, supposes a challenging problem for classification algorithms and may cause obtaining a model that well cover the slight injuries instances whereas the killed or severe injuries instances are misclassified frequently. Based on traffic accidents data collected on urban and suburban roads in Jordan for three years (2009-2011); three different data balancing techniques were used: under-sampling which removes some instances of the majority class, oversampling which creates new instances of the minority class and a mix technique that combines both. In addition, different Bayes classifiers were compared for the different imbalanced and balanced data sets: Averaged One-Dependence Estimators, Weightily Average One-Dependence Estimators, and Bayesian networks in order to identify factors that affect the severity of an accident. The results indicated that using the balanced data sets, especially those created using oversampling techniques, with Bayesian networks improved classifying a traffic accident according to its severity and reduced the misclassification of killed and severe injuries instances. On the other hand, the following variables were found to contribute to the occurrence of a killed causality or a severe injury in a traffic accident: number of vehicles involved, accident pattern, number of directions, accident type, lighting, surface condition, and speed limit. This work, to the knowledge of the authors, is the first that aims at analyzing historical data records for traffic accidents occurring in Jordan and the first to apply balancing techniques to analyze injury severity of traffic accidents. Copyright © 2015 Elsevier Ltd. All rights reserved.
Socioeconomic Position and Low Birth Weight among Mothers Exposed to Traffic-Related Air Pollution
Habermann, Mateus; Gouveia, Nelson
2014-01-01
Background Atmospheric pollution is a major public health concern. It can affect placental function and restricts fetal growth. However, scientific knowledge remains too limited to make inferences regarding causal associations between maternal exposure to air pollution and adverse effects on pregnancy. This study evaluated the association between low birth weight (LBW) and maternal exposure during pregnancy to traffic related air pollutants (TRAP) in São Paulo, Brazil. Methods and findings Analysis included 5,772 cases of term-LBW (<2,500 g) and 5,814 controls matched by sex and month of birth selected from the birth registration system. Mothers’ addresses were geocoded to estimate exposure according to 3 indicators: distance from home to heavy traffic roads, distance-weighted traffic density (DWTD) and levels of particulate matter ≤10 µg/m3 estimated through land use regression (LUR-PM10). Final models were evaluated using multiple logistic regression adjusting for birth, maternal and pregnancy characteristics. We found decreased odds in the risk of LBW associated with DWTD and LUR-PM10 in the highest quartiles of exposure with a significant linear trend of decrease in risk. The analysis with distance from heavy traffic roads was less consistent. It was also observed that mothers with higher education and neighborhood-level income were potentially more exposed to TRAP. Conclusions This study found an unexpected decreased risk of LBW associated with traffic related air pollution. Mothers with advantaged socioeconomic position (SEP) although residing in areas of higher vehicular traffic might not in fact be more expose to air pollution. It can also be that the protection against LBW arising from a better SEP is stronger than the effect of exposure to air pollution, and this exposure may not be sufficient to increase the risk of LBW for these mothers. PMID:25426640
Environmental impacts of urban snow management--the alpine case study of Innsbruck.
Engelhard, C; De Toffol, S; Lek, I; Rauch, W; Dallinger, R
2007-09-01
In regions with colder climate, snow at roads can accumulate significant amounts of pollutant chemicals. In northern countries various efforts have been made to face this problem, but for the alpine region little is known about the pollution of urban snow. The present case study was carried out in the city of Innsbruck (Austria). It aimed at measuring pollution of roadside snow and estimating the impact of snow management practises on environmental quality. Concentrations of copper, zinc, lead, cadmium, suspended solids and chloride were determined during a series of sampling events. Various locations with low and high traffic densities and in different distances from a highway have been investigated. The concentrations of copper were generally higher at sites with high traffic density compared to locations with low traffic impact. In contrast to this, the concentrations of zinc and lead remained almost unvaried irrespective of traffic density at the different sampling sites. For cadmium, the picture was more diverse, showing moderately elevated concentrations of this metal also at the urban reference site not polluted by traffic. This indicates that there may be also other important sources for cadmium besides traffic. Suspended solids accumulated in the roadside snow, the highest concentrations were found at the sites with high traffic density. The chloride concentrations were considerable in the snow, especially at the highway. Based on the results of the present measurement campaign, the environmental impact of snow disposal in rivers was also estimated. A negative impact on rivers from snow disposal seems likely to occur, although the discharged loads could only be calculated with substantial uncertainty, considering the high variability of the measured pollutant concentrations. For a more accurate evaluation of this management practise on rivers, further investigations would be necessary.
The Traffic Adaptive Data Dissemination (TrAD) Protocol for both Urban and Highway Scenarios
Tian, Bin; Hou, Kun Mean; Zhou, Haiying
2016-01-01
The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs) are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC) protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD) protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination. PMID:27338393
Robust range estimation with a monocular camera for vision-based forward collision warning system.
Park, Ki-Yeong; Hwang, Sun-Young
2014-01-01
We propose a range estimation method for vision-based forward collision warning systems with a monocular camera. To solve the problem of variation of camera pitch angle due to vehicle motion and road inclination, the proposed method estimates virtual horizon from size and position of vehicles in captured image at run-time. The proposed method provides robust results even when road inclination varies continuously on hilly roads or lane markings are not seen on crowded roads. For experiments, a vision-based forward collision warning system has been implemented and the proposed method is evaluated with video clips recorded in highway and urban traffic environments. Virtual horizons estimated by the proposed method are compared with horizons manually identified, and estimated ranges are compared with measured ranges. Experimental results confirm that the proposed method provides robust results both in highway and in urban traffic environments.
Robust Range Estimation with a Monocular Camera for Vision-Based Forward Collision Warning System
2014-01-01
We propose a range estimation method for vision-based forward collision warning systems with a monocular camera. To solve the problem of variation of camera pitch angle due to vehicle motion and road inclination, the proposed method estimates virtual horizon from size and position of vehicles in captured image at run-time. The proposed method provides robust results even when road inclination varies continuously on hilly roads or lane markings are not seen on crowded roads. For experiments, a vision-based forward collision warning system has been implemented and the proposed method is evaluated with video clips recorded in highway and urban traffic environments. Virtual horizons estimated by the proposed method are compared with horizons manually identified, and estimated ranges are compared with measured ranges. Experimental results confirm that the proposed method provides robust results both in highway and in urban traffic environments. PMID:24558344
The traffic crisis and a tale of two cities: Traffic and air quality in Bangkok and Mexico City
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pendakur, V.S.; Badami, M.G.
1995-12-31
This paper focuses on congestion management techniques, traffic congestion levels and air quality. By using data from Bangkok and Mexico City, it illustrates the need for drastic changes in transportation policy tools and techniques for congestion management and for improving environmental quality. New approaches to investment and regulatory policy analysis and implementation are suggested. This requires the inclusion of all costs and benefits (economic and ecological) in the policy matrix so that investment and regulatory policies act in unison. Megacities are dominant in social, political and economic terms. 30 to 60% of national GDP is typically produced in these cities.more » Their human and motor vehicle populations have been doubling every 15-20 and 6-10 years respectively. They also have the most severe traffic congestion and air quality problems. They have the nation`s highest incidence of poverty and absolute poverty. Large portions of their populations endure severely unhealthy housing and sanitation conditions. Following are important characteristics of urban transportation systems in the megacities: the city centres are heavily congested with motorized traffic; traffic crawl rates vary from 2 to 10 km/hr; car and motorcycle ownership are increasing at annual rates of 10-12% and 15-20% respectively; significant air pollution with no relief in sight; TDM strategies are primarily creating new supply of road capacity; fairly high transit trips with substantial transit investments; weak air pollution monitoring and enforcement; and fairly cheap fuel and high costs of vehicles.« less
Assessment of Traffic-Related Noise in Three Cities in the United States
Lee, Eunice Y.; Jerrett, Michael; Ross, Zev; Coogan, Patricia F.; Seto, Edmund Y. W.
2014-01-01
Background Traffic-related noise is a growing public health concern in developing and developed countries due to increasing vehicle traffic. Epidemiological studies have reported associations between noise exposure and high blood pressure, increased risk of hypertension and heart disease, and stress induced by sleep disturbance and annoyance. These findings motivate the need for regular noise assessments within urban areas. This paper assesses the relationships between traffic and noise in three US cities. Methods Noise measurements were conducted in downtown areas in three cities in the United States: Atlanta, Los Angeles, and New York City. For each city, we measured ambient noise levels, and assessed their correlation with simultaneously measured vehicle counts, and with traffic data provided by local Metropolitan Planning Organizations (MPO). Additionally, measured noise levels were compared to noise levels predicted by the Federal Highway Administration’s Traffic Noise Model using (1) simultaneously measured traffic counts or (2) MPO traffic data sources as model input. Results We found substantial variations in traffic and noise within and between cities. Total number of vehicle counts explained a substantial amount of variation in measured ambient noise in Atlanta (78%), Los Angeles (58%), and New York City (62%). Modeled noise levels were moderately correlated with measured noise levels when observed traffic counts were used as model input. Weaker correlations were found when MPO traffic data was used as model input. Conclusions Ambient noise levels measured in all three cities were correlated with traffic data, highlighting the importance of traffic planning in mitigating noise-related health effects. Model performance was sensitive to the traffic data used as input. Future noise studies that use modeled noise estimates should evaluate traffic data quality and should ideally include other factors, such as local roadway, building, and meteorological characteristics. PMID:24792415
Fan, Yaxin; Zhu, Xinyan; Guo, Wei; Guo, Tao
2018-01-01
The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions. PMID:29672551
NASA Astrophysics Data System (ADS)
Gunawan, Fergyanto E.; Abbas, Bahtiar S.; Atmadja, Wiedjaja; Yoseph Chandra, Fajar; Agung, Alexander AS; Kusnandar, Erwin
2014-03-01
Traffic congestion in Asian megacities has become extremely worse, and any means to lessen the congestion level is urgently needed. Building an efficient mass transportation system is clearly necessary. However, implementing Intelligent Transportation Systems (ITS) have also been demonstrated effective in various advanced countries. Recently, the floating vehicle technique (FVT), an ITS implementation, has become cost effective to provide real-time traffic information with proliferation of the smartphones. Although many publications have discussed various issues related to the technique, none of them elaborates the discrepancy of a single floating car data (FCD) and the associated fleet data. This work addresses the issue based on an analysis of Sugiyama et al's experimental data. The results indicate that there is an optimum averaging time interval such that the estimated velocity by the FVT reasonably representing the traffic velocity.
Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant
Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa
2013-09-17
System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.
High-luminance LEDs replace incandescent lamps in new applications
NASA Astrophysics Data System (ADS)
Evans, David L.
1997-04-01
The advent of high luminance AlInGaP and InGaN LED technologies has prompted the use of LED devices in new applications formally illuminated by incandescent lamps. The luminous efficiencies of these new LED technologies equals or exceeds that attainable with incandescent sources, with reliability factors that far exceed those of incandescent sources. The need for a highly efficient, dependable, and cost effective replacement for incandescent lamps is being fulfilled with high luminance LED lamps. This paper briefly described some of the new applications incorporating high luminance LED lamps, traffic signals and roadway signs for traffic management, automotive exterior lighting, active matrix and full color displays for commercial advertising, and commercial aircraft panel lighting and military aircraft NVG compatible lighting.
NASA Astrophysics Data System (ADS)
Yu, Nan; Cao, Yu
2017-05-01
The traffic demand elastic is proposed as a new indicator in this study to measure the feasibility of the high-speed railway construction in a more intuitive way. The Matrix Completion (MC) and Semi-Supervised Support Vector Machine (S3VM) are used to realize the measurement and prediction of this index on the basis of the satisfaction investigation on the 326 inter-city railways in china. It is demonstrated that instead of calculating the economic benefits brought by the construction of high-speed railway, this indicator can find the most urgent railways to be improved by directly evaluate the existing railway facilities from the perspective of transportation service improvement requirements.
Tétreault, Louis-François; Perron, Stéphane; Smargiassi, Audrey
2013-10-01
This review assessed the confounding effect of one traffic-related exposure (noise or air pollutants) on the association between the other exposure and cardiovascular outcomes. A systematic review was conducted with the databases Medline and Embase. The confounding effects in studies were assessed by using change in the estimate with a 10 % cutoff point. The influence on the change in the estimate of the quality of the studies, the exposure assessment methods and the correlation between road noise and air pollutions were also assessed. Nine publications were identified. For most studies, the specified confounders produced changes in estimates <10 %. The correlation between noise and pollutants, the quality of the study and of the exposure assessment do not seem to influence the confounding effects. Results from this review suggest that confounding of cardiovascular effects by noise or air pollutants is low, though with further improvements in exposure assessment, the situation may change. More studies using pollution indicators specific to road traffic are needed to properly assess if noise and air pollution are subjected to confounding.
Indirect Validation of Probe Speed Data on Arterial Corridors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eshragh, Sepideh; Young, Stanley E.; Sharifi, Elham
This study aimed to estimate the accuracy of probe speed data on arterial corridors on the basis of roadway geometric attributes and functional classification. It was assumed that functional class (medium and low) along with other road characteristics (such as weighted average of the annual average daily traffic, average signal density, average access point density, and average speed) were available as correlation factors to estimate the accuracy of probe traffic data. This study tested these factors as predictors of the fidelity of probe traffic data by using the results of an extensive validation exercise. This study showed strong correlations betweenmore » these geometric attributes and the accuracy of probe data when they were assessed by using average absolute speed error. Linear models were regressed to existing data to estimate appropriate models for medium- and low-type arterial corridors. The proposed models for medium- and low-type arterials were validated further on the basis of the results of a slowdown analysis. These models can be used to predict the accuracy of probe data indirectly in medium and low types of arterial corridors.« less
Traffic-related air pollution and congenital anomalies in Barcelona.
Schembari, Anna; Nieuwenhuijsen, Mark J; Salvador, Joaquin; de Nazelle, Audrey; Cirach, Marta; Dadvand, Payam; Beelen, Rob; Hoek, Gerard; Basagaña, Xavier; Vrijheid, Martine
2014-03-01
A recent meta-analysis suggested evidence for an effect of exposure to ambient air pollutants on risk of certain congenital heart defects. However, few studies have investigated the effects of traffic-related air pollutants with sufficient spatial accuracy. We estimated associations between congenital anomalies and exposure to traffic-related air pollution in Barcelona, Spain. Cases with nonchromosomal anomalies (n = 2,247) and controls (n = 2,991) were selected from the Barcelona congenital anomaly register during 1994-2006. Land use regression models from the European Study of Cohorts for Air Pollution Effects (ESCAPE), were applied to residential addresses at birth to estimate spatial exposure to nitrogen oxides and dioxide (NOx, NO2), particulate matter with diameter ≤ 10 μm (PM10), 10-2.5 μm (PMcoarse), ≤ 2.5 μm (PM2.5), and PM2.5 absorbance. Spatial estimates were adjusted for temporal trends using data from routine monitoring stations for weeks 3-8 of each pregnancy. Logistic regression models were used to calculate odds ratios (ORs) for 18 congenital anomaly groups associated with an interquartile-range (IQR) increase in exposure estimates. In spatial and spatiotemporal exposure models, we estimated statistically significant associations between an IQR increase in NO2 (12.2 μg/m3) and coarctation of the aorta (ORspatiotemporal = 1.15; 95% CI: 1.01, 1.31) and digestive system defects (ORspatiotemporal = 1.11; 95% CI: 1.00, 1.23), and between an IQR increase in PMcoarse (3.6 μg/m3) and abdominal wall defects (ORspatiotemporal = 1.93; 95% CI: 1.37, 2.73). Other statistically significant increased and decreased ORs were estimated based on the spatial model only or the spatiotemporal model only, but not both. Our results overall do not indicate an association between traffic-related air pollution and most groups of congenital anomalies. Findings for coarctation of the aorta are consistent with those of the previous meta-analysis. Schembari A, Nieuwenhuijsen MJ, Salvador J, de Nazelle A, Cirach M, Dadvand P, Beelen R, Hoek G, Basagaña X, Vrijheid M. 2014. Traffic-related air pollution and congenital anomalies in Barcelona. Environ Health Perspect 122:317-323; http://dx.doi.org/10.1289/ehp.1306802.
Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei
2014-01-01
The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.
Cortez-Lugo, Marlene; Escamilla-Núñez, Consuelo; Barraza-Villarreal, Albino; Texcalac-Sangrador, José Luis; Chow, Judith; Watson, John; Hernández-Cadena, Leticia; Romieu, Isabelle
2013-04-01
To study the relationship between light absorption measurements of PM2.5 at various distances from heavy traffic roads and diesel vehicle counts in Mexico City. PM2.5 samples were obtained from June 2003-June 2005 in three MCMA regions. Light absorption (b abs) in a subset of PM2.5 samples was determined. We evaluated the effect of distance and diesel vehicle counts to heavy traffic roads on PM2.5 b abs using generalized estimating equation models. Median PM2.5 b abs measurements significantly decrease as distance from heavy traffic roads increases (p<0.002); levels decreased by 7% (CI95% 0.9-14) for each 100 additional meters from heavy traffic roads. Our model predicts that PM2.5 b abs measurements would increase by 20% (CI95% 3-38) as the hourly heavy diesel vehicle count increases by 150 per hour. PM2.5 b abs measurements are significantly associated with distance from motorways and traffic density and therefore can be used to assess human exposure to traffic-related emissions.
Shafer, Paul R; Davis, Kevin C; Patel, Deesha; Rodes, Robert; Beistle, Diane
2016-02-17
In 2012, the US Centers for Disease Control and Prevention (CDC) launched Tips From Former Smokers (Tips), the first federally funded national tobacco education campaign. In 2013, a follow-up Tips campaign aired on national cable television networks, radio, and other channels, with supporting digital advertising to drive traffic to the Tips campaign website. The objective of this study was to use geographic and temporal variability in 2013 Tips campaign television media doses and ad tagging to evaluate changes in traffic to the campaign website in response to specific doses of campaign media. Linear regression models were used to estimate the dose-response relationship between weekly market-level television gross rating points (GRPs) and weekly Web traffic to the Tips campaign website. This relationship was measured using unique visitors, total visits, and page views as outcomes. Ad GRP effects were estimated separately for ads tagged with the Tips campaign website URL and 1-800-QUIT-NOW. In the average media market, an increase of 100 television GRPs per week for ads tagged with the Tips campaign website URL was associated with an increase of 650 unique visitors (P<.001), 769 total visits (P<.001), and 1255 total page views (P<.001) per week. The associations between GRPs for ads tagged with 1-800-QUIT-NOW and each Web traffic measure were also statistically significant (P<.001), but smaller in magnitude. Based on these findings, we estimate that the 16-week 2013 Tips television campaign generated approximately 660,000 unique visitors, 900,000 total visits, and 1,390,000 page views for the Tips campaign website. These findings can help campaign planners forecast the likely impact of targeted advertising efforts on consumers' use of campaign-specific websites.
Tzivian, Lilian; Jokisch, Martha; Winkler, Angela; Weimar, Christian; Hennig, Frauke; Sugiri, Dorothea; Soppa, Vanessa J; Dragano, Nico; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Hoffmann, Barbara
2017-06-01
Adverse effects of traffic-related air pollution (AP) and noise on cognitive functions have been proposed, but little is known about their interactions and the combined effect of co-exposure. Cognitive assessment was completed by 4086 participants of the population-based Heinz Nixdorf Recall cohort study using five neuropsychological subtests and an additively calculated global cognitive score (GCS). We assessed long-term residential concentrations for size-fractioned particulate matter (PM) and nitrogen oxides with land use regression. Road traffic noise (weighted 24-h (L DEN ) and night-time (L NIGHT ) means) was assessed according to the EU directive 2002/49/EC. Linear regression models adjusted for individual-level characteristics were calculated to estimate effect modification of associations between AP and noise with cognitive function. We used multiplicative interaction terms and categories of single or double high exposure, dichotomizing the potential effect modifier at the median (AP) or at an a priori defined threshold (road traffic noise). In fully adjusted models, high noise exposure increased the association of AP with cognitive function. For example, for an interquartile range increase of PM 2.5 (IQR 1.43), association s with GCS were: estimate (β)=-0.16 [95% confidence interval: -0.33; 0.01] and β=-0.48 [-0.72; -0.23] for low and high L DEN , respectively. The association of noise with GCS was restricted to highly AP-exposed participants. We observed stronger negative associations in those participants with double exposure compared to the addition of effect estimates of each single exposure. Our study suggests that AP and road traffic noise might act synergistically on cognitive function in adults. Copyright © 2017 Elsevier Ltd. All rights reserved.
Traffic pollution and the incidence of cardiorespiratory outcomes in an adult cohort in London.
Carey, I M; Anderson, H R; Atkinson, R W; Beevers, S; Cook, D G; Dajnak, D; Gulliver, J; Kelly, F J
2016-12-01
The epidemiological evidence for adverse health effects of long-term exposure to air and noise pollution from traffic is not coherent. Further, the relative roles of background versus near traffic pollution concentrations in this process are unclear. We investigated relationships between modelled concentrations of air and noise pollution from traffic and incident cardiorespiratory disease in London. Among 211 016 adults aged 40-79 years registered in 75 Greater London practices between 2005 and 2011, the first diagnosis for a range of cardiovascular and respiratory outcomes were identified from primary care and hospital records. Annual baseline concentrations for nitrogen oxide (NO x ), particulate matter with a median aerodynamic diameter <2.5 μm (PM 2.5 ) attributable to exhaust and non-exhaust sources, traffic intensity and noise were estimated at 20 m 2 resolution from dispersion models, linked to clinical data via residential postcode. HRs were adjusted for confounders including smoking and area deprivation. The largest observed associations were between traffic-related air pollution and heart failure (HR=1.10 for 20 μg/m 3 change in NO x , 95% CI 1.01 to 1.21). However, no other outcomes were consistently associated with any of the pollution indicators, including noise. The greater variations in modelled air pollution from traffic between practices, versus within, hampered meaningful fine spatial scale analyses. The associations observed with heart failure may suggest exacerbatory effects rather than underlying chronic disease. However, the overall failure to observe wider associations with traffic pollution may reflect that exposure estimates based on residence inadequately represent the relevant pattern of personal exposure, and future studies must address this issue. 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/.
Towards an integrated approach of pedestrian behaviour and exposure.
Papadimitriou, Eleonora
2016-07-01
In this paper, an integrated methodology for the analysis of pedestrian behaviour and exposure is proposed, allowing to identify and quantify the effect of pedestrian behaviour, road and traffic characteristics on pedestrian risk exposure, for each pedestrian and for populations of pedestrians. The paper builds on existing research on pedestrian exposure, namely the Routledge microscopic indicator, proposes adjustments to take into account road, traffic and human factors and extends the use of this indicator on area-wide level. Moreover, this paper uses integrated choice and latent variables (ICLV) models of pedestrian behaviour, taking into account road, traffic and human factors. Finally, a methodology is proposed for the integrated estimation of pedestrian behaviour and exposure on the basis of road, traffic and human factors. The method is tested with data from a field survey in Athens, Greece, which used pedestrian behaviour observations as well as a questionnaire on human factors of pedestrian behaviour. The data were used (i) to develop ICLV models of pedestrian behaviour and (ii) to estimate the behaviour and exposure of pedestrians for different road, traffic and behavioural scenarios. The results suggest that both pedestrian behaviour and exposure are largely defined by a small number of factors: road type, traffic volume and pedestrian risk-taking. The probability for risk-taking behaviour and the related exposure decrease in less demanding road and traffic environments. A synthesis of the results allows to enhance the understanding of the interactions between behaviour and exposure of pedestrians and to identify conditions of increased risk exposure. These conditions include principal urban arterials (where risk-taking behaviour is low but the related exposure is very high) and minor arterials (where risk-taking behaviour is more frequent, and the related exposure is still high). A "paradox" of increased risk-taking behaviour of pedestrians with low exposure is found, suggesting that these pedestrians may partly compensate in moderate traffic conditions due to their increased walking speed. Copyright © 2016 Elsevier Ltd. All rights reserved.
Predicting traffic load impact of alternative recreation developments
Gary H. Elsner; Ronald A. Oliveira
1973-01-01
Traffic load changes as a result of expansion of recreation facilities may be predicted through computations based on estimates of (a) drawing power of the recreation attracttions, overnight accommodations, and in- or out-terminals; (b) probable types of travel; (c) probable routes of travel; and (d) total number of cars in the recreation system. Once the basic model...
Multiple Vehicle Detection and Segmentation in Malaysia Traffic Flow
NASA Astrophysics Data System (ADS)
Fariz Hasan, Ahmad; Fikri Che Husin, Mohd; Affendi Rosli, Khairul; Norhafiz Hashim, Mohd; Faiz Zainal Abidin, Amar
2018-03-01
Vision based system are widely used in the field of Intelligent Transportation System (ITS) to extract a large amount of information to analyze traffic scenes. By rapid number of vehicles on the road as well as significant increase on cameras dictated the need for traffic surveillance systems. This system can take over the burden some task was performed by human operator in traffic monitoring centre. The main technique proposed by this paper is concentrated on developing a multiple vehicle detection and segmentation focusing on monitoring through Closed Circuit Television (CCTV) video. The system is able to automatically segment vehicle extracted from heavy traffic scene by optical flow estimation alongside with blob analysis technique in order to detect the moving vehicle. Prior to segmentation, blob analysis technique will compute the area of interest region corresponding to moving vehicle which will be used to create bounding box on that particular vehicle. Experimental validation on the proposed system was performed and the algorithm is demonstrated on various set of traffic scene.
Annual update of data for estimating ESALs.
DOT National Transportation Integrated Search
2006-10-01
A revised procedure for estimating equivalent single axleloads (ESALs) was developed in 1985. This procedure used weight, classification, and traffic volume data collected by the Transportation Cabinet's Division of Planning. : Annual updates of data...
NASA Astrophysics Data System (ADS)
Brewick, Patrick T.; Smyth, Andrew W.
2016-12-01
The authors have previously shown that many traditional approaches to operational modal analysis (OMA) struggle to properly identify the modal damping ratios for bridges under traffic loading due to the interference caused by the driving frequencies of the traffic loads. This paper presents a novel methodology for modal parameter estimation in OMA that overcomes the problems presented by driving frequencies and significantly improves the damping estimates. This methodology is based on finding the power spectral density (PSD) of a given modal coordinate, and then dividing the modal PSD into separate regions, left- and right-side spectra. The modal coordinates were found using a blind source separation (BSS) algorithm and a curve-fitting technique was developed that uses optimization to find the modal parameters that best fit each side spectra of the PSD. Specifically, a pattern-search optimization method was combined with a clustering analysis algorithm and together they were employed in a series of stages in order to improve the estimates of the modal damping ratios. This method was used to estimate the damping ratios from a simulated bridge model subjected to moving traffic loads. The results of this method were compared to other established OMA methods, such as Frequency Domain Decomposition (FDD) and BSS methods, and they were found to be more accurate and more reliable, even for modes that had their PSDs distorted or altered by driving frequencies.
Risk assessment of drinking water in a reservoir contaminated by PAH's originated from road traffic.
Ishimaru, T; Inouye, H; Morioka, T
1990-04-01
The loads of Polycyclic Aromatic Hydrocarbons (PAHs) originating from road traffic were measured and in units of per vehicle per meter was estimated as follows: 0.07 ng/veh.m for Benzo[a]pyrene, and 0.83 ng/veh.m for Dibenzanthracene and so on, and 5.77 ng/veh.m for total PAHs. This unit is applied to risk estimation of drinking water in a reservoir where it is planned to construct a new high way the near future, and the concentration in the reservoir water is estimated to be 3.3-101 ng/l for individual PAH's. Assuming standard oral exposure to PAHs in raw water for drinking water supply, the estimated lifetime risk of carcinogenesis was less than 1 in 10(6), which is not considered significant.
Estimating Traffic Accidents in Turkey Using Differential Evolution Algorithm
NASA Astrophysics Data System (ADS)
Akgüngör, Ali Payıdar; Korkmaz, Ersin
2017-06-01
Estimating traffic accidents play a vital role to apply road safety procedures. This study proposes Differential Evolution Algorithm (DEA) models to estimate the number of accidents in Turkey. In the model development, population (P) and the number of vehicles (N) are selected as model parameters. Three model forms, linear, exponential and semi-quadratic models, are developed using DEA with the data covering from 2000 to 2014. Developed models are statistically compared to select the best fit model. The results of the DE models show that the linear model form is suitable to estimate the number of accidents. The statistics of this form is better than other forms in terms of performance criteria which are the Mean Absolute Percentage Errors (MAPE) and the Root Mean Square Errors (RMSE). To investigate the performance of linear DE model for future estimations, a ten-year period from 2015 to 2024 is considered. The results obtained from future estimations reveal the suitability of DE method for road safety applications.
Estimation of a cover-type change matrix from error-prone data
Steen Magnussen
2009-01-01
Coregistration and classification errors seriously compromise per-pixel estimates of land cover change. A more robust estimation of change is proposed in which adjacent pixels are grouped into 3x3 clusters and treated as a unit of observation. A complete change matrix is recovered in a two-step process. The diagonal elements of a change matrix are recovered from...
NASA Technical Reports Server (NTRS)
White, B. S.; Castleman, K. R.
1981-01-01
An important step in the diagnosis of a cervical cytology specimen is estimating the proportions of the various cell types present. This is usually done with a cell classifier, the error rates of which can be expressed as a confusion matrix. We show how to use the confusion matrix to obtain an unbiased estimate of the desired proportions. We show that the mean square error of this estimate depends on a 'befuddlement matrix' derived from the confusion matrix, and how this, in turn, leads to a figure of merit for cell classifiers. Finally, we work out the two-class problem in detail and present examples to illustrate the theory.
[Health risk assessment of traffic-related air pollution near busy roads].
Host, S; Chatignoux, E; Leal, C; Grémy, I
2012-08-01
Although ambient urban air pollution has well-established health effects, epidemiology faces many difficulties in estimating the risks due to exposure to traffic pollutants near busy roads. This review aims to summarize how exposure to traffic-related air pollution near busy roads is assessed in epidemiological studies and main findings regarding health effects. After presenting the specificity of emissions due to traffic road, this review identifies the key methods and main results found in epidemiologic studies seeking to measure the influence of exposure to nearby traffic on health published over the past decade. The characterization and measurement of population exposure to traffic pollution faces many difficulties. Thus, epidemiological studies have used two broad categories of surrogates to assess exposure: direct measures of traffic itself such as distance of the residence to the nearest road and traffic volume and modeled concentrations of pollutant surrogates. Studies that implemented these methods showed that people living near heavy traffic road or exposed to near-road air pollution tend to report more health outcomes. Traffic-related air pollution near busy roads is the subject of increasing attention, and tends to be better characterized. However, its health impacts remain difficult to grasp, especially because of the vast diversity of approaches used in epidemiological studies. Greater consistency in the protocols would be desirable to provide better understanding of the health issue of traffic in urban areas and thus to better implement policies to protect those most at risk. Copyright © 2012 Elsevier Masson SAS. All rights reserved.
NASA Astrophysics Data System (ADS)
Islamiyati, A.; Fatmawati; Chamidah, N.
2018-03-01
The correlation assumption of the longitudinal data with bi-response occurs on the measurement between the subjects of observation and the response. It causes the auto-correlation of error, and this can be overcome by using a covariance matrix. In this article, we estimate the covariance matrix based on the penalized spline regression model. Penalized spline involves knot points and smoothing parameters simultaneously in controlling the smoothness of the curve. Based on our simulation study, the estimated regression model of the weighted penalized spline with covariance matrix gives a smaller error value compared to the error of the model without covariance matrix.
Abou-Senna, Hatem; Radwan, Essam; Westerlund, Kurt; Cooper, C David
2013-07-01
The Intergovernmental Panel on Climate Change (IPCC) estimates that baseline global GHG emissions may increase 25-90% from 2000 to 2030, with carbon dioxide (CO2 emissions growing 40-110% over the same period. On-road vehicles are a major source of CO2 emissions in all the developed countries, and in many of the developing countries in the world. Similarly, several criteria air pollutants are associated with transportation, for example, carbon monoxide (CO), nitrogen oxides (NO(x)), and particulate matter (PM). Therefore, the need to accurately quantify transportation-related emissions from vehicles is essential. The new US. Environmental Protection Agency (EPA) mobile source emissions model, MOVES2010a (MOVES), can estimate vehicle emissions on a second-by-second basis, creating the opportunity to combine a microscopic traffic simulation model (such as VISSIM) with MOVES to obtain accurate results. This paper presents an examination of four different approaches to capture the environmental impacts of vehicular operations on a 10-mile stretch of Interstate 4 (I-4), an urban limited-access highway in Orlando, FL. First (at the most basic level), emissions were estimated for the entire 10-mile section "by hand" using one average traffic volume and average speed. Then three advanced levels of detail were studied using VISSIM/MOVES to analyze smaller links: average speeds and volumes (AVG), second-by-second link drive schedules (LDS), and second-by-second operating mode distributions (OPMODE). This paper analyzes how the various approaches affect predicted emissions of CO, NO(x), PM2.5, PM10, and CO2. The results demonstrate that obtaining precise and comprehensive operating mode distributions on a second-by-second basis provides more accurate emission estimates. Specifically, emission rates are highly sensitive to stop-and-go traffic and the associated driving cycles of acceleration, deceleration, and idling. Using the AVG or LDS approach may overestimate or underestimate emissions, respectively, compared to an operating mode distribution approach. Transportation agencies and researchers in the past have estimated emissions using one average speed and volume on a long stretch of roadway. With MOVES, there is an opportunity for higher precision and accuracy. Integrating a microscopic traffic simulation model (such as VISSIM) with MOVES allows one to obtain precise and accurate emissions estimates. The proposed emission rate estimation process also can be extended to gridded emissions for ozone modeling, or to localized air quality dispersion modeling, where temporal and spatial resolution of emissions is essential to predict the concentration of pollutants near roadways.
Andreuccetti, Gabriel; Ye, Yu; Kang, Jaewook; Korcha, Rachael; Witbrodt, Jane A.; Carvalho, Heraclito B.; Cherpitel, Cheryl J.
2018-01-01
Recent evidence has indicated that cannabis use before driving is associated with a modest but increased risk for traffic-related injuries. However, the question of whether recent cannabis use is associated with a greater risk for other types of injuries remains unanswered. Aiming to understand better how acute cannabis use might affect the risk for all causes of injury, we have summarized the limited data available in the literature on the risk of non-traffic injuries associated with recent cannabis use. Very few studies were able to provide estimate risks for all injuries or injuries other than those related to road traffic injuries, with the limited evidence available showing mixed findings. The only significant risk found (in only one study) suggests an inverse association between all injuries and cannabis use. Study designs are limited, and the majority of studies have neither data on acute cannabis use among injured individuals nor a valid control group for estimating injury risk attributable to cannabis. In conclusion, studies of the association between cannabis and non-traffic injuries present several limitations, particularly regarding sampling strategies, injury risk assessment for different causes of injury, and a dose-response risk relationship with injury. Further studies, incorporating better design for different causes of injury and drug testing, are required to reach firmer conclusions on the association between cannabis use and non-traffic injury risk. PMID:29456273
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.
Seto, Edmund Yet Wah; Holt, Ashley; Rivard, Tom; Bhatia, Rajiv
2007-01-01
Background: Vehicle traffic is the major source of noise in urban environments, which in turn has multiple impacts on health. In this paper we investigate the spatial distribution of community noise exposures and annoyance. Traffic data from the City of San Francisco were used to model noise exposure by neighborhood and road type. Remote sensing data were used in the model to estimate neighborhood-specific percentages of cars, trucks, and buses on arterial versus non-arterial streets. The model was validated on 235 streets. Finally, an exposure-response relationship was used to predict the prevalence of high annoyance for different neighborhoods. Results: Urban noise was found to increase 6.7 dB (p < 0.001) with 10-fold increased street traffic, with important contributors to noise being bus and heavy truck traffic. Living along arterial streets also increased risk of annoyance by 40%. The relative risk of annoyance in one of the City's fastest growing neighborhoods, the South of Market Area, was found to be 2.1 times that of lowest noise neighborhood. However, higher densities of exposed individuals were found in Chinatown and Downtown/Civic Center. Overall, we estimated that 17% of the city's population was at risk of high annoyance from traffic noise. Conclusion: The risk of annoyance from urban noise is large, and varies considerably between neighborhoods. Such risk should be considered in urban areas undergoing rapid growth. We present a relatively simple GIS-based noise model that may be used for routinely evaluating the health impacts of environmental noise. PMID:17584947
Henry, Kevin; Wood, Nathan J.; Frazier, Tim G.
2017-01-01
Tsunami evacuation planning in coastal communities is typically focused on local events where at-risk individuals must move on foot in a matter of minutes to safety. Less attention has been placed on distant tsunamis, where evacuations unfold over several hours, are often dominated by vehicle use and are managed by public safety officials. Traditional traffic simulation models focus on estimating clearance times but often overlook the influence of varying population demand, alternative modes, background traffic, shadow evacuation, and traffic management alternatives. These factors are especially important for island communities with limited egress options to safety. We use the coastal community of Balboa Island, California (USA), as a case study to explore the range of potential clearance times prior to wave arrival for a distant tsunami scenario. We use a first-in–first-out queuing simulation environment to estimate variations in clearance times, given varying assumptions of the evacuating population (demand) and the road network over which they evacuate (supply). Results suggest clearance times are less than wave arrival times for a distant tsunami, except when we assume maximum vehicle usage for residents, employees, and tourists for a weekend scenario. A two-lane bridge to the mainland was the primary traffic bottleneck, thereby minimizing the effect of departure times, shadow evacuations, background traffic, boat-based evacuations, and traffic light timing on overall community clearance time. Reducing vehicular demand generally reduced clearance time, whereas improvements to road capacity had mixed results. Finally, failure to recognize non-residential employee and tourist populations in the vehicle demand substantially underestimated clearance time.
Hybrid Air Quality Modeling Approach For Use in the Near ...
The Near-road EXposures to Urban air pollutant Study (NEXUS) investigated whether children with asthma living in close proximity to major roadways in Detroit, MI, (particularly near roadways with high diesel traffic) have greater health impacts associated with exposure to air pollutants than those living farther away. A major challenge in such health and exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. This paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the AERMOD and R-LINE dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multiscale Air Quality (CMAQ) model and the Space/Time Ordinary Kriging (STOK) model. To capture the near-road pollutant gradients, refined “mini-grids” of model recep
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.
High blood pressure and long-term exposure to indoor noise and air pollution from road traffic.
Foraster, Maria; Künzli, Nino; Aguilera, Inmaculada; Rivera, Marcela; Agis, David; Vila, Joan; Bouso, Laura; Deltell, Alexandre; Marrugat, Jaume; Ramos, Rafel; Sunyer, Jordi; Elosua, Roberto; Basagaña, Xavier
2014-11-01
Traffic noise has been associated with prevalence of hypertension, but reports are inconsistent for blood pressure (BP). To ascertain noise effects and to disentangle them from those suspected to be from traffic-related air pollution, it may be essential to estimate people's noise exposure indoors in bedrooms. We analyzed associations between long-term exposure to indoor traffic noise in bedrooms and prevalent hypertension and systolic (SBP) and diastolic (DBP) BP, considering long-term exposure to outdoor nitrogen dioxide (NO2). We evaluated 1,926 cohort participants at baseline (years 2003-2006; Girona, Spain). Outdoor annual average levels of nighttime traffic noise (Lnight) and NO2 were estimated at postal addresses with a detailed traffic noise model and a land-use regression model, respectively. Individual indoor traffic Lnight levels were derived from outdoor Lnight with application of insulations provided by reported noise-reducing factors. We assessed associations for hypertension and BP with multi-exposure logistic and linear regression models, respectively. Median levels were 27.1 dB(A) (indoor Lnight), 56.7 dB(A) (outdoor Lnight), and 26.8 μg/m3 (NO2). Spearman correlations between outdoor and indoor Lnight with NO2 were 0.75 and 0.23, respectively. Indoor Lnight was associated both with hypertension (OR = 1.06; 95% CI: 0.99, 1.13) and SBP (β = 0.72; 95% CI: 0.29, 1.15) per 5 dB(A); and NO2 was associated with hypertension (OR = 1.16; 95% CI: 0.99, 1.36), SBP (β = 1.23; 95% CI: 0.21, 2.25), and DBP (β⊇= 0.56; 95% CI: -0.03, 1.14) per 10 μg/m3. In the outdoor noise model, Lnight was associated only with hypertension and NO2 with BP only. The indoor noise-SBP association was stronger and statistically significant with a threshold at 30 dB(A). Long-term exposure to indoor traffic noise was associated with prevalent hypertension and SBP, independently of NO2. Associations were less consistent for outdoor traffic Lnight and likely affected by collinearity.
A microcomputer based traffic evacuation modeling system for emergency planning application
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rathi, A.K.
1994-12-01
Vehicular evacuation is one of the major and often preferred protective action options available for emergency management in a real or anticipated disaster. Computer simulation models of evacuation traffic flow are used to estimate the time required for the affected populations to evacuate to safer areas, to evaluate effectiveness of vehicular evacuations as a protective action option. and to develop comprehensive evacuation plans when required. Following a review of the past efforts to simulate traffic flow during emergency evacuations, an overview of the key features in Version 2.0 of the Oak Ridge Evacuation Modeling System (OREMS) are presented in thismore » paper. OREMS is a microcomputer-based model developed to simulate traffic flow during regional emergency evacuations. OREMS integrates a state-of-the-art dynamic traffic flow and simulation model with advanced data editing and output display programs operating under a MS-Windows environment.« less
Road-traffic injuries: confronting disparities to address a global-health problem.
Ameratunga, Shanthi; Hijar, Martha; Norton, Robyn
2006-05-06
Evidence suggests that the present and projected global burden of road-traffic injuries is disproportionately borne by countries that can least afford to meet the health service, economic, and societal challenges posed. Although the evidence base on which these estimates are made remains somewhat precarious in view of the limited data systems in most low-income and middle-income countries (as per the classification on the World Bank website), these projections highlight the essential need to address road-traffic injuries as a public-health priority. Most well-evaluated effective interventions do not directly focus on efforts to protect vulnerable road users, such as motorcyclists and pedestrians. Yet, these groups comprise the majority of road-traffic victims in low-income and middle-income countries, and consequently, the majority of the road-traffic victims globally. Appropriately responding to these disparities in available evidence and prevention efforts is necessary if we are to comprehensively address this global-health dilemma.
Satellite applications to electric-utility communications needs. [land mobile satellite service
NASA Technical Reports Server (NTRS)
Horstein, M.; Barnett, R.
1981-01-01
Significant changes in the Nation's electric power systems are expected to result from the integration of new technology, possible during the next decade. Digital communications for monitor and control, exclusive of protective relaying, are expected to double or triple current traffic. A nationwide estimate of 13 Mb/s traffic is projected. Of this total, 8 Mb/s is attributed to the bulk-power system as it is now being operated (4 Mb/s). This traffic could be accommodated by current communications satellites using 3- to 4.5-m-diameter ground terminals costing $35,000 to $70,000 each. The remaining 5-Mb/s traffic is attributed to new technology concepts integrated into the distribution system. Such traffic is not compatible with current satellite technology because it requires small, low-cost ground terminals. Therefore, a high effective isotropic radiated power satellite, such as the one being planned by NASA for the Land Mobile Satellite Service, is required.
Road traffic noise abatement scenarios in Gothenburg 2015 - 2035.
Ögren, Mikael; Molnár, Peter; Barregard, Lars
2018-07-01
Exposure to high levels of road traffic noise at the most exposed building facade is increasing, both due to urbanization and due to overall traffic increase. This study investigated how different noise reduction measures would influence the noise exposure on a city-wide scale in Gothenburg, a city in Sweden with approximately 550,000 inhabitants. Noise exposure was estimated under several different scenarios for the period 2015-2035, using the standardized Nordic noise prediction method together with traffic flow measurements and population statistics. The scenarios were based on reducing speed limits, reducing traffic flows, introducing more electrically powered vehicles and introducing low-noise tires and pavements. The most effective measures were introducing low-noise tires or pavements, which in comparison to business as usual produced between 13% and 29% reduction in the number of inhabitants exposed above 55 dB equivalent level. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
On the Singularity in the Estimation of the Quaternion-of-Rotation
NASA Technical Reports Server (NTRS)
Bar-Itzhack, Itzhack Y.; Thienel, Julie K.
2003-01-01
It has been claimed in the archival literature that the covariance matrix of a Kalman filter, which is designed to estimate the quaternion-of-rotation, is necessarily rank deficient because the normality constraint of the quaternion produces dependence between the quaternion elements. In reality, though, this phenomenon does not occur. The covariance matrix is not singular, and the filter is well behaved. Several simple examples are presented that demonstrate the regularity of the covariance matrix. First, estimation cases are presented where a relationship exists between the estimated variables, and yet the covariance matrix is not singular. Then the particular problem of quaternion estimation is analyzed. It is shown that the discrepancy stems from the fact that a functional relationship exists between the elements of the true quaternion but not between its estimated elements.
The effects of congestions tax on air quality and health
NASA Astrophysics Data System (ADS)
Johansson, Christer; Burman, Lars; Forsberg, Bertil
The "Stockholm Trial" involved a road pricing system to improve the air quality and reduce traffic congestion. The test period of the trial was January 3-July 31, 2006. Vehicles travelling into and out of the charge cordon were charged for every passage during weekdays. The amount due varied during the day and was highest during rush hours (20 SEK = 2.2 EUR, maximum 60 SEK per day). Based on measured and modelled changes in road traffic it was estimated that this system resulted in a 15% reduction in total road use within the charged cordon. Total traffic emissions in this area of NO x and PM10 fell by 8.5% and 13%, respectively. Air quality dispersion modelling was applied to assess the effect of the emission reductions on ambient concentrations and population exposure. For the situations with and without the trial, meteorological conditions and other emissions than from road traffic were kept the same. The calculations show that, with a permanent congestion tax system like the Stockholm Trial, the annual average NO x concentrations would be lower by up to 12% along the most densely trafficked streets. PM10 concentrations would be up to 7% lower. The limit values for both PM10 and NO 2 would still be exceeded along the most densely trafficked streets. The total population exposure of NO x in Greater Stockholm (35 × 35 km with 1.44 million people) is estimated to decrease with a rather modest 0.23 μg m -3. However, based on a long-term epidemiological study, that found an increased mortality risk of 8% per 10 μg m -3 NO x, it is estimated that 27 premature deaths would be avoided every year. According to life-table analysis this would correspond to 206 years of life gained over 10 years per 100 000 people following the trial if the effects on exposures would persist. The effect on mortality is attributed to road traffic emissions (likely vehicle exhaust particles); NO x is merely regarded as an indicator of traffic exposure. This is only the tip of the ice-berg since reductions are expected in both respiratory and cardiovascular morbidity. This study demonstrates the importance of not only assessing the effects on air quality limit values, but also to make quantitative estimates of health impacts, in order to justify actions to reduce air pollution.
Annual update of data for estimating ESALs : draft.
DOT National Transportation Integrated Search
2008-10-01
A revised procedure for estimating equivalent single axleloads (ESALs) was developed in 1985. This procedure used weight, classification, and traffic volume data collected by the Transportation Cabinet's Division of Planning. : Annual updates of data...
Traffic volume estimation using network interpolation techniques.
DOT National Transportation Integrated Search
2013-12-01
Kriging method is a frequently used interpolation methodology in geography, which enables estimations of unknown values at : certain places with the considerations of distances among locations. When it is used in transportation field, network distanc...
Dynamic travel time estimation using regression trees.
DOT National Transportation Integrated Search
2008-10-01
This report presents a methodology for travel time estimation by using regression trees. The dissemination of travel time information has become crucial for effective traffic management, especially under congested road conditions. In the absence of c...
Holmes, John B; Dodds, Ken G; Lee, Michael A
2017-03-02
An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.
Bayesian hierarchical model for large-scale covariance matrix estimation.
Zhu, Dongxiao; Hero, Alfred O
2007-12-01
Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.
Outside and inside noise exposure in urban and suburban areas
Dwight E. Bishop; Myles A. Simpson
1977-01-01
In urban and suburban areas of the United States (away from major airports), the outdoor noise environment usually depends strongly on local vehicular traffic. By relating traffic flow to population density, a model of outdoor noise exposure has been developed for estimating the cumulative 24-hour noise exposure based upon the population density of the area. This noise...
Long-Term Tracking of a Specific Vehicle Using Airborne Optical Camera Systems
NASA Astrophysics Data System (ADS)
Kurz, F.; Rosenbaum, D.; Runge, H.; Cerra, D.; Mattyus, G.; Reinartz, P.
2016-06-01
In this paper we present two low cost, airborne sensor systems capable of long-term vehicle tracking. Based on the properties of the sensors, a method for automatic real-time, long-term tracking of individual vehicles is presented. This combines the detection and tracking of the vehicle in low frame rate image sequences and applies the lagged Cell Transmission Model (CTM) to handle longer tracking outages occurring in complex traffic situations, e.g. tunnels. The CTM model uses the traffic conditions in the proximities of the target vehicle and estimates its motion to predict the position where it reappears. The method is validated on an airborne image sequence acquired from a helicopter. Several reference vehicles are tracked within a range of 500m in a complex urban traffic situation. An artificial tracking outage of 240m is simulated, which is handled by the CTM. For this, all the vehicles in the close proximity are automatically detected and tracked to estimate the basic density-flow relations of the CTM model. Finally, the real and simulated trajectories of the reference vehicles in the outage are compared showing good correspondence also in congested traffic situations.
Gómez-Restrepo, Carlos; Naranjo-Lujan, Salomé; Rondón, Martín; Acosta, Andrés; Maldonado, Patricia; Arango Villegas, Carlos; Hurtado, Jaime; Hernández, Juan Carlos; Angarita, María Del Pilar; Peña, Marcela; Saavedra, Miguel Ángel; Quitian, Hoover
2017-06-01
In Colombia, some studies have estimated medical costs associated to traffic accidents. It is required to assess results by city or region and determine the influence of variables such as alcohol consumption. The main objective of this study was to identify health care costs associated to traffic accidents in Bogota and determine whether alcohol consumption can increase them. Cross-sectional costs study conducted in patients over 18 years treated in the emergency rooms of six different hospitals in Bogota, Colombia. The average total cost of medical care per patient was 628 USD, in Bogota-Colombia. The average cost per accident was estimated at 1,349 USD. On average, the total cost for health care for patients with positive blood alcohol level was 1.8 times higher than those who did not consume alcohol. The indirect costs were on average 115.3 USD per injured person. Numbers are expressed in 2011 U.S. dollars. Alcohol consumption increases the risk of traffic accidents and direct medical health costs. Copyright © 2016 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Klees, R.; Slobbe, D. C.; Farahani, H. H.
2018-03-01
The posed question arises for instance in regional gravity field modelling using weighted least-squares techniques if the gravity field functionals are synthesised from the spherical harmonic coefficients of a satellite-only global gravity model (GGM), and are used as one of the noisy datasets. The associated noise covariance matrix, appeared to be extremely ill-conditioned with a singular value spectrum that decayed gradually to zero without any noticeable gap. We analysed three methods to deal with the ill-conditioned noise covariance matrix: Tihonov regularisation of the noise covariance matrix in combination with the standard formula for the weighted least-squares estimator, a formula of the weighted least-squares estimator, which does not involve the inverse noise covariance matrix, and an estimator based on Rao's unified theory of least-squares. Our analysis was based on a numerical experiment involving a set of height anomalies synthesised from the GGM GOCO05s, which is provided with a full noise covariance matrix. We showed that the three estimators perform similar, provided that the two regularisation parameters each method knows were chosen properly. As standard regularisation parameter choice rules do not apply here, we suggested a new parameter choice rule, and demonstrated its performance. Using this rule, we found that the differences between the three least-squares estimates were within noise. For the standard formulation of the weighted least-squares estimator with regularised noise covariance matrix, this required an exceptionally strong regularisation, much larger than one expected from the condition number of the noise covariance matrix. The preferred method is the inversion-free formulation of the weighted least-squares estimator, because of its simplicity with respect to the choice of the two regularisation parameters.
Estimating the health benefits of planned public transit investments in Montreal.
Tétreault, Louis-François; Eluru, Naveen; Hatzopoulou, Marianne; Morency, Patrick; Plante, Celine; Morency, Catherine; Reynaud, Frederic; Shekarrizfard, Maryam; Shamsunnahar, Yasmin; Faghih Imani, Ahmadreza; Drouin, Louis; Pelletier, Anne; Goudreau, Sophie; Tessier, Francois; Gauvin, Lise; Smargiassi, Audrey
2018-01-01
Since public transit infrastructure affects road traffic volumes and influences transportation mode choice, which in turn impacts health, it is important to estimate the alteration of the health burden linked with transit policies. We quantified the variation in health benefits and burden between a business as usual (BAU) and a public transit (PT) scenarios in 2031 (with 8 and 19 new subway and train stations) for the greater Montreal region. Using mode choice and traffic assignment models, we predicted the transportation mode choice and traffic assignment on the road network. Subsequently, we estimated the distance travelled in each municipality by mode, the minutes spent in active transportation, as well as traffic emissions. Thereafter we estimated the health burden attributed to air pollution and road traumas and the gains associated with active transportation for both the BAU and PT scenarios. We predicted a slight decrease of overall trips and kilometers travelled by car as well as an increase of active transportation for the PT in 2031 vs the BAU. Our analysis shows that new infrastructure will reduce the overall burden of transportation by 2.5 DALYs per 100,000 persons. This decrease is caused by the reduction of road traumas occurring in the inner suburbs and central Montreal region as well as gains in active transportation in the inner suburbs. Based on the results of our study, transportation planned public transit projects for Montreal are unlikely to reduce drastically the burden of disease attributable to road vehicles and infrastructures in the Montreal region. The impact of the planned transportation infrastructures seems to be very low and localized mainly in the areas where new public transit stations are planned. Copyright © 2017 Elsevier Inc. All rights reserved.
Elemental carbon exposure at residence and survival after acute myocardial infarction.
von Klot, Stephanie; Gryparis, Alexandros; Tonne, Cathryn; Yanosky, Jeffrey; Coull, Brent A; Goldberg, Robert J; Lessard, Darleen; Melly, Steven J; Suh, Helen H; Schwartz, Joel
2009-07-01
Particulate air pollution has been consistently related to cardiovascular mortality. Some evidence suggests that particulate matter may accelerate the atherosclerotic process. Effects of within-city variations of particulate air pollution on survival after an acute cardiovascular event have been little explored. We conducted a cohort study of hospital survivors of acute myocardial infarction (MI) from the Worcester, MA, metropolitan area to investigate the long-term effects of within-city variation in traffic-related air pollution on mortality. The study builds on an ongoing community-wide investigation examining changes over time in MI incidence and case-fatality rates. We included confirmed cases of MI in 1995, 1997, 1999, 2001, and 2003. Long-term survival status was ascertained through 2005. A validated spatiotemporal land use regression model for traffic-related air pollution was developed and annual averages of elemental carbon at residence estimated. The effect of estimated elemental carbon on the long-term mortality of patients discharged after MI was analyzed using a Cox proportional hazards model, controlling for a variety of demographic, medical history, and clinical variables. Of the 3895 patients with validated MI, 44% died during follow-up. Exposure to estimated elemental carbon in the year of entry into the study was 0.44 microg/m on average. All-cause mortality increased by 15% (95% confidence interval = 0.03%-29%) per interquartile range increase in estimated yearly elemental carbon (0.24 microg/m) after the second year of survival. No association between traffic-related pollution and all-cause mortality was observed during the first 2 years of follow-up. Chronic traffic-related particulate air pollution is associated with increased mortality in hospital survivors of acute MI after the second year of survival.
Method for estimating power outages and restoration during natural and man-made events
Omitaomu, Olufemi A.; Fernandez, Steven J.
2016-01-05
A method of modeling electric supply and demand with a data processor in combination with a recordable medium, and for estimating spatial distribution of electric power outages and affected populations. A geographic area is divided into cells to form a matrix. Within the matrix, supply cells are identified as containing electric substations and demand cells are identified as including electricity customers. Demand cells of the matrix are associated with the supply cells as a function of the capacity of each of the supply cells and the proximity and/or electricity demand of each of the demand cells. The method includes estimating a power outage by applying disaster event prediction information to the matrix, and estimating power restoration using the supply and demand cell information of the matrix and standardized and historical restoration information.
Covariance Matrix Estimation for Massive MIMO
NASA Astrophysics Data System (ADS)
Upadhya, Karthik; Vorobyov, Sergiy A.
2018-04-01
We propose a novel pilot structure for covariance matrix estimation in massive multiple-input multiple-output (MIMO) systems in which each user transmits two pilot sequences, with the second pilot sequence multiplied by a random phase-shift. The covariance matrix of a particular user is obtained by computing the sample cross-correlation of the channel estimates obtained from the two pilot sequences. This approach relaxes the requirement that all the users transmit their uplink pilots over the same set of symbols. We derive expressions for the achievable rate and the mean-squared error of the covariance matrix estimate when the proposed method is used with staggered pilots. The performance of the proposed method is compared with existing methods through simulations.
Within-city contrasts in PM composition and sources and their relationship with nitrogen oxides.
Minguillón, M C; Rivas, I; Aguilera, I; Alastuey, A; Moreno, T; Amato, F; Sunyer, J; Querol, X
2012-10-26
The present work is part of the INMA (INfancia y Medio Ambiente -'Environment and Childhood') project, which aims at assessing the adverse effects of exposure to air pollution during pregnancy and early in life. The present study was performed in the city of Sabadell (Northeast Spain) at three sampling sites covering different traffic characteristics, during two times of the year. It assesses time and spatial variations of PM(2.5) concentrations, chemical components and source contributions, as well as gaseous pollutants. Furthermore, a cross-correlation analysis of PM components and source contributions with gaseous pollutants used as a proxy for exposure assessment is carried out. Our data show the influence of traffic emissions in the Sabadell area. The main PM sources identified by Positive Matrix Factorisation (PMF) were similar between the two seasons: mineral source (traffic-induced resuspension, demolition/construction and natural background), secondary sulphate (higher in summer), secondary nitrate (only during winter), industrial, and road traffic, which was the main contributor to PM(2.5) at two of the sites. The correlation of concentrations of nitrogen oxides was especially strong with those of elemental carbon (EC). The relatively weaker correlations with organic carbon (OC) in summer are attributed to the variable formation of secondary OC. Strong correlations between concentration of nitrogen oxides and PM(2.5) road traffic contributions obtained from source apportionment analysis were seen at all sites. Therefore, under the studied urban environment, nitrogen oxides can be used as a proxy for the exposure to road traffic contribution to PM(2.5); the use of NO(x) concentrations being preferred, with NO and NO(2) as second and third options, respectively.
Imputing missing data via sparse reconstruction techniques.
DOT National Transportation Integrated Search
2017-06-01
The State of Texas does not currently have an automated approach for estimating volumes for links without counts. This research project proposes the development of an automated system to efficiently estimate the traffic volumes on uncounted links, in...
NASA Technical Reports Server (NTRS)
Engelland, Shawn A.; Capps, Alan
2011-01-01
Current aircraft departure release times are based on manual estimates of aircraft takeoff times. Uncertainty in takeoff time estimates may result in missed opportunities to merge into constrained en route streams and lead to lost throughput. However, technology exists to improve takeoff time estimates by using the aircraft surface trajectory predictions that enable air traffic control tower (ATCT) decision support tools. NASA s Precision Departure Release Capability (PDRC) is designed to use automated surface trajectory-based takeoff time estimates to improve en route tactical departure scheduling. This is accomplished by integrating an ATCT decision support tool with an en route tactical departure scheduling decision support tool. The PDRC concept and prototype software have been developed, and an initial test was completed at air traffic control facilities in Dallas/Fort Worth. This paper describes the PDRC operational concept, system design, and initial observations.
Satellite switched FDMA advanced communication technology satellite program
NASA Technical Reports Server (NTRS)
Atwood, S.; Higton, G. H.; Wood, K.; Kline, A.; Furiga, A.; Rausch, M.; Jan, Y.
1982-01-01
The satellite switched frequency division multiple access system provided a detailed system architecture that supports a point to point communication system for long haul voice, video and data traffic between small Earth terminals at Ka band frequencies at 30/20 GHz. A detailed system design is presented for the space segment, small terminal/trunking segment at network control segment for domestic traffic model A or B, each totaling 3.8 Gb/s of small terminal traffic and 6.2 Gb/s trunk traffic. The small terminal traffic (3.8 Gb/s) is emphasized, for the satellite router portion of the system design, which is a composite of thousands of Earth stations with digital traffic ranging from a single 32 Kb/s CVSD voice channel to thousands of channels containing voice, video and data with a data rate as high as 33 Mb/s. The system design concept presented, effectively optimizes a unique frequency and channelization plan for both traffic models A and B with minimum reorganization of the satellite payload transponder subsystem hardware design. The unique zoning concept allows multiple beam antennas while maximizing multiple carrier frequency reuse. Detailed hardware design estimates for an FDMA router (part of the satellite transponder subsystem) indicate a weight and dc power budget of 353 lbs, 195 watts for traffic model A and 498 lbs, 244 watts for traffic model B.
Is Traffic Still an Important Emitter of Monoaromatic Organic Compounds in European Urban Areas?
Borbon, Agnès; Boynard, Anne; Salameh, Thérèse; Baudic, Alexia; Gros, Valérie; Gauduin, Julie; Perrussel, Olivier; Pallares, Cyril
2018-01-16
Trends of long-term observations and emission inventories suggest that traffic emissions will no longer dominate the concentrations of monoaromatic compounds (i.e., TEX - toluene, xylenes, and ethylbenzene) in European urban areas. But the split limit between traffic and other emission sector contributions such as solvent use remains tenuous. Here long-term observations of an extensive set of hydrocarbons, including TEX, at traffic and urban background sites in London, Paris and Strasbourg were combined to estimate the relative importance of traffic emissions on TEX in every city. When analyzing the urban enhancement emission ratios of TEX-to-benzene on a seasonal basis, two potential source signatures other than traffic could be differentiated in all cities (1) summertime evaporation from fuel and/or solvent and (2) wintertime domestic heating. However, traffic emissions still unambiguously dominate the concentration levels of TEX in every city despite the reduction of their emissions at exhaust pipe over the last two decades. Traffic explains between 60% and 96% (at ±20%) of TEX levels while it is less clear for xylenes at some locations. Our results provide a basis to evaluate regional emission inventories. The method is applicable at any urban area where speciated hydrocarbon monitoring is available.
Rockett, Ian R H; Jiang, Shuhan; Yang, Qian; Yang, Tingzhong; Yang, Xiaozhao Y; Peng, Sihui; Yu, Lingwei
2017-08-18
This study estimated the prevalence of road traffic injury among Chinese urban residents and examined individual and regional-level correlates. A cross-sectional multistage process was used to sample residents from 21 selected cities in China. Survey respondents reported their history of road traffic injury in the past 12 months through a community survey. Multilevel, multivariable logistic regression analysis was used to identify injury correlates. Based on a retrospective 12-month reporting window, road traffic injury prevalence among urban residents was 13.2%. Prevalence of road traffic injury, by type, was 8.7, 8.7, 8.5, and 7.7% in the automobile, bicycle, motorcycle, and pedestrian categories, respectively. Multilevel analysis showed that prevalence of road traffic injury was positively associated with minority status, income, and mental health disorder score at the individual level. Regionally, road traffic injury was associated with geographic location of residence and prevalence of mental health disorders. Both individual and regional-level variables were associated with road traffic injury among Chinese urban residents, a finding whose implications transcend wholesale imported generic solutions. This descriptive research demonstrates an urgent need for longitudinal studies across China on risk and protective factors, in order to inform injury etiology, surveillance, prevention, treatment, and evaluation.
Stable Estimation of a Covariance Matrix Guided by Nuclear Norm Penalties
Chi, Eric C.; Lange, Kenneth
2014-01-01
Estimation of a covariance matrix or its inverse plays a central role in many statistical methods. For these methods to work reliably, estimated matrices must not only be invertible but also well-conditioned. The current paper introduces a novel prior to ensure a well-conditioned maximum a posteriori (MAP) covariance estimate. The prior shrinks the sample covariance estimator towards a stable target and leads to a MAP estimator that is consistent and asymptotically efficient. Thus, the MAP estimator gracefully transitions towards the sample covariance matrix as the number of samples grows relative to the number of covariates. The utility of the MAP estimator is demonstrated in two standard applications – discriminant analysis and EM clustering – in this sampling regime. PMID:25143662
NASA Astrophysics Data System (ADS)
Paz, Shlomit; Goldstein, Pavel; Kordova-Biezuner, Levana; Adler, Lea
2017-04-01
Exposure to benzene has been associated with multiple severe impacts on health. This notwithstanding, at most monitoring stations, benzene is not monitored on a regular basis. The aims of the study were to compare benzene rates in different urban environments (region with heavy traffic and industrial region), to analyse the relationship between benzene and meteorological parameters in a Mediterranean climate type, to estimate the linkages between benzene and NOx and to suggest a prediction model for benzene rates based on NOx levels in order contribute to a better estimation of benzene. Data were used from two different monitoring stations, located on the eastern Mediterranean coast: 1) a traffic monitoring station in Tel Aviv, Israel (TLV) located in an urban region with heavy traffic; 2) a general air quality monitoring station in Haifa Bay (HIB), located in Israel's main industrial region. At each station, hourly, daily, monthly, seasonal, and annual data of benzene, NOx, mean temperature, relative humidity, inversion level, and temperature gradient were analysed over three years: 2008, 2009, and 2010. A prediction model for benzene rates based on NOx levels (which are monitored regularly) was developed to contribute to a better estimation of benzene. The severity of benzene pollution was found to be considerably higher at the traffic monitoring station (TLV) than at the general air quality station (HIB), despite the location of the latter in an industrial area. Hourly, daily, monthly, seasonal, and annual patterns have been shown to coincide with anthropogenic activities (traffic), the day of the week, and atmospheric conditions. A strong correlation between NOx and benzene allowed the development of a prediction model for benzene rates, based on NOx, the day of the week, and the month. The model succeeded in predicting the benzene values throughout the year (except for September). The severity of benzene pollution was found to be considerably higher at the traffic station (TLV) than at the general air quality station (HIB), despite being located in an industrial area. Hourly, daily, seasonal, and annual patterns of benzene rates have been shown to coincide with anthropogenic activities (traffic), day of the week, and atmospheric conditions. A prediction model for benzene rates was developed, based on NOx, the day of the week, and the month. The model suggested in this study might be useful for identifying potential risk of benzene in other urban environments.
Anomalous dynamics of intruders in a crowded environment of mobile obstacles
Sentjabrskaja, Tatjana; Zaccarelli, Emanuela; De Michele, Cristiano; Sciortino, Francesco; Tartaglia, Piero; Voigtmann, Thomas; Egelhaaf, Stefan U.; Laurati, Marco
2016-01-01
Many natural and industrial processes rely on constrained transport, such as proteins moving through cells, particles confined in nanocomposite materials or gels, individuals in highly dense collectives and vehicular traffic conditions. These are examples of motion through crowded environments, in which the host matrix may retain some glass-like dynamics. Here we investigate constrained transport in a colloidal model system, in which dilute small spheres move in a slowly rearranging, glassy matrix of large spheres. Using confocal differential dynamic microscopy and simulations, here we discover a critical size asymmetry, at which anomalous collective transport of the small particles appears, manifested as a logarithmic decay of the density autocorrelation functions. We demonstrate that the matrix mobility is central for the observed anomalous behaviour. These results, crucially depending on size-induced dynamic asymmetry, are of relevance for a wide range of phenomena ranging from glassy systems to cell biology. PMID:27041068
Methodology for Generating Conflict Scenarios by Time Shifting Recorded Traffic Data
NASA Technical Reports Server (NTRS)
Paglione, Mike; Oaks, Robert; Bilimoria, Karl D.
2003-01-01
A methodology is presented for generating conflict scenarios that can be used as test cases to estimate the operational performance of a conflict probe. Recorded air traffic data is time shifted to create traffic scenarios featuring conflicts with characteristic properties similar to those encountered in typical air traffic operations. First, a reference set of conflicts is obtained from trajectories that are computed using birth points and nominal flight plans extracted from recorded traffic data. Distributions are obtained for several primary properties (e.g., encounter angle) that are most likely to affect the performance of a conflict probe. A genetic algorithm is then utilized to determine the values of time shifts for the recorded track data so that the primary properties of conflicts generated by the time shifted data match those of the reference set. This methodology is successfully demonstrated using recorded traffic data for the Memphis Air Route Traffic Control Center; a key result is that the required time shifts are less than 5 min for 99% of the tracks. It is also observed that close matching of the primary properties used in this study additionally provides a good match for some other secondary properties.
Caselli, Federico; Corradi, Antonio
2018-01-01
The relevance of effective and efficient solutions for vehicle traffic surveillance is widely recognized in order to enable advanced strategies for traffic management, e.g., based on dynamically adaptive and decentralized traffic light management. However, most related solutions in the literature, based on the powerful enabler of cooperative vehicular communications, assume the complete penetration rate of connectivity/communication technologies (and willingness to participate in the collaborative surveillance service) over the targeted vehicle population, thus making them not applicable nowadays. The paper originally proposes an innovative solution for cooperative traffic surveillance based on vehicular communications capable of: (i) working with low penetration rates of the proposed technology and (ii) of collecting a large set of monitoring data about vehicle mobility in targeted areas of interest. The paper presents insights and lessons learnt from the design and implementation work of the proposed solution. Moreover, it reports extensive performance evaluation results collected on realistic simulation scenarios based on the usage of iTETRIS with real traces of vehicular traffic of the city of Bologna. The reported results show the capability of our proposal to consistently estimate the real vehicular traffic even with low penetration rates of our solution (only 10%). PMID:29522427
Westgate, Philip M
2013-07-20
Generalized estimating equations (GEEs) are routinely used for the marginal analysis of correlated data. The efficiency of GEE depends on how closely the working covariance structure resembles the true structure, and therefore accurate modeling of the working correlation of the data is important. A popular approach is the use of an unstructured working correlation matrix, as it is not as restrictive as simpler structures such as exchangeable and AR-1 and thus can theoretically improve efficiency. However, because of the potential for having to estimate a large number of correlation parameters, variances of regression parameter estimates can be larger than theoretically expected when utilizing the unstructured working correlation matrix. Therefore, standard error estimates can be negatively biased. To account for this additional finite-sample variability, we derive a bias correction that can be applied to typical estimators of the covariance matrix of parameter estimates. Via simulation and in application to a longitudinal study, we show that our proposed correction improves standard error estimation and statistical inference. Copyright © 2012 John Wiley & Sons, Ltd.
A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain.
Barba, Lida; Rodríguez, Nibaldo
2017-01-01
Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT.
A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain
Rodríguez, Nibaldo
2017-01-01
Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT. PMID:28261267
NASA Astrophysics Data System (ADS)
Yokoi, Toshiyuki; Itoh, Michimasa; Oguri, Koji
Most of the traffic accidents have been caused by inappropriate driver's mental state. Therefore, driver monitoring is one of the most important challenges to prevent traffic accidents. Some studies for evaluating the driver's mental state while driving have been reported; however driver's mental state should be estimated in real-time in the future. This paper proposes a way to estimate quantitatively driver's mental workload using heart rate variability. It is assumed that the tolerance to driver's mental workload is different depending on the individual. Therefore, we classify people based on their individual tolerance to mental workload. Our estimation method is multiple linear regression analysis, and we compare it to NASA-TLX which is used as the evaluation method of subjective mental workload. As a result, the coefficient of correlation improved from 0.83 to 0.91, and the standard deviation of error also improved. Therefore, our proposed method demonstrated the possibility to estimate mental workload.
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.
Traffic model for the satellite component of UMTS
NASA Technical Reports Server (NTRS)
Hu, Y. F.; Sheriff, R. E.
1995-01-01
An algorithm for traffic volume estimation for satellite mobile communications systems has been developed. This algorithm makes use of worldwide databases for demographic and economic data. In order to provide for such an estimation, the effects of competing services have been considered so that likely market demand can be forecasted. Different user groups of the predicted market have been identified according to expectations in the quality of services and mobility requirement. The number of users for different user groups are calculated taking into account the gross potential market, the penetration rate of the identified services and the profitability to provide such services via satellite.
Life-Cycle Cost/Benefit Assessment of Expedite Departure Path (EDP)
NASA Technical Reports Server (NTRS)
Wang, Jianzhong Jay; Chang, Paul; Datta, Koushik
2005-01-01
This report presents a life-cycle cost/benefit assessment (LCCBA) of Expedite Departure Path (EDP), an air traffic control Decision Support Tool (DST) currently under development at NASA. This assessment is an update of a previous study performed by bd Systems, Inc. (bd) during FY01, with the following revisions: The life-cycle cost assessment methodology developed by bd for the previous study was refined and calibrated using Free Flight Phase 1 (FFP1) cost information for Traffic Management Advisor (TMA, or TMA-SC in the FAA's terminology). Adjustments were also made to the site selection and deployment scheduling methodology to include airspace complexity as a factor. This technique was also applied to the benefit extrapolation methodology to better estimate potential benefits for other years, and at other sites. This study employed a new benefit estimating methodology because bd s previous single year potential benefit assessment of EDP used unrealistic assumptions that resulted in optimistic estimates. This methodology uses an air traffic simulation approach to reasonably predict the impacts from the implementation of EDP. The results of the costs and benefits analyses were then integrated into a life-cycle cost/benefit assessment.
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.
Estimating the Contrail Impact on Climate Using the UK Met Office Model
NASA Astrophysics Data System (ADS)
Rap, A.; Forster, P. M.
2008-12-01
With air travel predicted to increase over the coming century, the emissions associated with air traffic are expected to have a significant warming effect on climate. According to current best estimates, an important contribution comes from contrails. However, as reported by the IPCC fourth assessment report, these current best estimates still have a high uncertainty. The development and validation of contrail parameterizations in global climate models is therefore very important. This current study develops a contrail parameterization within the UK Met Office Climate Model. Using this new parameterization, we estimate that for the 2002 traffic, the global mean annual contrail coverage is approximately 0.11%, a value which in good agreement with several other estimates. The corresponding contrail radiative forcing (RF) is calculated to be approximately 4 and 6 mWm-2 in all-sky and clear-sky conditions, respectively. These values lie within the lower end of the RF range reported by the latest IPCC assessment. The relatively high cloud masking effect on contrails observed by our parameterization compared with other studies is investigated, and a possible cause for this difference is suggested. The effect of the diurnal variations of air traffic on both contrail coverage and contrail RF is also investigated. The new parameterization is also employed in thirty-year slab-ocean model runs in order to give one of the first insights into contrail effects on daily temperature range and the climate impact of contrails.
NASA Astrophysics Data System (ADS)
Pan, X. G.; Wang, J. Q.; Zhou, H. Y.
2013-05-01
The variance component estimation (VCE) based on semi-parametric estimator with weighted matrix of data depth has been proposed, because the coupling system model error and gross error exist in the multi-source heterogeneous measurement data of space and ground combined TT&C (Telemetry, Tracking and Command) technology. The uncertain model error has been estimated with the semi-parametric estimator model, and the outlier has been restrained with the weighted matrix of data depth. On the basis of the restriction of the model error and outlier, the VCE can be improved and used to estimate weighted matrix for the observation data with uncertain model error or outlier. Simulation experiment has been carried out under the circumstance of space and ground combined TT&C. The results show that the new VCE based on the model error compensation can determine the rational weight of the multi-source heterogeneous data, and restrain the outlier data.
A Robust Statistics Approach to Minimum Variance Portfolio Optimization
NASA Astrophysics Data System (ADS)
Yang, Liusha; Couillet, Romain; McKay, Matthew R.
2015-12-01
We study the design of portfolios under a minimum risk criterion. The performance of the optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio asset returns. For large portfolios, the number of available market returns is often of similar order to the number of assets, so that the sample covariance matrix performs poorly as a covariance estimator. Additionally, financial market data often contain outliers which, if not correctly handled, may further corrupt the covariance estimation. We address these shortcomings by studying the performance of a hybrid covariance matrix estimator based on Tyler's robust M-estimator and on Ledoit-Wolf's shrinkage estimator while assuming samples with heavy-tailed distribution. Employing recent results from random matrix theory, we develop a consistent estimator of (a scaled version of) the realized portfolio risk, which is minimized by optimizing online the shrinkage intensity. Our portfolio optimization method is shown via simulations to outperform existing methods both for synthetic and real market data.
Smallwood, D. O.
1996-01-01
It is shown that the usual method for estimating the coherence functions (ordinary, partial, and multiple) for a general multiple-input! multiple-output problem can be expressed as a modified form of Cholesky decomposition of the cross-spectral density matrix of the input and output records. The results can be equivalently obtained using singular value decomposition (SVD) of the cross-spectral density matrix. Using SVD suggests a new form of fractional coherence. The formulation as a SVD problem also suggests a way to order the inputs when a natural physical order of the inputs is absent.
Fast Drawing of Traffic Sign Using Mobile Mapping System
NASA Astrophysics Data System (ADS)
Yao, Q.; Tan, B.; Huang, Y.
2016-06-01
Traffic sign provides road users with the specified instruction and information to enhance traffic safety. Automatic detection of traffic sign is important for navigation, autonomous driving, transportation asset management, etc. With the advance of laser and imaging sensors, Mobile Mapping System (MMS) becomes widely used in transportation agencies to map the transportation infrastructure. Although many algorithms of traffic sign detection are developed in the literature, they are still a tradeoff between the detection speed and accuracy, especially for the large-scale mobile mapping of both the rural and urban roads. This paper is motivated to efficiently survey traffic signs while mapping the road network and the roadside landscape. Inspired by the manual delineation of traffic sign, a drawing strategy is proposed to quickly approximate the boundary of traffic sign. Both the shape and color prior of the traffic sign are simultaneously involved during the drawing process. The most common speed-limit sign circle and the statistic color model of traffic sign are studied in this paper. Anchor points of traffic sign edge are located with the local maxima of color and gradient difference. Starting with the anchor points, contour of traffic sign is drawn smartly along the most significant direction of color and intensity consistency. The drawing process is also constrained by the curvature feature of the traffic sign circle. The drawing of linear growth is discarded immediately if it fails to form an arc over some steps. The Kalman filter principle is adopted to predict the temporal context of traffic sign. Based on the estimated point,we can predict and double check the traffic sign in consecutive frames.The event probability of having a traffic sign over the consecutive observations is compared with the null hypothesis of no perceptible traffic sign. The temporally salient traffic sign is then detected statistically and automatically as the rare event of having a traffic sign.The proposed algorithm is tested with a diverse set of images that are taken inWuhan, China with theMMS ofWuhan University. Experimental results demonstrate that the proposed algorithm can detect traffic signs at the rate of over 80% in around 10 milliseconds. It is promising for the large-scale traffic sign survey and change detection using the mobile mapping system.
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...
Estimates of alcohol involvement in fatal crashes : new alcohol methodology
DOT National Transportation Integrated Search
2002-01-01
The National Highway Traffic Safety Administration (NHTSA) has adopted a new method to : estimate missing blood alcohol concentration (BAC) test result data. This new method, multiple : imputation, will be used by NHTSAs National Center for Statis...
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
Gauvin, Lise; Plante, Céline; Fournier, Michel; Morency, Catherine
2012-01-01
Objectives. We examined the extent to which differential traffic volume and road geometry can explain social inequalities in pedestrian, cyclist, and motor vehicle occupant injuries across wealthy and poor urban areas. Methods. We performed a multilevel observational study of all road users injured over 5 years (n = 19 568) at intersections (n = 17 498) in a large urban area (Island of Montreal, Canada). We considered intersection-level (traffic estimates, major roads, number of legs) and area-level (population density, commuting travel modes, household income) characteristics in multilevel Poisson regressions that nested intersections in 506 census tracts. Results. There were significantly more injured pedestrians, cyclists, and motor vehicle occupants at intersections in the poorest than in the richest areas. Controlling for traffic volume, intersection geometry, and pedestrian and cyclist volumes greatly attenuated the event rate ratios between intersections in the poorest and richest areas for injured pedestrians (−70%), cyclists (−44%), and motor vehicle occupants (−44%). Conclusions. Roadway environment can explain a substantial portion of the excess rate of road traffic injuries in the poorest urban areas. PMID:22515869
A radical change in traffic law: effects on fatalities in the Czech Republic.
Montag, J
2014-12-01
This study examines short- and long-run effects of a new-stricter-road traffic law on traffic accident-related fatalities in the Czech Republic. The law introduced tougher punishments through the introduction of a demerit point system and a manifold increase in fines, together with augmented authority of traffic police. Identification is based on difference-in-differences methodology, with neighbouring countries serving as a control group. There was a sharp, 33.3%, decrease in accident-related fatalities during the first three post-reform months. This translates into 127 saved lives (95% confidence interval: 51, 204). The decline was, however, temporary; the estimates of the effects going beyond the first year are around zero. Unique data on traffic police activity reveal that police resources devoted to traffic law enforcement gradually declined. Tougher penalties have significant, but often short-lived effects. Weaker enforcement in the aftermath of such reforms may explain the absence of long-run effects. © The Author 2014. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
The October 1973 expendable launch vehicle traffic model, revision 2
NASA Technical Reports Server (NTRS)
1974-01-01
Traffic model data for current expendable launch vehicles (assuming no space shuttle) for calendar years 1980 through 1991 are presented along with some supporting and summary data. This model was based on a payload program equivalent in scientific return to the October 1973 NASA Payload Model, the NASA estimated non NASA/non DoD Payload Model, and the 1971 DoD Mission Model.
Prenatal air pollution exposure and ultrasound measures of fetal growth in Los Angeles, California.
Ritz, Beate; Qiu, Jiaheng; Lee, Pei-Chen; Lurmann, Fred; Penfold, Bryan; Erin Weiss, Robert; McConnell, Rob; Arora, Chander; Hobel, Calvin; Wilhelm, Michelle
2014-04-01
Few previous studies examined the impact of prenatal air pollution exposures on fetal development based on ultrasound measures during pregnancy. In a prospective birth cohort of more than 500 women followed during 1993-1996 in Los Angeles, California, we examined how air pollution impacts fetal growth during pregnancy. Exposure to traffic related air pollution was estimated using CALINE4 air dispersion modeling for nitrogen oxides (NOx) and a land use regression (LUR) model for nitrogen monoxide (NO), nitrogen dioxide (NO2) and NOx. Exposures to carbon monoxide (CO), NO2, ozone (O3) and particles <10μm in aerodynamic diameter (PM10) were estimated using government monitoring data. We employed a linear mixed effects model to estimate changes in fetal size at approximately 19, 29 and 37 weeks gestation based on ultrasound. Exposure to traffic-derived air pollution during 29 to 37 weeks was negatively associated with biparietal diameter at 37 weeks gestation. For each interquartile range (IQR) increase in LUR-based estimates of NO, NO2 and NOx, or freeway CALINE4 NOx we estimated a reduction in biparietal diameter of 0.2-0.3mm. For women residing within 5km of a monitoring station, we estimated biparietal diameter reductions of 0.9-1.0mm per IQR increase in CO and NO2. Effect estimates were robust to adjustment for a number of potential confounders. We did not observe consistent patterns for other growth endpoints we examined. Prenatal exposure to traffic-derived pollution was negatively associated with fetal head size measured as biparietal diameter in late pregnancy. Copyright © 2014 Elsevier Inc. All rights reserved.
Prenatal Air Pollution Exposure and Ultrasound Measures of Fetal Growth in Los Angeles, California
Ritz, Beate; Qiu, Jiaheng; Lee, Pei-Chen; Lurmann, Fred; Penfold, Bryan; Weiss, Robert Erin; McConnell, Rob; Arora, Chander; Hobel, Calvin; Wilhelm, Michelle
2014-01-01
Background Few previous studies examined the impact of prenatal air pollution exposures on fetal development based on ultrasound measures during pregnancy. Methods In a prospective birth cohort of more than 500 women followed during 1993-1996 in Los Angeles, California, we examined how air pollution impacts fetal growth during pregnancy. Exposure to traffic related air pollution was estimated using CALINE4 air dispersion modeling for nitrogen oxides (NOx) and a land use regression (LUR) model for nitrogen monoxide (NO), nitrogen dioxide (NO2) and NOx. Exposures to carbon monoxide (CO), NO2, ozone (O3) and particles <10 μm in aerodynamic diameter (PM10) were estimated using government monitoring data. We employed a linear mixed effects model to estimate changes in fetal size at approximately 19, 29 and 37 weeks gestation based on ultrasound. Results Exposure to traffic-derived air pollution during 29 to 37 weeks was negatively associated with biparietal diameter at 37 weeks gestation. For each interquartile range (IQR) increase in LUR-based estimates of NO, NO2 and NOx, or freeway CALINE4 NOx we estimated a reduction in biparietal diameter of 0.2-0.3 mm. For women residing within 5 km of a monitoring station, we estimated biparietal diameter reductions of 0.9-1.0 mm per IQR increase in CO and NO2. Effect estimates were robust to adjustment for a number of potential confounders. We did not observe consistent patterns for other growth endpoints we examined. Conclusions Prenatal exposure to traffic-derived pollution was negatively associated with fetal head size measured as biparietal diameter in late pregnancy. PMID:24517884
Hankey, Steve; Lindsey, Greg; Marshall, Julian D
2017-04-01
Providing infrastructure and land uses to encourage active travel (i.e., bicycling and walking) are promising strategies for designing health-promoting cities. Population-level exposure to air pollution during active travel is understudied. Our goals were a ) to investigate population-level patterns in exposure during active travel, based on spatial estimates of bicycle traffic, pedestrian traffic, and particulate concentrations; and b ) to assess how those exposure patterns are associated with the built environment. We employed facility-demand models (active travel) and land use regression models (particulate concentrations) to estimate block-level ( n = 13,604) exposure during rush-hour (1600-1800 hours) in Minneapolis, Minnesota. We used the model-derived estimates to identify land use patterns and characteristics of the street network that are health promoting. We also assessed how exposure is correlated with indicators of health disparities (e.g., household income, proportion of nonwhite residents). Our work uses population-level rates of active travel (i.e., traffic flows) rather than the probability of walking or biking (i.e., "walkability" or "bikeability") to assess exposure. Active travel often occurs on high-traffic streets or near activity centers where particulate concentrations are highest (i.e., 20-42% of active travel occurs on blocks with high population-level exposure). Only 2-3% of blocks (3-8% of total active travel) are "sweet spots" (i.e., high active travel, low particulate concentrations); sweet spots are located a ) near but slightly removed from the city-center or b ) on off-street trails. We identified 1,721 blocks (~ 20% of local roads) where shifting active travel from high-traffic roads to adjacent low-traffic roads would reduce exposure by ~ 15%. Active travel is correlated with population density, land use mix, open space, and retail area; particulate concentrations were mostly unchanged with land use. Public health officials and urban planners may use our findings to promote healthy transportation choices. When designing health-promoting cities, benefits (physical activity) as well as hazards (air pollution) should be evaluated.
Performance analysis of structured gradient algorithm. [for adaptive beamforming linear arrays
NASA Technical Reports Server (NTRS)
Godara, Lal C.
1990-01-01
The structured gradient algorithm uses a structured estimate of the array correlation matrix (ACM) to estimate the gradient required for the constrained least-mean-square (LMS) algorithm. This structure reflects the structure of the exact array correlation matrix for an equispaced linear array and is obtained by spatial averaging of the elements of the noisy correlation matrix. In its standard form the LMS algorithm does not exploit the structure of the array correlation matrix. The gradient is estimated by multiplying the array output with the receiver outputs. An analysis of the two algorithms is presented to show that the covariance of the gradient estimated by the structured method is less sensitive to the look direction signal than that estimated by the standard method. The effect of the number of elements on the signal sensitivity of the two algorithms is studied.
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata
Chen, Yangzhou; Guo, Yuqi; Wang, Ying
2017-01-01
In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.
Chen, Yangzhou; Guo, Yuqi; Wang, Ying
2017-03-29
In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.
Pedersen, Marie; Garne, Ester; Hansen-Nord, Nete; Hjortebjerg, Dorrit; Ketzel, Matthias; Raaschou-Nielsen, Ole; Nybo Andersen, Anne-Marie; Sørensen, Mette
2017-11-01
Ambient air pollution has been associated with certain congenital anomalies, but few studies rely on assessment of fine-scale variation in air quality and associations with noise from road traffic are unexplored. Among 84,218 liveborn singletons (1997-2002) from the Danish National Birth Cohort with complete covariate data and residential address history from conception until birth, we identified major congenital anomalies in 4018 children. Nitrogen dioxide (NO 2 ) and noise from road traffic (L den ) burden during fetal life was modeled. Outcome and covariate data were derived from registries, hospital records and questionnaires. Odds ratios (ORs) for eleven major anomaly groups associated with road traffic pollution during first trimester were estimated using logistic regression with generalized estimating equation (GEE) approach. Most of the associations tested did not suggest increased risks. A 10-µg/m 3 increase in NO 2 exposure during first trimester was associated with an adjusted ORs of 1.22 (95% confidence interval: 0.98-1.52) for ear, face and neck anomalies; 1.14 0.98-1.33) for urinary anomalies. A 10-dB increase in road traffic noise was also associated with these subgroups of anomalies as well as with an increased OR for orofacial cleft anomalies (1.17, 0.94-1.47). Inverse associations for several both air pollution and noise were observed for atrial septal defects (0.85, 0.68-1.04 and 0.81, 0.65-0.99, respectively). Residential road traffic exposure to noise or air pollution during pregnancy did not seem to pose a risk for development of congenital anomalies. Copyright © 2017 Elsevier Inc. All rights reserved.
Gorski Findling, Mary T; Werth, Paul M; Musicus, Aviva A; Bragg, Marie A; Graham, Dan J; Elbel, Brian; Roberto, Christina A
2018-01-01
In 2011, a National Academy of Medicine report recommended that packaged food in the U.S. display a uniform front-of-package nutrition label, using a system such as a 0-3 star ranking. Few studies have directly compared this to other labels to determine which best informs consumers and encourages healthier purchases. In 2013, we randomized adult participants (N=1247) in an Internet-based survey to one of six conditions: no label control; single traffic light; multiple traffic light; Facts Up Front; NuVal; or 0-3 star ranking. We compared groups on purchase intentions and accuracy of participants' interpretation of food labels. There were no differences in the nutritional quality of hypothetical shopping baskets across conditions (p=0.845). All labels improved consumers' abilities to judge the nutritional quality of foods relative to no label, but the best designs varied by outcomes. NuVal and multiple traffic light labels led to the greatest accuracy identifying the healthier of two products (p<0.001), while the multiple traffic light also led to the most accurate estimates of saturated fat, sugar, and sodium (p<0.001). The single traffic light outperformed other labels when participants compared nutrient levels between similar products (p<0.03). Single/multiple traffic light and Facts Up Front labels led to the most accurate calories per serving estimations (p<0.001). Although front-of-package labels helped participants more accurately assess products' nutrition information relative to no label, no conditions shifted adults' purchase intentions. Results did not point to a clearly superior label design, but they suggest that a 3-star label might not be best for educating consumers. Copyright © 2017 Elsevier Inc. All rights reserved.
Collective benefits in traffic during mega events via the use of information technologies
Xu, Yanyan; González, Marta C.
2017-01-01
Information technologies today can inform each of us about the route with the shortest time, but they do not contain incentives to manage travellers such that we all get collective benefits in travel times. To that end we need travel demand estimates and target strategies to reduce the traffic volume from the congested roads during peak hours in a feasible way. During large events, the traffic inconveniences in large cities are unusually high, yet temporary, and the entire population may be more willing to adopt collective recommendations for collective benefits in traffic. In this paper, we integrate, for the first time, big data resources to estimate the impact of events on traffic and propose target strategies for collective good at the urban scale. In the context of the Olympic Games in Rio de Janeiro, we first predict the expected increase in traffic. To that end, we integrate data from mobile phones, Airbnb, Waze and transit information, with game schedules and expected attendance in each venue. Next, we evaluate different route choice scenarios for drivers during the peak hours. Finally, we gather information on the trips that contribute the most to the global congestion which could be redirected from vehicles to transit. Interestingly, we show that (i) following new route alternatives during the event with individual shortest times can save more collective travel time than keeping the routine routes used before the event, uncovering the positive value of information technologies during events; (ii) with only a small proportion of people selected from specific areas switching from driving to public transport, the collective travel time can be reduced to a great extent. Results are presented online for evaluation by the public and policymakers (www.flows-rio2016.com (last accessed 3 September 2017)). PMID:28404868
Collective benefits in traffic during mega events via the use of information technologies.
Xu, Yanyan; González, Marta C
2017-04-01
Information technologies today can inform each of us about the route with the shortest time, but they do not contain incentives to manage travellers such that we all get collective benefits in travel times. To that end we need travel demand estimates and target strategies to reduce the traffic volume from the congested roads during peak hours in a feasible way. During large events, the traffic inconveniences in large cities are unusually high, yet temporary, and the entire population may be more willing to adopt collective recommendations for collective benefits in traffic. In this paper, we integrate, for the first time, big data resources to estimate the impact of events on traffic and propose target strategies for collective good at the urban scale. In the context of the Olympic Games in Rio de Janeiro, we first predict the expected increase in traffic. To that end, we integrate data from mobile phones, Airbnb, Waze and transit information, with game schedules and expected attendance in each venue. Next, we evaluate different route choice scenarios for drivers during the peak hours. Finally, we gather information on the trips that contribute the most to the global congestion which could be redirected from vehicles to transit. Interestingly, we show that (i) following new route alternatives during the event with individual shortest times can save more collective travel time than keeping the routine routes used before the event, uncovering the positive value of information technologies during events; (ii) with only a small proportion of people selected from specific areas switching from driving to public transport, the collective travel time can be reduced to a great extent. Results are presented online for evaluation by the public and policymakers (www.flows-rio2016.com (last accessed 3 September 2017)). © 2017 The Author(s).
A note on the upper bound of the spectral radius for SOR iteration matrix
NASA Astrophysics Data System (ADS)
Chang, D.-W. Da-Wei
2004-05-01
Recently, Wang and Huang (J. Comput. Appl. Math. 135 (2001) 325, Corollary 4.7) established the following estimation on the upper bound of the spectral radius for successive overrelaxation (SOR) iteration matrix:ρSOR≤1-ω+ωρGSunder the condition that the coefficient matrix A is a nonsingular M-matrix and ω≥1, where ρSOR and ρGS are the spectral radius of SOR iteration matrix and Gauss-Seidel iteration matrix, respectively. In this note, we would like to point out that the above estimation is not valid in general.
Empirical State Error Covariance Matrix for Batch Estimation
NASA Technical Reports Server (NTRS)
Frisbee, Joe
2015-01-01
State estimation techniques effectively provide mean state estimates. However, the theoretical state error covariance matrices provided as part of these techniques often suffer from a lack of confidence in their ability to describe the uncertainty in the estimated states. By a reinterpretation of the equations involved in the weighted batch least squares algorithm, it is possible to directly arrive at an empirical state error covariance matrix. The proposed empirical state error covariance matrix will contain the effect of all error sources, known or not. This empirical error covariance matrix may be calculated as a side computation for each unique batch solution. Results based on the proposed technique will be presented for a simple, two observer and measurement error only problem.
Myocardial Infarction Risk Due to Aircraft, Road, and Rail Traffic Noise.
Seidler, Andreas; Wagner, Mandy; Schubert, Melanie; Dröge, Patrik; Pons-Kühnemann, Jörn; Swart, Enno; Zeeb, Hajo; Hegewald, Janice
2016-06-17
Traffic noise can induce stress reactions that have effects on the cardiovascular system. The exposure-risk relationship between aircraft, road, and rail traffic noise and myocardial infarction is currently unknown. 19 632 patients from the Rhine-Main region of Germany who were diagnosed with myocardial infarction in the years 2006-2010 were compared with 834 734 control subjects. The assignment of persons to groups was performed on the basis of billing and prescription data from three statutory health insurance carriers. The exposure of all insurees to aircraft, road, and rail traffic noise in 2005 was determined from their residence addresses. As estimators of risk, odds ratios (OR) were calculated by logistic regression analysis, with adjustment for age, sex, regional social status variables, and individual social status (if available). The evaluation was performed on the basis of the continuous 24-hour noise level and the categorized noise level (in 5 decibel classes). The linear model revealed a statistically significant risk increase due to road noise (2.8% per 10 dB rise, 95% confidence interval [1.2; 4.5]) and railroad noise (2.3% per 10 dB rise [0.5; 4.2]), but not airplane noise. Airplane noise levels of 60 dB and above were associated with a higher risk of myocardial infarction (OR 1.42 [0.62; 3.25]). This higher risk is statistically significant if the analysis is restricted to patients who had died of myocardial infarction by 2014/2015 (OR 2.70 [1.08; 6.74]. In this subgroup, the risk estimators for all three types of traffic noise were of comparable magnitude (3.2% to 3.9% per 10 dB rise in noise level). In this study, a substantial proportion of the population was exposed to traffic noise levels that were associated with an albeit small increase in the risk of myocardial infarction. These findings underscore the importance of effective traffic noise prevention.
Antonucci, Arianna; Vitali, Matteo; Avino, Pasquale; Manigrasso, Maurizio; Protano, Carmela
2016-08-01
A HS-SPME method coupled with GC-MS analysis has been developed for simultaneously measuring the concentration of 10 volatile organic compounds (VOCs) (benzene, toluene, ethylbenzene, o-, m-, and p-xylene, methyl tert-butyl ether, ethyl tert-butyl ether, 2-methyl-2-butyl methyl ether, and diisopropyl ether) in urine matrix as a biomonitoring tool for populations at low levels of exposure to such VOCs. These compounds, potentially toxic for human health, are common contaminants of both outdoor and indoor air, as they are released by autovehicular traffic; some of them are also present in environmental tobacco smoke (ETS). Thus, the exposure to these pollutants cannot be neglected and should be assessed. The low limits of detection and quantification (LODs and LOQs <6.5 and 7.5 ng L(-1), respectively) and the high reproducibility (CVs <4 %) make the developed method suited for biomonitoring populations exposed at low levels such as children. Further, the method is cost-effective and low in time-consumption; therefore, it is useful for investigating large populations. It has been applied to children exposed to traffic pollution and/or ETS; the relevant results are reported, and the relevant implications are discussed.
The estimation error covariance matrix for the ideal state reconstructor with measurement noise
NASA Technical Reports Server (NTRS)
Polites, Michael E.
1988-01-01
A general expression is derived for the state estimation error covariance matrix for the Ideal State Reconstructor when the input measurements are corrupted by measurement noise. An example is presented which shows that the more measurements used in estimating the state at a given time, the better the estimator.
Spacecraft inertia estimation via constrained least squares
NASA Technical Reports Server (NTRS)
Keim, Jason A.; Acikmese, Behcet A.; Shields, Joel F.
2006-01-01
This paper presents a new formulation for spacecraft inertia estimation from test data. Specifically, the inertia estimation problem is formulated as a constrained least squares minimization problem with explicit bounds on the inertia matrix incorporated as LMIs [linear matrix inequalities). The resulting minimization problem is a semidefinite optimization that can be solved efficiently with guaranteed convergence to the global optimum by readily available algorithms. This method is applied to data collected from a robotic testbed consisting of a freely rotating body. The results show that the constrained least squares approach produces more accurate estimates of the inertia matrix than standard unconstrained least squares estimation methods.
DOT National Transportation Integrated Search
1981-10-01
Two statistical procedures have been developed to estimate hourly or daily aircraft counts. These counts can then be transformed into estimates of instantaneous air counts. The first procedure estimates the stable (deterministic) mean level of hourly...
Alcohol, psychoactive substances and non-fatal road traffic accidents - a case-control study
2012-01-01
Background The prevalence of alcohol and other psychoactive substances is high in biological specimens from injured drivers, while the prevalence of these psychoactive substances in samples from drivers in normal traffic is low. The aim of this study was to compare the prevalence of alcohol and psychoactive substances in drivers admitted to hospital for treatment of injuries after road traffic accidents with that in drivers in normal traffic, and calculate risk estimates for the substances, and combinations of substances found in both groups. Methods Injured drivers were recruited in the hospital emergency department and drivers in normal conditions were taken from the hospital catchment area in roadside tests of moving traffic. Substances found in blood samples from injured drivers and oral fluid samples from drivers in moving traffic were compared using equivalent cut off concentrations, and risk estimates were calculated using logistic regression analyses. Results In 21.9% of the injured drivers, substances were found: most commonly alcohol (11.5%) and stimulants eg. cocaine or amphetamines (9.4%). This compares to 3.2% of drivers in normal traffic where the most commonly found substances were z-hypnotics (0.9%) and benzodiazepines (0.8%). The greatest increase in risk of being injured was for alcohol combined with any other substance (OR: 231.9, 95% CI: 33.3- 1615.4, p < 0.001), for more than three psychoactive substances (OR: 38.9, 95% CI: 8.2- 185.0, p < 0.001) and for alcohol alone (OR: 36.1, 95% CI: 13.2- 98.6, p < 0.001). Single use of non-alcohol substances was not associated with increased accident risk. Conclusion The prevalence of psychoactive substances was higher among injured drivers than drivers in normal moving traffic. The risk of accident is greatly increased among drivers who tested positive for alcohol, in particular, those who had also ingested one or more psychoactive substances. Various preventive measures should be considered to curb the prevalence of driving under the influence of psychoactive substances as these drivers constitute a significant risk for other road users as well as themselves. PMID:22943663
Dollars for lives: the effect of highway capital investments on traffic fatalities.
Nguyen-Hoang, Phuong; Yeung, Ryan
2014-12-01
This study examines the effect of highway capital investments on highway fatalities. We used state-level data from the 48 contiguous states in the United States from 1968 through 2010 to estimate the effects on highway fatalities of capital expenditures and highway capital stock. We estimated these effects by controlling for a set of control variables together with state and year dummy variables and state-specific linear time trends. We found that capital expenditures and capital stock had significant and negative effects on highway fatalities. States faced with declines in gas tax revenues have already cut back drastically on spending on roads including on maintenance and capital outlay. If this trend continues, it may undermine traffic safety. While states and local governments are currently fiscally strained, it is important for them to continue investments in roadways to enhance traffic safety and, more significantly, to save lives. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.
Traffic Aware Strategic Aircrew Requests (TASAR)
NASA Technical Reports Server (NTRS)
Wing, David J.
2014-01-01
The Traffic Aware Strategic Aircrew Request (TASAR) concept offers onboard automation for the purpose of advising the pilot of traffic compatible trajectory changes that would be beneficial to the flight. A fast-time simulation study was conducted to assess the benefits of TASAR to Alaska Airlines. The simulation compares historical trajectories without TASAR to trajectories developed with TASAR and evaluated by controllers against their objectives. It was estimated that between 8,000 and 12,000 gallons of fuel and 900 to 1,300 minutes could be saved annually per aircraft. These savings were applied fleet-wide to produce an estimated annual cost savings to Alaska Airlines in excess of $5 million due to fuel, maintenance, and depreciation cost savings. Switching to a more wind-optimal trajectory was found to be the use case that generated the highest benefits out of the three TASAR use cases analyzed. Alaska TASAR requests peaked at four to eight requests per hour in high-altitude Seattle center sectors south of Seattle-Tacoma airport..
Lee, Jong-Tae; Son, Ji-Young; Cho, Yong-Sung
2007-08-01
The objective of this study is to see whether there were any health benefits of mitigated air pollution concentration due to reduced traffic flow during a citywide intervention for the 2002 Summer Asian Games. Relative risks of hospitalization for childhood asthma during the post-Asian Game period compared with the baseline period were estimated using a time-series analysis of the generalized additive Poisson model. Fourteen consecutive days of traffic volume control in Busan during the Games reduced all regulated air pollutant levels by 1-25%. The estimated relative risk of hospitalization during the post-Games period over the baseline period was 0.73 (95% confidence interval [CI] = 0.49, 1.11). We observed that this reduced air pollution was unique in 2002 when the traffic volume reduction program was applied during the Games period. This empirical data provides epidemiologic evidence of the health benefits resulting from environmental interventions to reduce ambient air pollution.
Truck movements in America : shipments from, to, within, and through states
DOT National Transportation Integrated Search
1997-05-01
This report presents new estimates of the movements of commodities by truck to, from, within, and through each state. These estimates show the magnitude of interstate commerce on the nation's highways, particularly on the traffic that travels through...
Airport Surface Traffic Control Concept Formulation Study : Volume 4. Estimation of Requirements
DOT National Transportation Integrated Search
1975-07-01
A detailed study of requirements was performed and is presented. This requirements effort provided an estimate of the performance requirements of a surveillance sensor that would be required in a TAGS (Tower Automated Ground Surveillance) system for ...
Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection*
Fan, Jianqing; Li, Yingying; Yu, Ke
2012-01-01
Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated in Fan et al. (2011). The required high-dimensional volatility matrix can be estimated by using high frequency financial data. This enables us to better adapt to the local volatilities and local correlations among vast number of assets and to increase significantly the sample size for estimating the volatility matrix. This paper studies the volatility matrix estimation using high-dimensional high-frequency data from the perspective of portfolio selection. Specifically, we propose the use of “pairwise-refresh time” and “all-refresh time” methods based on the concept of “refresh time” proposed by Barndorff-Nielsen et al. (2008) for estimation of vast covariance matrix and compare their merits in the portfolio selection. We establish the concentration inequalities of the estimates, which guarantee desirable properties of the estimated volatility matrix in vast asset allocation with gross exposure constraints. Extensive numerical studies are made via carefully designed simulations. Comparing with the methods based on low frequency daily data, our methods can capture the most recent trend of the time varying volatility and correlation, hence provide more accurate guidance for the portfolio allocation in the next time period. The advantage of using high-frequency data is significant in our simulation and empirical studies, which consist of 50 simulated assets and 30 constituent stocks of Dow Jones Industrial Average index. PMID:23264708
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2012-01-01
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented. PMID:24348088
Large Covariance Estimation by Thresholding Principal Orthogonal Complements.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2013-09-01
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented.
Improving stochastic estimates with inference methods: calculating matrix diagonals.
Selig, Marco; Oppermann, Niels; Ensslin, Torsten A
2012-02-01
Estimating the diagonal entries of a matrix, that is not directly accessible but only available as a linear operator in the form of a computer routine, is a common necessity in many computational applications, especially in image reconstruction and statistical inference. Here, methods of statistical inference are used to improve the accuracy or the computational costs of matrix probing methods to estimate matrix diagonals. In particular, the generalized Wiener filter methodology, as developed within information field theory, is shown to significantly improve estimates based on only a few sampling probes, in cases in which some form of continuity of the solution can be assumed. The strength, length scale, and precise functional form of the exploited autocorrelation function of the matrix diagonal is determined from the probes themselves. The developed algorithm is successfully applied to mock and real world problems. These performance tests show that, in situations where a matrix diagonal has to be calculated from only a small number of computationally expensive probes, a speedup by a factor of 2 to 10 is possible with the proposed method. © 2012 American Physical Society
Assimilating Eulerian and Lagrangian data in traffic-flow models
NASA Astrophysics Data System (ADS)
Xia, Chao; Cochrane, Courtney; DeGuire, Joseph; Fan, Gaoyang; Holmes, Emma; McGuirl, Melissa; Murphy, Patrick; Palmer, Jenna; Carter, Paul; Slivinski, Laura; Sandstede, Björn
2017-05-01
Data assimilation of traffic flow remains a challenging problem. One difficulty is that data come from different sources ranging from stationary sensors and camera data to GPS and cell phone data from moving cars. Sensors and cameras give information about traffic density, while GPS data provide information about the positions and velocities of individual cars. Previous methods for assimilating Lagrangian data collected from individual cars relied on specific properties of the underlying computational model or its reformulation in Lagrangian coordinates. These approaches make it hard to assimilate both Eulerian density and Lagrangian positional data simultaneously. In this paper, we propose an alternative approach that allows us to assimilate both Eulerian and Lagrangian data. We show that the proposed algorithm is accurate and works well in different traffic scenarios and regardless of whether ensemble Kalman or particle filters are used. We also show that the algorithm is capable of estimating parameters and assimilating real traffic observations and synthetic observations obtained from microscopic models.
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.
Incidence of real-world automotive parent and halogenated PAH in urban atmosphere.
Gao, Pan-Pan; Zhao, Yi-Bo; Ni, Hong-Gang
2018-06-01
This study reports results from a tunnel experiment impact of real-world traffic-related particle and gas parent and halogenated polycyclic aromatic hydrocarbons (PAHs and HPAHs) on urban air. The traffic related emission characteristics and subsequent environmental behavior of these compounds were investigated. To understand the significance of real-world transport emissions to the urban air, traffic-related mass emissions of PAHs and HPAHs were estimated based on measured emission factors. According to our results, PAHs and HPAHs emissions via particulate phase were greater than those via gaseous phase; particles in 2.1-3.3 μm size fraction, have the major contribution to particulate PAHs and HPAHs emissions. Over all, contribution of traffic-related emission of PAHs (only ∼3% of the total PAHs emission in China) is an overstated source of PAHs pollution in China. Actually, exhaust pipe emission contributed much less than the total traffic-related emission of pollutants. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Alaigba, D. B.; Soumah, M.; Banjo, M. O.
2017-05-01
The problem of urban mobility is complicated by traffic delay, resulting from poor planning, high population density and poor condition of roads within urban spaces. This study assessed traffic congestion resulting from differential contribution made by various land-uses along Apapa-Oworoshoki expressway in Lagos metropolis. The data for this study was from both primary and secondary sources; GPS point data was collected at selected points for traffic volume count; observation of the nature of vehicular traffic congestion, and land use types along the corridor. Existing data on traffic count along the corridor, connectivity map and land use map sourced from relevant authorities were acquired. Traffic congestion within the area was estimated using volume capacity ratio (V/C). Heterogeneity Index was developed and used to quantify the percentage contribution to traffic volume from various land-use categories. Analytical Hierarchical Processing (AHP) and knowledge-based weighting were used to rank the importance of different heterogeneity indices. Results showed significant relationship between the degree of heterogeneity of the land use pattern and road traffic congestion. Volume Capacity Ratio computed revealed that the route corridor exceeds its designed capacity in the southward direction between the hours of 8am and 12pm on working days. Five major nodes were analyzed along the corridor, and were all above the expected Passenger Car Unit (PCU), these are "Oshodi" 15 %, "Airport junction" 10 %, "Cele bus stop" 21 %, "Mile 2" 14 %, "Berger" 15 % and "Tincan bus stop" 33 % indicating heavy traffic congestion.
Non-urban mobile radio market demand forecast
NASA Technical Reports Server (NTRS)
Castruccio, P. A.; Cooper, J.
1982-01-01
A national nonmetropolitan land mobile traffic model for 1990-2000 addresses user classes, density classes, traffic mix statistics, distance distribution, geographic distribution, price elasticity, and service quality elasticity. Traffic demands for business, special industrial, and police were determined on the basis of surveys in 73 randomly selected nonurban counties. The selected services represent 69% of total demand. The results were extrapolated to all services in the non-SMSA areas of the contiguous United States. Radiotelephone services were considered separately. Total non-SMSA mobile radio demand (one way) estimates are given. General functional requirements include: hand portability, privacy, reduction of blind spots, two way data transmission, position location, slow scan imagery.
Extracellular matrix directions estimation of the heart on micro-focus x-ray CT volumes
NASA Astrophysics Data System (ADS)
Oda, Hirohisa; Oda, Masahiro; Kitasaka, Takayuki; Akita, Toshiaki; Mori, Kensaku
2017-03-01
In this paper we propose an estimation method of extracellular matrix directions of the heart. Myofiber are surrounded by the myocardial cell sheets whose directions have strong correspondence between heart failure. Estimation of the myocardial cell sheet directions is difficult since they are very thin. Therefore, we estimate the extracellular matrices which are touching to the sheets as if piled up. First, we perform a segmentation of the extracellular matrices by using the Hessian analysis. Each extracellular matrix region has sheet-like shape. We estimate the direction of each extracellular matrix region by the principal component analysis (PCA). In our experiments, mean inclination angles of two normal canine hearts were 50.6 and 46.2 degrees, while the angle of a failing canine heart was 57.4 degrees. This results well fit the anatomical knowledge that failing hearts tend to have vertical myocardical cell sheets.
Childhood incident asthma and traffic-related air pollution at home and school.
McConnell, Rob; Islam, Talat; Shankardass, Ketan; Jerrett, Michael; Lurmann, Fred; Gilliland, Frank; Gauderman, Jim; Avol, Ed; Künzli, Nino; Yao, Ling; Peters, John; Berhane, Kiros
2010-07-01
Traffic-related air pollution has been associated with adverse cardiorespiratory effects, including increased asthma prevalence. However, there has been little study of effects of traffic exposure at school on new-onset asthma. We evaluated the relationship of new-onset asthma with traffic-related pollution near homes and schools. Parent-reported physician diagnosis of new-onset asthma (n = 120) was identified during 3 years of follow-up of a cohort of 2,497 kindergarten and first-grade children who were asthma- and wheezing-free at study entry into the Southern California Children's Health Study. We assessed traffic-related pollution exposure based on a line source dispersion model of traffic volume, distance from home and school, and local meteorology. Regional ambient ozone, nitrogen dioxide (NO(2)), and particulate matter were measured continuously at one central site monitor in each of 13 study communities. Hazard ratios (HRs) for new-onset asthma were scaled to the range of ambient central site pollutants and to the residential interquartile range for each traffic exposure metric. Asthma risk increased with modeled traffic-related pollution exposure from roadways near homes [HR 1.51; 95% confidence interval (CI), 1.25-1.82] and near schools (HR 1.45; 95% CI, 1.06-1.98). Ambient NO(2) measured at a central site in each community was also associated with increased risk (HR 2.18; 95% CI, 1.18-4.01). In models with both NO(2) and modeled traffic exposures, there were independent associations of asthma with traffic-related pollution at school and home, whereas the estimate for NO(2) was attenuated (HR 1.37; 95% CI, 0.69-2.71). Traffic-related pollution exposure at school and homes may both contribute to the development of asthma.
Horton, Kyle G; Shriver, W Gregory; Buler, Jeffrey J
2016-01-01
Daily magnitudes and fluxes of landbird migration are often measured via nocturnal traffic rates aloft or diurnal densities within terrestrial habitats during stopover. However, these measures are not consistently correlated and at times reveal opposing trends. For this reason we sought to determine how comparison methods (daily magnitude or daily flux), nocturnal monitoring tools (weather surveillance radar, WSR; thermal imaging, TI), and temporal scale (preceding or following diurnal sampling) influenced correlation strength from stopover densities estimated by daily transect counts. We quantified nocturnal traffic rates at two temporal scales; averaged across the entire night and within individual decile periods of the night, and at two spatial scales; within 1 km of airspace surrounding the site via WSR and directly overhead within the narrow beam of a TI. Overall, the magnitude of daily bird density during stopover was positively related to the magnitude of broad-scale radar traffic rates of migrants on preceding and following nights during both the spring and fall. These relationships were strongest on the following night, and particularly from measures early in the night. Only during the spring on the following nights did we find positive correlations between the daily flux of transect counts and migration traffic rates (both WSR and TI). This indicates that our site likely had a more consistent daily turnover of migrants compared to the fall. The lack of general correlations between seasonal trends or daily flux in fine-scale TI traffic rates and stopover densities across or within nights was unexpected and likely due to poor sampling of traffic rates due to the camera's narrow beam. The order (preceding or following day) and metric of comparisons (magnitude or flux), as well as the tool (WSR or TI) used for monitoring nocturnal migration traffic can have dramatic impacts when compared with ground-based estimates of migrant density. WSR provided measures of the magnitude and daily flux in nocturnal migration traffic rates that related to daily stopover counts of migrants during spring and fall. Relationships among migrating bird flux measures are more complex than simple measures of magnitude of migration. Care should be given to address these complexities when comparing data among methods.
Real-time state estimation in a flight simulator using fNIRS.
Gateau, Thibault; Durantin, Gautier; Lancelot, Francois; Scannella, Sebastien; Dehais, Frederic
2015-01-01
Working memory is a key executive function for flying an aircraft. This function is particularly critical when pilots have to recall series of air traffic control instructions. However, working memory limitations may jeopardize flight safety. Since the functional near-infrared spectroscopy (fNIRS) method seems promising for assessing working memory load, our objective is to implement an on-line fNIRS-based inference system that integrates two complementary estimators. The first estimator is a real-time state estimation MACD-based algorithm dedicated to identifying the pilot's instantaneous mental state (not-on-task vs. on-task). It does not require a calibration process to perform its estimation. The second estimator is an on-line SVM-based classifier that is able to discriminate task difficulty (low working memory load vs. high working memory load). These two estimators were tested with 19 pilots who were placed in a realistic flight simulator and were asked to recall air traffic control instructions. We found that the estimated pilot's mental state matched significantly better than chance with the pilot's real state (62% global accuracy, 58% specificity, and 72% sensitivity). The second estimator, dedicated to assessing single trial working memory loads, led to 80% classification accuracy, 72% specificity, and 89% sensitivity. These two estimators establish reusable blocks for further fNIRS-based passive brain computer interface development.
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.
Davis, Kevin C; Patel, Deesha; Rodes, Robert; Beistle, Diane
2016-01-01
Background In 2012, the US Centers for Disease Control and Prevention (CDC) launched Tips From Former Smokers (Tips), the first federally funded national tobacco education campaign. In 2013, a follow-up Tips campaign aired on national cable television networks, radio, and other channels, with supporting digital advertising to drive traffic to the Tips campaign website. Objective The objective of this study was to use geographic and temporal variability in 2013 Tips campaign television media doses and ad tagging to evaluate changes in traffic to the campaign website in response to specific doses of campaign media. Methods Linear regression models were used to estimate the dose-response relationship between weekly market-level television gross rating points (GRPs) and weekly Web traffic to the Tips campaign website. This relationship was measured using unique visitors, total visits, and page views as outcomes. Ad GRP effects were estimated separately for ads tagged with the Tips campaign website URL and 1-800-QUIT-NOW. Results In the average media market, an increase of 100 television GRPs per week for ads tagged with the Tips campaign website URL was associated with an increase of 650 unique visitors (P<.001), 769 total visits (P<.001), and 1255 total page views (P<.001) per week. The associations between GRPs for ads tagged with 1-800-QUIT-NOW and each Web traffic measure were also statistically significant (P<.001), but smaller in magnitude. Conclusions Based on these findings, we estimate that the 16-week 2013 Tips television campaign generated approximately 660,000 unique visitors, 900,000 total visits, and 1,390,000 page views for the Tips campaign website. These findings can help campaign planners forecast the likely impact of targeted advertising efforts on consumers’ use of campaign-specific websites. PMID:26887959
Fleisch, Abby F.; Rifas-Shiman, Sheryl L.; Koutrakis, Petros; Schwartz, Joel D.; Kloog, Itai; Melly, Steven; Coull, Brent A.; Zanobetti, Antonella; Gillman, Matthew W.; Gold, Diane R.; Oken, Emily
2014-01-01
Background Prenatal air pollution exposure inhibits fetal growth, but implications for postnatal growth are unknown. Methods We assessed weights and lengths of US infants in the Project Viva cohort at birth and 6 months. We estimated third-trimester residential air pollution exposures using spatiotemporal models. We estimated neighborhood traffic density and roadway proximity at birth address using geographic information systems. We performed linear and logistic regression adjusted for sociodemographic variables, fetal growth, and gestational age at birth. Results Mean birth weight-for-gestational age z-score (fetal growth) was 0.17 (SD = 0.97; n=2,114), 0-6 month weight-for-length gain was 0.23 z-units (SD = 1.11; n=689), and 17% had weight-for-length ≥95th percentile at 6 months of age. Infants exposed to the highest (vs. lowest) quartile of neighborhood traffic density had lower fetal growth (−0.13 units [95% confidence interval (CI) = −0.25 to −0.01]), more rapid 0-6 month weight-for-length gain (0.25 units [95% CI = 0.01 to 0.49]), and higher odds of weight-for-length ≥95th percentile at 6 months (1.84 [95% CI = 1.11 to 3.05]). Neighborhood traffic density was additionally associated with an infant being in both the lowest quartile of fetal growth and highest quartile of 0-6 month weight-for-length gain (Q4 vs. Q1, OR = 3.01 [95% CI = 1.08 to 8.44]). Roadway proximity and third-trimester black carbon exposure were similarly associated with growth outcomes. For third-trimester PM2.5, effect estimates were in the same direction, but smaller and imprecise. Conclusions Infants exposed to higher traffic-related pollution in early life may exhibit more rapid postnatal weight gain in addition to reduced fetal growth. PMID:25437317
Estimation of red-light running frequency using high-resolution traffic and signal data.
Chen, Peng; Yu, Guizhen; Wu, Xinkai; Ren, Yilong; Li, Yueguang
2017-05-01
Red-light-running (RLR) emerges as a major cause that may lead to intersection-related crashes and endanger intersection safety. To reduce RLR violations, it's critical to identify the influential factors associated with RLR and estimate RLR frequency. Without resorting to video camera recordings, this study investigates this important issue by utilizing high-resolution traffic and signal event data collected from loop detectors at five intersections on Trunk Highway 55, Minneapolis, MN. First, a simple method is proposed to identify RLR by fully utilizing the information obtained from stop bar detectors, downstream entrance detectors and advance detectors. Using 12 months of event data, a total of 6550 RLR cases were identified. According to a definition of RLR frequency as the conditional probability of RLR on a certain traffic or signal condition (veh/1000veh), the relationships between RLR frequency and some influential factors including arriving time at advance detector, approaching speed, headway, gap to the preceding vehicle on adjacent lane, cycle length, geometric characteristics and even snowing weather were empirically investigated. Statistical analysis shows good agreement with the traffic engineering practice, e.g., RLR is most likely to occur on weekdays during peak periods under large traffic demands and longer signal cycles, and a total of 95.24% RLR events occurred within the first 1.5s after the onset of red phase. The findings confirmed that vehicles tend to run the red light when they are close to intersection during phase transition, and the vehicles following the leading vehicle with short headways also likely run the red light. Last, a simplified nonlinear regression model is proposed to estimate RLR frequency based on the data from advance detector. The study is expected to helpbetter understand RLR occurrence and further contribute to the future improvement of intersection safety. Copyright © 2017 Elsevier Ltd. All rights reserved.
Fleisch, Abby F; Rifas-Shiman, Sheryl L; Koutrakis, Petros; Schwartz, Joel D; Kloog, Itai; Melly, Steven; Coull, Brent A; Zanobetti, Antonella; Gillman, Matthew W; Gold, Diane R; Oken, Emily
2015-01-01
Prenatal air pollution exposure inhibits fetal growth, but implications for postnatal growth are unknown. We assessed weights and lengths of US infants in the Project Viva cohort at birth and 6 months. We estimated 3rd-trimester residential air pollution exposures using spatiotemporal models. We estimated neighborhood traffic density and roadway proximity at birth address using geographic information systems. We performed linear and logistic regression adjusted for sociodemographic variables, fetal growth, and gestational age at birth. Mean birth weight-for-gestational age z-score (fetal growth) was 0.17 (standard deviation [SD] = 0.97; n = 2,114), 0- to 6-month weight-for-length gain was 0.23 z-units (SD = 1.11; n = 689), and 17% had weight-for-length ≥95th percentile at 6 months of age. Infants exposed to the highest (vs. lowest) quartile of neighborhood traffic density had lower fetal growth (-0.13 units [95% confidence interval (CI) = -0.25 to -0.01]), more rapid 0- to 6-month weight-for-length gain (0.25 units [95% CI = 0.01 to 0.49]), and higher odds of weight-for-length ≥95th percentile at 6 months (1.84 [95% CI = 1.11 to 3.05]). Neighborhood traffic density was additionally associated with an infant being in both the lowest quartile of fetal growth and the highest quartile of 0- to 6-month weight-for-length gain (Q4 vs. Q1, odds ratio = 3.01 [95% CI = 1.08 to 8.44]). Roadway proximity and 3rd-trimester black carbon exposure were similarly associated with growth outcomes. For 3rd-trimester particulate matter (PM2.5), effect estimates were in the same direction, but smaller and imprecise. Infants exposed to higher traffic-related pollution in early life may exhibit more rapid postnatal weight gain in addition to reduced fetal growth.
Irregular Forces in Counterinsurgency Operations: Their Roles and Considerations
2010-05-10
highways channelized traffic between the larger population centers. Iraq’s oil reserves, conservatively estimated at 350 billion barrels , were the...laws, the easy availability of weapons made this matter hard to enforce. CF provided concrete barriers and other material to reinforce traffic control...sniper rifles, and handguns . To reduce GOI concerns of SOI rebellion, CF required all SOIs to obey Iraqi laws to include curfews when not on duty