An explanatory analysis of driver injury severity in rear-end crashes using a decision table/Naïve Bayes (DTNB) hybrid classifier.

PubMed

Chen, Cong; Zhang, Guohui; Yang, Jinfu; Milton, John C; Alcántara, Adélamar Dely

2016-05-01

Rear-end crashes are a major type of traffic crashes in the U.S. Of practical necessity is a comprehensive examination of its mechanism that results in injuries and fatalities. Decision table (DT) and Naïve Bayes (NB) methods have both been used widely but separately for solving classification problems in multiple areas except for traffic safety research. Based on a two-year rear-end crash dataset, this paper applies a decision table/Naïve Bayes (DTNB) hybrid classifier to select the deterministic attributes and predict driver injury outcomes in rear-end crashes. The test results show that the hybrid classifier performs reasonably well, which was indicated by several performance evaluation measurements, such as accuracy, F-measure, ROC, and AUC. Fifteen significant attributes were found to be significant in predicting driver injury severities, including weather, lighting conditions, road geometry characteristics, driver behavior information, etc. The extracted decision rules demonstrate that heavy vehicle involvement, a comfortable traffic environment, inferior lighting conditions, two-lane rural roadways, vehicle disabled damage, and two-vehicle crashes would increase the likelihood of drivers sustaining fatal injuries. The research limitations on data size, data structure, and result presentation are also summarized. The applied methodology and estimation results provide insights for developing effective countermeasures to alleviate rear-end crash injury severities and improve traffic system safety performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adaptive video-based vehicle classification technique for monitoring traffic.

DOT National Transportation Integrated Search

2015-08-01

This report presents a methodology for extracting two vehicle features, vehicle length and number of axles in order : to classify the vehicles from video, based on Federal Highway Administration (FHWA)s recommended vehicle : classification scheme....

Fault classification method for the driving safety of electrified vehicles

NASA Astrophysics Data System (ADS)

Wanner, Daniel; Drugge, Lars; Stensson Trigell, Annika

2014-05-01

A fault classification method is proposed which has been applied to an electric vehicle. Potential faults in the different subsystems that can affect the vehicle directional stability were collected in a failure mode and effect analysis. Similar driveline faults were grouped together if they resembled each other with respect to their influence on the vehicle dynamic behaviour. The faults were physically modelled in a simulation environment before they were induced in a detailed vehicle model under normal driving conditions. A special focus was placed on faults in the driveline of electric vehicles employing in-wheel motors of the permanent magnet type. Several failures caused by mechanical and other faults were analysed as well. The fault classification method consists of a controllability ranking developed according to the functional safety standard ISO 26262. The controllability of a fault was determined with three parameters covering the influence of the longitudinal, lateral and yaw motion of the vehicle. The simulation results were analysed and the faults were classified according to their controllability using the proposed method. It was shown that the controllability decreased specifically with increasing lateral acceleration and increasing speed. The results for the electric driveline faults show that this trend cannot be generalised for all the faults, as the controllability deteriorated for some faults during manoeuvres with low lateral acceleration and low speed. The proposed method is generic and can be applied to various other types of road vehicles and faults.

Homogenization of Vehicle Fleet Frontal Crash Pulses from 2000–2010

PubMed Central

Locey, Caitlin M.; Garcia-Espana, J. Felipe; Toh, Akira; Belwadi, Aditya; Arbogast, Kristy B.; Maltese, Matthew R.

2012-01-01

Full-scale vehicle crash tests are performed globally to assess vehicle structure and restraint system performance. The crash pulse, captured by accelerometers mounted within the occupant compartment, measures the motion of the vehicle during the impact event. From an occupant’s perspective, the crash pulse is the inertial event to which the vehicle’s restraint systems must respond in order to mitigate the forces and accelerations that act on a passenger, and thus reduce injury risk. The objective of this study was to quantify the characteristics of crash pulses for different vehicle types in the contemporary North American fleet, and delineate current trends in crash pulse evolution. NHTSA and Transport Canada crash test databases were queried for full-frontal rigid barrier crash tests of passenger vehicles model year 2000–2010 with impact angle equaling zero degrees. Acceleration-time histories were analyzed for all accelerometers attached to the vehicle structure within the occupant compartment. Custom software calculated the following crash pulse characteristics (CPCs): peak deceleration, time of peak deceleration, onset rate, pulse duration, and change in velocity. Vehicle body types were classified by adapting the Highway Loss Data Institute (HLDI) methodology, and vehicles were assigned a generation start year in place of model year in order to more accurately represent structural change over time. 1094 vehicle crash tests with 2795 individual occupant compartment-mounted accelerometers were analyzed. We found greater peak decelerations and and shorter pulse durations across multiple vehicle types in newer model years as compared to older. For midsize passenger cars, large passenger cars, and large SUVs in 56 km/h rigid barrier tests, maximum deceleration increased by 0.40, 0.96, and 1.57 g/year respectively, and pulse duration decreased by 0.74, 1.87, and 2.51 ms/year. We also found that the crash pulse characteristics are becoming more homogeneous in the modern vehicle fleet; the range of peak deceleration values for all vehicle classes decreased from 17.1 g in 1997–1999 generation start years to 10.7 g in 2009–2010 generation years, and the pulse duration range decreased from 39.5 ms to 13.4 ms for the same generation year groupings. This latter finding suggests that the designs of restraint systems may become more universally applicable across vehicle body types, since the occupant compartment accelerations are not as divergent for newer vehicles. PMID:23169139

Intelligent Sensing and Classification in DSR-Based Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Dempsey, Tae; Sahin, Gokhan; Morton, Yu T. (Jade

Wireless ad hoc networks have fundamentally altered today's battlefield, with applications ranging from unmanned air vehicles to randomly deployed sensor networks. Security and vulnerabilities in wireless ad hoc networks have been considered at different layers, and many attack strategies have been proposed, including denial of service (DoS) through the intelligent jamming of the most critical packet types of flows in a network. This paper investigates the effectiveness of intelligent jamming in wireless ad hoc networks using the Dynamic Source Routing (DSR) and TCP protocols and introduces an intelligent classifier to facilitate the jamming of such networks. Assuming encrypted packet headers and contents, our classifier is based solely on the observable characteristics of size, inter-arrival timing, and direction and classifies packets with up to 99.4% accuracy in our experiments.

Motor vehicle fuel analyzer

DOEpatents

Hoffheins, B.S.; Lauf, R.J.

1997-08-05

A gas detecting system is described for classifying the type of liquid fuel in a container or tank. The system includes a plurality of semiconductor gas sensors, each of which differs from the other in its response to various organic vapors. The system includes a means of processing the responses of the plurality of sensors such that the responses to any particular organic substance or mixture is sufficiently distinctive to constitute a recognizable ``signature``. The signature of known substances are collected and divided into two classes based on some other known characteristic of the substances. A pattern recognition system classifies the signature of an unknown substance with reference to the two user-defined classes, thereby classifying the unknown substance with regard to the characteristic of interest, such as its suitability for a particular use. 14 figs.

Motor vehicle fuel analyzer

DOEpatents

Hoffheins, Barbara S.; Lauf, Robert J.

1997-01-01

A gas detecting system for classifying the type of liquid fuel in a container or tank. The system includes a plurality of semiconductor gas sensors, each of which differs from the other in its response to various organic vapors. The system includes a means of processing the responses of the plurality of sensors such that the responses to any particular organic substance or mixture is sufficiently distinctive to constitute a recognizable "signature". The signature of known substances are collected and divided into two classes based on some other known characteristic of the substances. A pattern recognition system classifies the signature of an unknown substance with reference to the two user-defined classes, thereby classifying the unknown substance with regard to the characteristic of interest, such as its suitability for a particular use.

Preliminary analysis of the JAPE ground vehicle test data with an artificial neural network classifier

NASA Technical Reports Server (NTRS)

Larsen, Nathan F.; Carnes, Ben L.

1993-01-01

Remotely sensing and classifying military vehicles in a battlefield environment have been the source of much research over the past 20 years. The ability to know where threat vehicles are located is an obvious advantage to military personnel. In the past active methods of ground vehicle detection such as radar have been used, but with the advancement of technology to locate these active sensors, passive sensors are preferred. Passive sensors detect acoustic emissions, seismic movement, electromagnetic radiation, etc., produced by the target and use this information to describe it. Deriving the mathematical models to classify vehicles in this manner has been, and is, quite complex and not always reliable. However, with the resurgence of artificial neural network (ANN) research in the past few years, developing models for this work may be a thing of the past. Preliminary results from an ANN analysis to the tank signatures recorded at the Joint Acoustic Propagation Experiment (JAPE) at the US Army White Sands Missile Range, NM, in July 1991, are presented.

Automatic construction of a recurrent neural network based classifier for vehicle passage detection

NASA Astrophysics Data System (ADS)

Burnaev, Evgeny; Koptelov, Ivan; Novikov, German; Khanipov, Timur

2017-03-01

Recurrent Neural Networks (RNNs) are extensively used for time-series modeling and prediction. We propose an approach for automatic construction of a binary classifier based on Long Short-Term Memory RNNs (LSTM-RNNs) for detection of a vehicle passage through a checkpoint. As an input to the classifier we use multidimensional signals of various sensors that are installed on the checkpoint. Obtained results demonstrate that the previous approach to handcrafting a classifier, consisting of a set of deterministic rules, can be successfully replaced by an automatic RNN training on an appropriately labelled data.

Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

PubMed

Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

2017-02-10

Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

Multiple-Primitives Hierarchical Classification of Airborne Laser Scanning Data in Urban Areas

NASA Astrophysics Data System (ADS)

Ni, H.; Lin, X. G.; Zhang, J. X.

2017-09-01

A hierarchical classification method for Airborne Laser Scanning (ALS) data of urban areas is proposed in this paper. This method is composed of three stages among which three types of primitives are utilized, i.e., smooth surface, rough surface, and individual point. In the first stage, the input ALS data is divided into smooth surfaces and rough surfaces by employing a step-wise point cloud segmentation method. In the second stage, classification based on smooth surfaces and rough surfaces is performed. Points in the smooth surfaces are first classified into ground and buildings based on semantic rules. Next, features of rough surfaces are extracted. Then, points in rough surfaces are classified into vegetation and vehicles based on the derived features and Random Forests (RF). In the third stage, point-based features are extracted for the ground points, and then, an individual point classification procedure is performed to classify the ground points into bare land, artificial ground and greenbelt. Moreover, the shortages of the existing studies are analyzed, and experiments show that the proposed method overcomes these shortages and handles more types of objects.

Vehicle classification in WAMI imagery using deep network

NASA Astrophysics Data System (ADS)

Yi, Meng; Yang, Fan; Blasch, Erik; Sheaff, Carolyn; Liu, Kui; Chen, Genshe; Ling, Haibin

2016-05-01

Humans have always had a keen interest in understanding activities and the surrounding environment for mobility, communication, and survival. Thanks to recent progress in photography and breakthroughs in aviation, we are now able to capture tens of megapixels of ground imagery, namely Wide Area Motion Imagery (WAMI), at multiple frames per second from unmanned aerial vehicles (UAVs). WAMI serves as a great source for many applications, including security, urban planning and route planning. These applications require fast and accurate image understanding which is time consuming for humans, due to the large data volume and city-scale area coverage. Therefore, automatic processing and understanding of WAMI imagery has been gaining attention in both industry and the research community. This paper focuses on an essential step in WAMI imagery analysis, namely vehicle classification. That is, deciding whether a certain image patch contains a vehicle or not. We collect a set of positive and negative sample image patches, for training and testing the detector. Positive samples are 64 × 64 image patches centered on annotated vehicles. We generate two sets of negative images. The first set is generated from positive images with some location shift. The second set of negative patches is generated from randomly sampled patches. We also discard those patches if a vehicle accidentally locates at the center. Both positive and negative samples are randomly divided into 9000 training images and 3000 testing images. We propose to train a deep convolution network for classifying these patches. The classifier is based on a pre-trained AlexNet Model in the Caffe library, with an adapted loss function for vehicle classification. The performance of our classifier is compared to several traditional image classifier methods using Support Vector Machine (SVM) and Histogram of Oriented Gradient (HOG) features. While the SVM+HOG method achieves an accuracy of 91.2%, the accuracy of our deep network-based classifier reaches 97.9%.

Distribution of dilemma zone after intelligent transportation system established

NASA Astrophysics Data System (ADS)

Deng, Yuanchang; Yang, Huiqin; Wu, Linying

2017-03-01

Dilemma zone refers to an area where vehicles can neither clear the intersection during the yellow interval nor stop safely before the stop line. The purpose of this paper is to analyzing the distribution of two types of dilemma zone after intelligent transportation system (ITS) established at Outer Ring Roads signalized intersections in Guangzhou Higher Education Mega Center. To collect field data a drone aircraft was used. When calculating the type II dilemma zone's distribution, we considered the information of drivers' aggressiveness, which was classified by driving speed and type I dilemma zone as well. We also compared the two types dilemma zone's distribution before and after ITS established and analyzed the changes, which was brought by ITS.

Infrared target simulation environment for pattern recognition applications

NASA Astrophysics Data System (ADS)

Savakis, Andreas E.; George, Nicholas

1994-07-01

The generation of complete databases of IR data is extremely useful for training human observers and testing automatic pattern recognition algorithms. Field data may be used for realism, but require expensive and time-consuming procedures. IR scene simulation methods have emerged as a more economical and efficient alternative for the generation of IR databases. A novel approach to IR target simulation is presented in this paper. Model vehicles at 1:24 scale are used for the simulation of real targets. The temperature profile of the model vehicles is controlled using resistive circuits which are embedded inside the models. The IR target is recorded using an Inframetrics dual channel IR camera system. Using computer processing we place the recorded IR target in a prerecorded background. The advantages of this approach are: (1) the range and 3D target aspect can be controlled by the relative position between the camera and model vehicle; (2) the temperature profile can be controlled by adjusting the power delivered to the resistive circuit; (3) the IR sensor effects are directly incorporated in the recording process, because the real sensor is used; (4) the recorded target can embedded in various types of backgrounds recorded under different weather conditions, times of day etc. The effectiveness of this approach is demonstrated by generating an IR database of three vehicles which is used to train a back propagation neural network. The neural network is capable of classifying vehicle type, vehicle aspect, and relative temperature with a high degree of accuracy.

41 CFR 102-34.45 - How are passenger automobiles classified?

Code of Federal Regulations, 2013 CFR

2013-07-01

... automobiles classified? 102-34.45 Section 102-34.45 Public Contracts and Property Management Federal Property... MANAGEMENT Obtaining Fuel Efficient Motor Vehicles § 102-34.45 How are passenger automobiles classified? Passenger automobiles are classified in the following table: Sedan class Station wagon class Descriptive...

41 CFR 102-34.45 - How are passenger automobiles classified?

Code of Federal Regulations, 2014 CFR

2014-01-01

... automobiles classified? 102-34.45 Section 102-34.45 Public Contracts and Property Management Federal Property... MANAGEMENT Obtaining Fuel Efficient Motor Vehicles § 102-34.45 How are passenger automobiles classified? Passenger automobiles are classified in the following table: Sedan class Station wagon class Descriptive...

41 CFR 102-34.45 - How are passenger automobiles classified?

Code of Federal Regulations, 2011 CFR

2011-01-01

... automobiles classified? 102-34.45 Section 102-34.45 Public Contracts and Property Management Federal Property... MANAGEMENT Obtaining Fuel Efficient Motor Vehicles § 102-34.45 How are passenger automobiles classified? Passenger automobiles are classified in the following table: Sedan class Station wagon class Descriptive...

41 CFR 102-34.45 - How are passenger automobiles classified?

Code of Federal Regulations, 2012 CFR

2012-01-01

... automobiles classified? 102-34.45 Section 102-34.45 Public Contracts and Property Management Federal Property... MANAGEMENT Obtaining Fuel Efficient Motor Vehicles § 102-34.45 How are passenger automobiles classified? Passenger automobiles are classified in the following table: Sedan class Station wagon class Descriptive...

41 CFR 102-34.45 - How are passenger automobiles classified?

Code of Federal Regulations, 2010 CFR

2010-07-01

... automobiles classified? 102-34.45 Section 102-34.45 Public Contracts and Property Management Federal Property... MANAGEMENT Obtaining Fuel Efficient Motor Vehicles § 102-34.45 How are passenger automobiles classified? Passenger automobiles are classified in the following table: Sedan class Station wagon class Descriptive...

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

NASA Technical Reports Server (NTRS)

Neilan, James H.; Cross, Charles; Rothhaar, Paul; Tran, Loc; Motter, Mark; Qualls, Garry; Trujillo, Anna; Allen, B. Danette

2016-01-01

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

Pavement type and wear condition classification from tire cavity acoustic measurements with artificial neural networks.

PubMed

Masino, Johannes; Foitzik, Michael-Jan; Frey, Michael; Gauterin, Frank

2017-06-01

Tire road noise is the major contributor to traffic noise, which leads to general annoyance, speech interference, and sleep disturbances. Standardized methods to measure tire road noise are expensive, sophisticated to use, and they cannot be applied comprehensively. This paper presents a method to automatically classify different types of pavement and the wear condition to identify noisy road surfaces. The methods are based on spectra of time series data of the tire cavity sound, acquired under normal vehicle operation. The classifier, an artificial neural network, correctly predicts three pavement types, whereas there are few bidirectional mis-classifications for two pavements, which have similar physical characteristics. The performance measures of the classifier to predict a new or worn out condition are over 94.6%. One could create a digital map with the output of the presented method. On the basis of these digital maps, road segments with a strong impact on tire road noise could be automatically identified. Furthermore, the method can estimate the road macro-texture, which has an impact on the tire road friction especially on wet conditions. Overall, this digital map would have a great benefit for civil engineering departments, road infrastructure operators, and for advanced driver assistance systems.

40 CFR 86.085-20 - Incomplete vehicles, classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., classification. (a) An incomplete truck less than 8,500 pounds gross vehicle weight rating shall be classified by... 40 Protection of Environment 18 2010-07-01 2010-07-01 false Incomplete vehicles, classification... PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY VEHICLES AND ENGINES General...

Automated time activity classification based on global positioning system (GPS) tracking data

PubMed Central

2011-01-01

Background Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. Methods We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Results Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data. Conclusions Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns. PMID:22082316

Automated time activity classification based on global positioning system (GPS) tracking data.

PubMed

Wu, Jun; Jiang, Chengsheng; Houston, Douglas; Baker, Dean; Delfino, Ralph

2011-11-14

Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data. We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model. Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data. Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns.

Use of car crashes resulting in fatal and serious injuries to analyze a safe road transport system model and to identify system weaknesses.

PubMed

Stigson, Helena; Hill, Julian

2009-10-01

The objective of this study was to evaluate a model for a safe road transport system, based on some safety performance indicators regarding the road user, the vehicle, and the road, by using crashes with fatally and seriously injured car occupants. The study also aimed to evaluate whether the model could be used to identify system weaknesses and components (road user, vehicles, and road) where improvements would yield the highest potential for further reductions in serious injuries. Real-life car crashes with serious injury outcomes (Maximum Abbreviated Injury Scale 2+) were classified according to the vehicle's safety rating by Euro NCAP (European New Car Assessment Programme) and whether the vehicle was fitted with ESC (Electronic Stability Control). For each crash, the road was also classified according to EuroRAP (European Road Assessment Programme) criteria, and human behavior in terms of speeding, seat belt use, and driving under the influence of alcohol/drugs. Each crash was compared and classified according to the model criteria. Crashes where the safety criteria were not met in more than one of the 3 components were reclassified to identify whether all the components were correlated to the injury outcome. In-depth crash injury data collected by the UK On The Spot (OTS) accident investigation project was used in this study. All crashes in the OTS database occurring between 2000 and 2005 with a car occupant with injury rated MAIS2+ were included, for a total of 101 crashes with 120 occupants. It was possible to classify 90 percent of the crashes according to the model. Eighty-six percent of the occupants were injured when more than one of the 3 components were noncompliant with the safety criteria. These cases were reclassified to identify whether all of the components were correlated to the injury outcome. In 39 of the total 108 cases, at least two components were still seen to interact. The remaining cases were only related to one of the safety criteria, namely, the road user (26), the vehicle (19), and the road (24). The criteria for the road and the vehicle did not address multiple event crashes, rear-end crashes, hitting stationary/parked vehicles, or trailers. The model for a safe road transport system was found useful to classify fatal and serious road vehicle crashes. It was possible to classify 90 percent of the crashes according to the safety road transport model. For all these cases it was possible to identify weaknesses and parts of the road transport system with the highest potential to prevent fatal and serious injuries. Injury outcomes were mostly related to an interaction between the 3 components: the road, the vehicle, and the road user.

Using unmanned aerial vehicle-borne magnetic sensors to detect and locate improvised explosive devices and unexploded ordnance

NASA Astrophysics Data System (ADS)

Trammell, Hoke S., III; Perry, Alexander R.; Kumar, Sankaran; Czipott, Peter V.; Whitecotton, Brian R.; McManus, Tobin J.; Walsh, David O.

2005-05-01

Magnetic sensors configured as a tensor magnetic gradiometer not only detect magnetic targets, but also determine their location and their magnetic moment. Magnetic moment information can be used to characterize and classify objects. Unexploded ordnance (UXO) and thus many types of improvised explosive device (IED) contain steel, and thus can be detected magnetically. Suitable unmanned aerial vehicle (UAV) platforms, both gliders and powered craft, can enable coverage of a search area much more rapidly than surveys using, for instance, total-field magnetometers. We present data from gradiometer passes over different shells using a gradiometer mounted on a moving cart. We also provide detection range and speed estimates for aerial detection by a UAV.

Hybrid vehicle potential assessment. Volume 7: Hybrid vehicle review

NASA Technical Reports Server (NTRS)

Leschly, K. O.

1979-01-01

Review of hybrid vehicles built during the past ten years or planned to be built in the near future is presented. An attempt is made to classify and analyze these vehicles to get an overall picture of their key characteristics. The review includes onroad hybrid passenger cars, trucks, vans, and buses.

Predicting crash frequency for multi-vehicle collision types using multivariate Poisson-lognormal spatial model: A comparative analysis.

PubMed

Hosseinpour, Mehdi; Sahebi, Sina; Zamzuri, Zamira Hasanah; Yahaya, Ahmad Shukri; Ismail, Noriszura

2018-06-01

According to crash configuration and pre-crash conditions, traffic crashes are classified into different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear-end, and angle crashes, are more frequent than single-vehicle crashes, and most often result in serious consequences. From a methodological point of view, the majority of prior studies focused on multivehicle collisions have employed univariate count models to estimate crash counts separately by collision type. However, univariate models fail to account for correlations which may exist between different collision types. Among others, multivariate Poisson lognormal (MVPLN) model with spatial correlation is a promising multivariate specification because it not only allows for unobserved heterogeneity (extra-Poisson variation) and dependencies between collision types, but also spatial correlation between adjacent sites. However, the MVPLN spatial model has rarely been applied in previous research for simultaneously modelling crash counts by collision type. Therefore, this study aims at utilizing a MVPLN spatial model to estimate crash counts for four different multi-vehicle collision types, including head-on, rear-end, angle, and sideswipe collisions. To investigate the performance of the MVPLN spatial model, a two-stage model and a univariate Poisson lognormal model (UNPLN) spatial model were also developed in this study. Detailed information on roadway characteristics, traffic volume, and crash history were collected on 407 homogeneous segments from Malaysian federal roads. The results indicate that the MVPLN spatial model outperforms the other comparing models in terms of goodness-of-fit measures. The results also show that the inclusion of spatial heterogeneity in the multivariate model significantly improves the model fit, as indicated by the Deviance Information Criterion (DIC). The correlation between crash types is high and positive, implying that the occurrence of a specific collision type is highly associated with the occurrence of other crash types on the same road segment. These results support the utilization of the MVPLN spatial model when predicting crash counts by collision manner. In terms of contributing factors, the results show that distinct crash types are attributed to different subsets of explanatory variables. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fault detection and multiclassifier fusion for unmanned aerial vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Yan, Weizhong

2001-03-01

UAVs demand more accurate fault accommodation for their mission manager and vehicle control system in order to achieve a reliability level that is comparable to that of a pilot aircraft. This paper attempts to apply multi-classifier fusion techniques to achieve the necessary performance of the fault detection function for the Lockheed Martin Skunk Works (LMSW) UAV Mission Manager. Three different classifiers that meet the design requirements of the fault detection of the UAAV are employed. The binary decision outputs from the classifiers are then aggregated using three different classifier fusion schemes, namely, majority vote, weighted majority vote, and Naieve Bayes combination. All of the three schemes are simple and need no retraining. The three fusion schemes (except the majority vote that gives an average performance of the three classifiers) show the classification performance that is better than or equal to that of the best individual. The unavoidable correlation between the classifiers with binary outputs is observed in this study. We conclude that it is the correlation between the classifiers that limits the fusion schemes to achieve an even better performance.

Automatic vehicle counting system for traffic monitoring

NASA Astrophysics Data System (ADS)

Crouzil, Alain; Khoudour, Louahdi; Valiere, Paul; Truong Cong, Dung Nghy

2016-09-01

The article is dedicated to the presentation of a vision-based system for road vehicle counting and classification. The system is able to achieve counting with a very good accuracy even in difficult scenarios linked to occlusions and/or presence of shadows. The principle of the system is to use already installed cameras in road networks without any additional calibration procedure. We propose a robust segmentation algorithm that detects foreground pixels corresponding to moving vehicles. First, the approach models each pixel of the background with an adaptive Gaussian distribution. This model is coupled with a motion detection procedure, which allows correctly location of moving vehicles in space and time. The nature of trials carried out, including peak periods and various vehicle types, leads to an increase of occlusions between cars and between cars and trucks. A specific method for severe occlusion detection, based on the notion of solidity, has been carried out and tested. Furthermore, the method developed in this work is capable of managing shadows with high resolution. The related algorithm has been tested and compared to a classical method. Experimental results based on four large datasets show that our method can count and classify vehicles in real time with a high level of performance (>98%) under different environmental situations, thus performing better than the conventional inductive loop detectors.

Alternative Fuels Data Center

Science.gov Websites

vehicles altered to operate on propane, natural gas, methane gas, ethanol, or electricity are classified as information about vehicle conversion certification requirements, see the Alternative Fuels Data Center's

Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

NASA Astrophysics Data System (ADS)

Kachach, Redouane; Cañas, José María

2016-05-01

Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

Vehicle Detection with Occlusion Handling, Tracking, and OC-SVM Classification: A High Performance Vision-Based System

PubMed Central

Velazquez-Pupo, Roxana; Sierra-Romero, Alberto; Torres-Roman, Deni; Shkvarko, Yuriy V.; Romero-Delgado, Misael

2018-01-01

This paper presents a high performance vision-based system with a single static camera for traffic surveillance, for moving vehicle detection with occlusion handling, tracking, counting, and One Class Support Vector Machine (OC-SVM) classification. In this approach, moving objects are first segmented from the background using the adaptive Gaussian Mixture Model (GMM). After that, several geometric features are extracted, such as vehicle area, height, width, centroid, and bounding box. As occlusion is present, an algorithm was implemented to reduce it. The tracking is performed with adaptive Kalman filter. Finally, the selected geometric features: estimated area, height, and width are used by different classifiers in order to sort vehicles into three classes: small, midsize, and large. Extensive experimental results in eight real traffic videos with more than 4000 ground truth vehicles have shown that the improved system can run in real time under an occlusion index of 0.312 and classify vehicles with a global detection rate or recall, precision, and F-measure of up to 98.190%, and an F-measure of up to 99.051% for midsize vehicles. PMID:29382078

An algorithm for monitoring the traffic on a less-travelled road using multi-modal sensor suite

NASA Astrophysics Data System (ADS)

Damarla, Thyagaraju; Chatters, Gary; Liss, Brian; Vu, Hao; Sabatier, James M.

2014-06-01

We conducted an experiment to correlate the information gathered by a suite of hard sensors with the information on social networks such as Twitter, Facebook, etc. The experiment consisting of monitoring traffic on a well- traveled road and on a road inside a facility. The sensors suite selected mainly consists of sensors that require low power for operation and last a longtime. The output of each sensor is analyzed to classify the targets as ground vehicles, humans, and airborne targets. The algorithm is also used to count the number of targets belonging to each type so the sensor can store the information for anomaly detection. In this paper, we describe the classifier algorithms used for acoustic, seismic, and passive infrared (PIR) sensor data.

Hip and Wrist Accelerometer Algorithms for Free-Living Behavior Classification.

PubMed

Ellis, Katherine; Kerr, Jacqueline; Godbole, Suneeta; Staudenmayer, John; Lanckriet, Gert

2016-05-01

Accelerometers are a valuable tool for objective measurement of physical activity (PA). Wrist-worn devices may improve compliance over standard hip placement, but more research is needed to evaluate their validity for measuring PA in free-living settings. Traditional cut-point methods for accelerometers can be inaccurate and need testing in free living with wrist-worn devices. In this study, we developed and tested the performance of machine learning (ML) algorithms for classifying PA types from both hip and wrist accelerometer data. Forty overweight or obese women (mean age = 55.2 ± 15.3 yr; BMI = 32.0 ± 3.7) wore two ActiGraph GT3X+ accelerometers (right hip, nondominant wrist; ActiGraph, Pensacola, FL) for seven free-living days. Wearable cameras captured ground truth activity labels. A classifier consisting of a random forest and hidden Markov model classified the accelerometer data into four activities (sitting, standing, walking/running, and riding in a vehicle). Free-living wrist and hip ML classifiers were compared with each other, with traditional accelerometer cut points, and with an algorithm developed in a laboratory setting. The ML classifier obtained average values of 89.4% and 84.6% balanced accuracy over the four activities using the hip and wrist accelerometer, respectively. In our data set with average values of 28.4 min of walking or running per day, the ML classifier predicted average values of 28.5 and 24.5 min of walking or running using the hip and wrist accelerometer, respectively. Intensity-based cut points and the laboratory algorithm significantly underestimated walking minutes. Our results demonstrate the superior performance of our PA-type classification algorithm, particularly in comparison with traditional cut points. Although the hip algorithm performed better, additional compliance achieved with wrist devices might justify using a slightly lower performing algorithm.

32 CFR 154.18 - Certain positions not necessarily requiring access to classified information.

Code of Federal Regulations, 2011 CFR

2011-07-01

... contract employee (including commercial carrier) operating a vehicle or providing security to a vehicle... military, civilian personnel, consultants, and contractor personnel performing on unclassified automated...

Characterization of individual complex particles in urban atmospheric environment

NASA Astrophysics Data System (ADS)

Suzuki, K.; Takii, T.; Tomiyasu, B.; Nihei, Y.

2006-07-01

The origins of carrier particles of complex particles (iron-rich particles) collected from the urban atmospheric environment near to road traffic and a railroad were investigated from the detailed surface information using FE-SEM/EDS and TOF-SIMS analyses. From the FE-SEM/EDS analyses, the iron-rich particles were classified into two typical types (spherical type and non-spherical type). From the TOF-SIMS measurements, the characteristic secondary ions of spherical type of iron-rich particles were 23Na + and 39K +. The minor components of non-spherical type were Al, Ca and Ba. On the other hand, we carried out TOF-SIMS measurement to materials of rail origin and brake origin. From the comparison of these spectra pattern, it seemed that the spherical type of iron-rich particles was emitted from the rail origin. We concluded that the origin of non-spherical type of iron-rich particles were brake pad of vehicles.

Studies of vehicle overtaking dynamics and its influence on traffic flow at a bidirectional road

NASA Astrophysics Data System (ADS)

Echab, H.; Marzoug, R.; Lakouari, N.; Ez-Zahraouy, H.

For the purposes of optimizing traffic flow composed of different types of vehicles, it is important to understand the interactions between them. This paper proposes a cellular automata model to investigate a bidirectional two-lane traffic flow under the periodic boundary condition. The vehicle flux and the phase diagrams of the system in the (ρ1,ρ2) space are constructed by applying two different overtaking models (symmetric, asymmetric). The inter-lane correlation and the overtaking frequency are also studied. The simulation results show that the variation of the density of one lane has an apparent influence on the traffic of the adjacent lane. Furthermore, it is found that the phase diagram on both models is classified into several regions. Thus, for the symmetric model, as the overtaking probability increases, the traffic on the system becomes better. Likewise, the results also indicate that the asymmetric model can effectively enhance the traffic capacity and alleviate the congested state.

Monocular precrash vehicle detection: features and classifiers.

PubMed

Sun, Zehang; Bebis, George; Miller, Ronald

2006-07-01

Robust and reliable vehicle detection from images acquired by a moving vehicle (i.e., on-road vehicle detection) is an important problem with applications to driver assistance systems and autonomous, self-guided vehicles. The focus of this work is on the issues of feature extraction and classification for rear-view vehicle detection. Specifically, by treating the problem of vehicle detection as a two-class classification problem, we have investigated several different feature extraction methods such as principal component analysis, wavelets, and Gabor filters. To evaluate the extracted features, we have experimented with two popular classifiers, neural networks and support vector machines (SVMs). Based on our evaluation results, we have developed an on-board real-time monocular vehicle detection system that is capable of acquiring grey-scale images, using Ford's proprietary low-light camera, achieving an average detection rate of 10 Hz. Our vehicle detection algorithm consists of two main steps: a multiscale driven hypothesis generation step and an appearance-based hypothesis verification step. During the hypothesis generation step, image locations where vehicles might be present are extracted. This step uses multiscale techniques not only to speed up detection, but also to improve system robustness. The appearance-based hypothesis verification step verifies the hypotheses using Gabor features and SVMs. The system has been tested in Ford's concept vehicle under different traffic conditions (e.g., structured highway, complex urban streets, and varying weather conditions), illustrating good performance.

Implications of uncertainty on regional CO2 mitigation policies for the U.S. onroad sector based on a high-resolution emissions estimate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mendoza, D.; Gurney, Kevin R.; Geethakumar, Sarath

2013-04-01

In this study we present onroad fossil fuel CO2 emissions estimated by the Vulcan Project, an effort quantifying fossil fuel CO2 emissions for the U.S. in high spatial and temporal resolution. This high-resolution data, aggregated at the state-level and classified in broad road and vehicle type categories, is compared to a commonly used national-average approach. We find that the use of national averages incurs state-level biases for road groupings that are almost twice as large as for vehicle groupings. The uncertainty for all groups exceeds the bias, and both quantities are positively correlated with total state emissions. States with themore » largest emissions totals are typically similar to one another in terms of emissions fraction distribution across road and vehicle groups, while smaller-emitting states have a wider range of variation in all groups. Errors in reduction estimates as large as ±60% corresponding to ±0.2 MtC are found for a national-average emissions mitigation strategy focused on a 10% emissions reduction from a single vehicle class, such as passenger gas vehicles or heavy diesel trucks. Recommendations are made for reducing CO2 emissions uncertainty by addressing its main drivers: VMT and fuel efficiency uncertainty.« less

A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles.

PubMed

Suhr, Jae Kyu; Jung, Ho Gi

2018-04-16

An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The proposed method can readily be commercialized since it uses only those sensors already mounted on off-the-shelf vehicles: an around-view monitor (AVM) system, ultrasonic sensors, and in-vehicle motion sensors. This method first detects separating lines by extracting parallel line pairs from AVM images. Parking slot candidates are generated by pairing separating lines based on the geometric constraints of the parking slot. These candidates are confirmed by recognizing their entrance positions using line and corner features and classifying their occupancies using ultrasonic sensors. For more reliable recognition, this method uses the separating lines and parking slots not only found in the current image but also found in previous images by tracking their positions using the in-vehicle motion-sensor-based vehicle odometry. The proposed method was quantitatively evaluated using a dataset obtained during the day, night, and underground, and it outperformed previous methods by showing a 95.24% recall and a 97.64% precision.

A Universal Vacant Parking Slot Recognition System Using Sensors Mounted on Off-the-Shelf Vehicles

PubMed Central

2018-01-01

An automatic parking system is an essential part of autonomous driving, and it starts by recognizing vacant parking spaces. This paper proposes a method that can recognize various types of parking slot markings in a variety of lighting conditions including daytime, nighttime, and underground. The proposed method can readily be commercialized since it uses only those sensors already mounted on off-the-shelf vehicles: an around-view monitor (AVM) system, ultrasonic sensors, and in-vehicle motion sensors. This method first detects separating lines by extracting parallel line pairs from AVM images. Parking slot candidates are generated by pairing separating lines based on the geometric constraints of the parking slot. These candidates are confirmed by recognizing their entrance positions using line and corner features and classifying their occupancies using ultrasonic sensors. For more reliable recognition, this method uses the separating lines and parking slots not only found in the current image but also found in previous images by tracking their positions using the in-vehicle motion-sensor-based vehicle odometry. The proposed method was quantitatively evaluated using a dataset obtained during the day, night, and underground, and it outperformed previous methods by showing a 95.24% recall and a 97.64% precision. PMID:29659512

Analysis of resonance mechanism and conditions of train bridge system

NASA Astrophysics Data System (ADS)

Xia, H.; Zhang, N.; Guo, W. W.

2006-11-01

In this paper, the resonance mechanism and conditions of train-bridge system are investigated through theoretical derivations, numerical simulations and experimental data analyses. The resonant responses of the bridge induced by moving trains are classified into three types according to different resonance mechanisms: the first is related to the periodical actions of moving load series of the vertical weights, lateral centrifugal and wind forces of vehicles; the second is induced by the loading rate of moving load series of vehicles; the third is owing to the periodically loading of the swing forces of the train vehicles excited by track irregularities and wheel hunting movements. The vehicle resonance is induced by the periodical action of regular arrangement of bridge spans and their deflections. The resonant conditions are proposed and the corresponding resonant train speeds are determined. The application scopes of resonance conditions are discussed. The resonance of the train-bridge system is affected by the span, total length, lateral and vertical stiffness of the bridge, the compositions of the train, and the axle arrangements and natural frequencies of the vehicles. The resonant train speeds for some bridges are estimated and are compared with the critical train speeds obtained from the dynamic simulation of train-bridge interaction model or from the field measurements.

STS-38 Space Shuttle mission report

NASA Technical Reports Server (NTRS)

Camp, David W.; Germany, D. M.; Nicholson, Leonard S.

1991-01-01

The STS-38 Space Shuttle Program Mission Report contains a summary of the vehicle subsystem activities on this thirty-seventh flight of the Space Shuttle and the seventh flight of the Orbiter vehicle Atlantis (OV-104). In addition to the Atlantis vehicle, the flight vehicle consisted of an External Tank (ET) (designated as ET-40/LWT-33), three Space Shuttle main engines (SSME's) (serial numbers 2019, 2022, 2027), and two Solid Rocket Boosters (SRB's), designated as BI-039. The STS-38 mission was a classified Department of Defense mission, and as much, the classified portions of the mission are not presented in this report. The sequence of events for this mission is shown. The significant problems that occurred in the Space Shuttle Orbiter subsystem during the mission are summarized and the official problem tracking list is presented. In addition, each Space Shuttle Orbiter problem is cited in the subsystem discussion.

STS-36 Space Shuttle mission report

NASA Technical Reports Server (NTRS)

Mechelay, Joseph E.; Germany, D. M.; Nicholson, Leonard S.

1990-01-01

The STS-36 Space Shuttle Program Mission Report contains a summary of the vehicle subsystem activities on this thirty-fourth flight of the Space Shuttle and the sixth flight of the OV-104 Orbiter vehicle, Atlantis. In addition to the Atlantis vehicle, the flight vehicle consisted of an External Tank (ET) (designated as ET-33/LWT-26), three Space Shuttle main engines (SSME's) (serial numbers 2019, 2030, and 2029), and two Solid Rocket Boosters (SRB's) (designated as BI-036). The STS-36 mission was a classified Department of Defense mission, and as such, the classified portions of the mission are not discussed. The unclassified sequence of events for this mission is shown in tabular form. Summarized are the significant problems that occurred in the Orbiter subsystems during the mission. The official problem tracking list is presented. In addition, each of the Orbiter problems is cited in the subsystem discussion.

Intelligence and Electronic Warfare (IEW) System Fact Sheets

DTIC Science & Technology

1994-04-06

unattended ground sensor system that detects, classifies, and determines direction of movement of intruding personnel and vehicles . It uses remotely...fixed and moving target locations, speed and direction of movement, and classification of tracked/wheeled vehicles . The GSM is equipped with standard... Vehicle The Pointer is a Hand-Launched Unmanned Aerial Vehicle (HL-UAV) to be employed by battalion scouts for t"over-the-hillll reconnaissance and

Safety effects of exclusive and concurrent signal phasing for pedestrian crossing.

PubMed

Zhang, Yaohua; Mamun, Sha A; Ivan, John N; Ravishanker, Nalini; Haque, Khademul

2015-10-01

This paper describes the estimation of pedestrian crash count and vehicle interaction severity prediction models for a sample of signalized intersections in Connecticut with either concurrent or exclusive pedestrian phasing. With concurrent phasing, pedestrians cross at the same time as motor vehicle traffic in the same direction receives a green phase, while with exclusive phasing, pedestrians cross during their own phase when all motor vehicle traffic on all approaches is stopped. Pedestrians crossing at each intersection were observed and classified according to the severity of interactions with motor vehicles. Observation intersections were selected to represent both types of signal phasing while controlling for other physical characteristics. In the nonlinear mixed models for interaction severity, pedestrians crossing on the walk signal at an exclusive signal experienced lower interaction severity compared to those crossing on the green light with concurrent phasing; however, pedestrians crossing on a green light where an exclusive phase was available experienced higher interaction severity. Intersections with concurrent phasing have fewer total pedestrian crashes than those with exclusive phasing but more crashes at higher severity levels. It is recommended that exclusive pedestrian phasing only be used at locations where pedestrians are more likely to comply. Copyright © 2015. Published by Elsevier Ltd.

Systematic review of military motor vehicle crash-related injuries.

PubMed

Krahl, Pamela L; Jankosky, Christopher J; Thomas, Richard J; Hooper, Tomoko I

2010-01-01

Motor vehicle crashes account for nearly one third of U.S. military fatalities annually. The objective of this review is to summarize the published evidence on injuries due specifically to military motor vehicle (MMV) crashes. A search of 18 electronic databases identified English language publications addressing MMV crash-related injuries between 1970 and 2006 that were available to the general public. Documents limited in distribution to military or government personnel were not evaluated. Relevant articles were categorized by study design. The search identified only 13 studies related specifically to MMV crashes. Most were case reports or case series (n=8); only one could be classified as an intervention study. Nine of the studies were based solely on data from service-specific military safety centers. Few studies exist on injuries resulting from crashes of military motor vehicles. Epidemiologic studies that assess injury rates, type, severity, and risk factors are needed, followed by studies to evaluate targeted interventions and prevention strategies. Interventions currently underway should be evaluated for effectiveness, and those proven effective in the civilian community, such as graduated driver licensing, should be considered for implementation and evaluation in military populations. Published by Elsevier Inc.

Evaluation of the statutory classification of three-wheeled, motorized invalid vehicles.

DOT National Transportation Integrated Search

1978-01-01

In response to an objection by interested individuals to the fact that Virginia law classifies three-wheeled, motorized invalid vehicles as motorcycles and subjects them to all registration, safety inspection, and operator requirements applicable to ...

Use of fatal real-life crashes to analyze a safe road transport system model, including the road user, the vehicle, and the road.

PubMed

Stigson, Helena; Krafft, Maria; Tingvall, Claes

2008-10-01

To evaluate if the Swedish Road Administration (SRA) model for a safe road transport system, which includes the interaction between the road user, the vehicle, and the road, could be used to classify fatal car crashes according to some safety indicators. Also, to present a development of the model to better identify system weakness. Real-life crashes with a fatal outcome were classified according to the vehicle's safety rating by Euro NCAP (European Road Assessment Programme) and fitment of ESC (Electronic Stability Control). For each crash, the road was also classified according to EuroRAP (European Road Assessment Programme) criteria, and human behavior in terms of speeding, seat belt use, and driving under the influence of alcohol. Each crash was compared with the model criteria, to identify components that might have contributed to fatal outcome. All fatal crashes where a car occupant was killed that occurred in Sweden during 2004 were included: in all, 215 crashes with 248 fatalities. The data were collected from the in-depth fatal crash data of the Swedish Road Administration (SRA). It was possible to classify 93% of the fatal car crashes according to the SRA model. A number of shortcomings in the criteria were identified since the model did not address rear-end or animal collisions or collisions with stationary/parked vehicles or trailers (18 out of 248 cases). Using the further developed model, it was possible to identify that most of the crashes occurred when two or all three components interacted (in 85 of the total 230 cases). Noncompliance with safety criteria for the road user, the vehicle, and the road led to fatal outcome in 43, 27, and 75 cases, respectively. The SRA model was found to be useful for classifying fatal crashes but needs to be further developed to identify how the components interact and thereby identify weaknesses in the road traffic system. This developed model might be a tool to systematically identify which of the components are linked to fatal outcome. In the presented study, fatal outcomes were mostly related to an interaction between the three components: the road, the vehicle, and the road user. Of the three components, the road was the one that was most often linked to a fatal outcome.

Estimating the contributions of mobile sources of PAH to urban air using real-time PAH monitoring.

PubMed

Dunbar, J C; Lin, C I; Vergucht, I; Wong, J; Duran, J L

2001-11-12

Motor vehicles are a significant source of airborne polycyclic aromatic hydrocarbons (PAH) in many urban areas. Traditional approaches used in determining the relative contributions of individual vehicle types to the total amount of PAH in air have been based on the analysis of integrated samples of airborne particles and gases for the presence of chemical tracers indicative of the vehicles from which the chemicals derived. As an alternative, we have used a photoelectric aerosol sensor (PAS) capable of measuring PAH levels in real-time in the emissions plumes from motor vehicles. We placed the PAS near a traffic-light in Kenmore Square, a busy crossroads in downtown Boston (MA, USA). A video camera co-located at the site recorded the vehicles passing the sensor, and this record was correlated with the PAS data. During a 5-day monitoring period (approximately 59 h) in the summer of 1998, over 34,000 motor vehicles were counted and classified and over 24,000 PAS readings were recorded (frequency = 1/8.6 s). The composition of the vehicle population was 94% passenger vehicles, 1.4% buses, 2.6% small trucks, 1.3% medium trucks, 0.35% large trucks, and 0.45% garbage and construction trucks. In analyzing the PAS data, it was assumed that the highest PAS measurements--those that exceeded the 95% critical level of the 5-min moving average of all the PAS measurements--were indicative of primary vehicular emissions. We found that approximately 46% of the mass of particle-bound PAH (i.e. approximately 46% of the integrated area under the PAS signal vs. time plots) was attributable to primary emissions from motor vehicles passing the sensor. Of this, 35-61% was attributable to passenger vehicles (cars, pickup trucks, and sports utility vehicles) and 39-65% was attributable to non-passenger vehicles [buses (14-23%), small trucks (12-20%), medium trucks (8.4-14%), large trucks (2.9-4.8%) and garbage and construction trucks (1.9-3.2%)]. Our results suggest that on a per vehicle basis, buses and trucks--the majority of which run on diesel fuel--emitted greater amounts of particle-bound PAH than passenger vehicles. Overall, we found that real-time photoelectric aerosol sensing (in combination with video photography) is useful for estimating the contributions of airborne PAB from different vehicle types. Due to the physical constraints of our monitoring site and the high volumes of traffic, however, it was not possible to uniquely attribute PAS signals to individual vehicles.

Increasing accuracy of vehicle speed measurement in congested traffic over dual-loop sensors.

DOT National Transportation Integrated Search

2014-09-01

Classified vehicle counts are a critical measure for forecasting the health of the roadway infrastructure : and for planning future improvements to the transportation network. Balancing the cost of data : collection with the fidelity of the measureme...

Idea Project Final Report, Laser Vehicle Detector-Classifier

DOT National Transportation Integrated Search

1995-11-28

WEIGH-IN-MOTION OR WIM, COMMERCIAL VEHICLE OPERATIONS OR CVO : THIS INVESTIGATION WAS COMPLETED AS PART OF THE ITS-IDEA PROGRAM, WHICH IS ONE OF THREE IDEA PROGRAMS MANAGED BY THE TRANSPORTATION RESEARCH BOARD (TRB) TO FOSTER INNOVATIONS IN SURFAC...

A Study of Feature Combination for Vehicle Detection Based on Image Processing

PubMed Central

2014-01-01

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification. PMID:24672299

An assessment of autonomous vehicles : traffic impacts and infrastructure needs : final report.

DOT National Transportation Integrated Search

2017-03-01

The project began by understanding the current state of practice and trends. NHTSAs four-level taxonomy for automated vehicles was used to classify smart driving technologies and infrastructure needs. The project used surveys to analyze and gain a...

40 CFR 86.094-21 - Application for certification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... dedicated vehicle (manufacturers must obtain advance approval from the Administrator to classify methanol..., Liquefied Petroleum Gas-Fueled and Methanol-Fueled Heavy-Duty Vehicles § 86.094-21 Application for... methanol-fueled engines, the Administrator does not assume that each evaporative emission family...

Online Aerial Terrain Mapping for Ground Robot Navigation.

PubMed

Peterson, John; Chaudhry, Haseeb; Abdelatty, Karim; Bird, John; Kochersberger, Kevin

2018-02-20

This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle's overhead view to inform the ground vehicle's path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles. This paper describes the architecture of the system and quantifies the registration errors between the vehicles.

Research in interactive scene analysis

NASA Technical Reports Server (NTRS)

Tenenbaum, J. M.; Barrow, H. G.; Weyl, S. A.

1976-01-01

Cooperative (man-machine) scene analysis techniques were developed whereby humans can provide a computer with guidance when completely automated processing is infeasible. An interactive approach promises significant near-term payoffs in analyzing various types of high volume satellite imagery, as well as vehicle-based imagery used in robot planetary exploration. This report summarizes the work accomplished over the duration of the project and describes in detail three major accomplishments: (1) the interactive design of texture classifiers; (2) a new approach for integrating the segmentation and interpretation phases of scene analysis; and (3) the application of interactive scene analysis techniques to cartography.

Comparison of performance of object-based image analysis techniques available in open source software (Spring and Orfeo Toolbox/Monteverdi) considering very high spatial resolution data

NASA Astrophysics Data System (ADS)

Teodoro, Ana C.; Araujo, Ricardo

2016-01-01

The use of unmanned aerial vehicles (UAVs) for remote sensing applications is becoming more frequent. However, this type of information can result in several software problems related to the huge amount of data available. Object-based image analysis (OBIA) has proven to be superior to pixel-based analysis for very high-resolution images. The main objective of this work was to explore the potentialities of the OBIA methods available in two different open source software applications, Spring and OTB/Monteverdi, in order to generate an urban land cover map. An orthomosaic derived from UAVs was considered, 10 different regions of interest were selected, and two different approaches were followed. The first one (Spring) uses the region growing segmentation algorithm followed by the Bhattacharya classifier. The second approach (OTB/Monteverdi) uses the mean shift segmentation algorithm followed by the support vector machine (SVM) classifier. Two strategies were followed: four classes were considered using Spring and thereafter seven classes were considered for OTB/Monteverdi. The SVM classifier produces slightly better results and presents a shorter processing time. However, the poor spectral resolution of the data (only RGB bands) is an important factor that limits the performance of the classifiers applied.

Comparison of injury mortality risk in motor vehicle crash versus other etiologies.

PubMed

Kilgo, Patrick D; Weaver, Ashley A; Barnard, Ryan T; Love, Timothy P; Stitzel, Joel D

2014-06-01

The mortality risk ratio (MRR), a measure of the proportion of people who died that sustained a given injury, is reported to be among the most powerful discriminators of mortality following trauma. The primary aim was to determine whether mechanistic differences exist and are quantifiable when comparing MRR-based injury severity across two broadly defined etiologies (motor vehicle crash (MVC) versus non-MVC) for the clarification of important injury types that have some room for improvement by emergency treatment and vehicle design. All International Classification of Diseases, 9th revision (ICD-9) coded injuries in the National Trauma Data Bank (NTDB) database were stratified into MVC and non-MVC groups and the MRR for each injury was computed within each group. Injuries were classified as 11 different types for MRR comparison between etiologies. Overall, MRRs for specific injuries were 10-18% lower for MVC compared to non-MVC etiologies. MVCs however produced much higher mean MRRs for crushing injuries (0.184 versus 0.072) and internal injuries to the thorax, abdomen, and pelvis (0.200 versus 0.169). Non-MVCs produced much higher MRRs for intracranial injuries (0.199 versus 0.250). Analysis of the top 95% most frequent MVC injuries revealed higher MVC MRR values for 78% of the injuries with MRR ratios indicating an average 50% increase in a given injury's MRR when MVC was the etiology. Addressing the large differences in MRR in between etiologies for identical injuries could provide a reduction in fatalities and may be important to patient triage and vehicle safety design. Copyright © 2014 Elsevier Ltd. All rights reserved.

40 CFR 372.23 - SIC and NAICS codes to which this Part applies.

Code of Federal Regulations, 2014 CFR

2014-07-01

... engaged in manufacturing orthopedic devices to prescription in a retail environment (previously classified... for facilities primarily engaged in web search portals; 541712—Research and Development in the... engaged in Guided missile and space vehicle engine research and development (previously classified under...

Improving Night Time Driving Safety Using Vision-Based Classification Techniques.

PubMed

Chien, Jong-Chih; Chen, Yong-Sheng; Lee, Jiann-Der

2017-09-24

The risks involved in nighttime driving include drowsy drivers and dangerous vehicles. Prominent among the more dangerous vehicles around at night are the larger vehicles which are usually moving faster at night on a highway. In addition, the risk level of driving around larger vehicles rises significantly when the driver's attention becomes distracted, even for a short period of time. For the purpose of alerting the driver and elevating his or her safety, in this paper we propose two components for any modern vision-based Advanced Drivers Assistance System (ADAS). These two components work separately for the single purpose of alerting the driver in dangerous situations. The purpose of the first component is to ascertain that the driver would be in a sufficiently wakeful state to receive and process warnings; this is the driver drowsiness detection component. The driver drowsiness detection component uses infrared images of the driver to analyze his eyes' movements using a MSR plus a simple heuristic. This component issues alerts to the driver when the driver's eyes show distraction and are closed for a longer than usual duration. Experimental results show that this component can detect closed eyes with an accuracy of 94.26% on average, which is comparable to previous results using more sophisticated methods. The purpose of the second component is to alert the driver when the driver's vehicle is moving around larger vehicles at dusk or night time. The large vehicle detection component accepts images from a regular video driving recorder as input. A bi-level system of classifiers, which included a novel MSR-enhanced KAZE-base Bag-of-Features classifier, is proposed to avoid false negatives. In both components, we propose an improved version of the Multi-Scale Retinex (MSR) algorithm to augment the contrast of the input. Several experiments were performed to test the effects of the MSR and each classifier, and the results are presented in experimental results section of this paper.

Improving Night Time Driving Safety Using Vision-Based Classification Techniques

PubMed Central

Chien, Jong-Chih; Chen, Yong-Sheng; Lee, Jiann-Der

2017-01-01

The risks involved in nighttime driving include drowsy drivers and dangerous vehicles. Prominent among the more dangerous vehicles around at night are the larger vehicles which are usually moving faster at night on a highway. In addition, the risk level of driving around larger vehicles rises significantly when the driver’s attention becomes distracted, even for a short period of time. For the purpose of alerting the driver and elevating his or her safety, in this paper we propose two components for any modern vision-based Advanced Drivers Assistance System (ADAS). These two components work separately for the single purpose of alerting the driver in dangerous situations. The purpose of the first component is to ascertain that the driver would be in a sufficiently wakeful state to receive and process warnings; this is the driver drowsiness detection component. The driver drowsiness detection component uses infrared images of the driver to analyze his eyes’ movements using a MSR plus a simple heuristic. This component issues alerts to the driver when the driver’s eyes show distraction and are closed for a longer than usual duration. Experimental results show that this component can detect closed eyes with an accuracy of 94.26% on average, which is comparable to previous results using more sophisticated methods. The purpose of the second component is to alert the driver when the driver’s vehicle is moving around larger vehicles at dusk or night time. The large vehicle detection component accepts images from a regular video driving recorder as input. A bi-level system of classifiers, which included a novel MSR-enhanced KAZE-base Bag-of-Features classifier, is proposed to avoid false negatives. In both components, we propose an improved version of the Multi-Scale Retinex (MSR) algorithm to augment the contrast of the input. Several experiments were performed to test the effects of the MSR and each classifier, and the results are presented in experimental results section of this paper. PMID:28946643

CA Air Resource Board's On-Road Diesel Regulation: TRUCRS Reporting for CY2017.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jadhav, Pradnya

Diesel on-road vehicles with a Gross Vehicle Weight Rating (GVWR) greater than 14,000 pounds that operate in California are subject to the On-Road Diesel-Vehicle Regulation. SNL/CA operates eight diesel vehicles that are subject to this regulation; four of the vehicles are classified as low-use vehicles and four of the vehicles have Particulate Matter Filters installed as original equipment. This regulation requires that all fleets using flexibility options, such as the low-use exemption, report annually by January 31 in order to extend the exemption for that year. CA ARB encourages facilities to complete the reporting requirements using the TRUCRS on-line reportingmore » tool.« less

Unmanned Aerial Vehicles Produce High-Resolution Seasonally-Relevant Imagery for Classifying Wetland Vegetation

NASA Astrophysics Data System (ADS)

Marcaccio, J. V.; Markle, C. E.; Chow-Fraser, P.

2015-08-01

With recent advances in technology, personal aerial imagery acquired with unmanned aerial vehicles (UAVs) has transformed the way ecologists can map seasonal changes in wetland habitat. Here, we use a multi-rotor (consumer quad-copter, the DJI Phantom 2 Vision+) UAV to acquire a high-resolution (< 8 cm) composite photo of a coastal wetland in summer 2014. Using validation data collected in the field, we determine if a UAV image and SWOOP (Southwestern Ontario Orthoimagery Project) image (collected in spring 2010) differ in their classification of type of dominant vegetation type and percent cover of three plant classes: submerged aquatic vegetation, floating aquatic vegetation, and emergent vegetation. The UAV imagery was more accurate than available SWOOP imagery for mapping percent cover of submergent and floating vegetation categories, but both were able to accurately determine the dominant vegetation type and percent cover of emergent vegetation. Our results underscore the value and potential for affordable UAVs (complete quad-copter system < 3,000 CAD) to revolutionize the way ecologists obtain imagery and conduct field research. In Canada, new UAV regulations make this an easy and affordable way to obtain multiple high-resolution images of small (< 1.0 km2) wetlands, or portions of larger wetlands throughout a year.

Asphyxia: a rare cause of death for motor vehicle crash occupants.

PubMed

Conroy, Carol; Stanley, Christina; Eastman, A Brent; Vaughan, Teresa; Vilke, Gary M; Hoyt, David B; Pacyna, Sharon; Smith, Alan

2008-03-01

Motor vehicle related trauma is one of the leading causes of traumatic death. Although most of these deaths are because of severe blunt force trauma, there are people without severe injury who die of asphyxia related to the motor vehicle collision. There were 37 deaths because of motor vehicle related asphyxia in San Diego County during 1995-2004. Almost half (48.6%) of these deaths were because of compression asphyxia, 29.7% were positional asphyxia deaths, and 16.2% died of a combination of compression and positional asphyxia. We were unable to classify the mechanism of asphyxia for the remaining 5.4% of asphyxia deaths. Almost all occupants dying from asphyxia were involved in rollover crashes and may have been incapacitated by obesity, drug or alcohol intoxication, or blunt force trauma. Compression asphyxia deaths occurred both from vehicle crush with intrusion into the passenger compartment and from ejection of the occupant and subsequent crushing by the vehicle. Positional asphyxia occurred in positions interfering with normal respiration, including inversion. None of the occupants had injury severe enough to result in death at the scene if they had not first died of asphyxia. This study suggests classifying the mechanism of asphyxia for these fatalities may be a challenge to forensic pathologists who seldom see these rare deaths.

14 CFR 420.19 - Launch site location review-general.

Code of Federal Regulations, 2011 CFR

2011-01-01

... nm orbit Weight class Small Medium Medium large Large 28 degrees inclination * ≤4400 >4400 to ≤11100.... Orbital expendable launch vehicles are further classified by weight class, based on the weight of payload... class of orbital expendable launch vehicles flown from a launch point, the applicant shall demonstrate...

Online Aerial Terrain Mapping for Ground Robot Navigation

PubMed Central

Peterson, John; Chaudhry, Haseeb; Abdelatty, Karim; Bird, John; Kochersberger, Kevin

2018-01-01

This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle’s overhead view to inform the ground vehicle’s path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles. This paper describes the architecture of the system and quantifies the registration errors between the vehicles. PMID:29461496

Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles

PubMed Central

Gökçe, Fatih; Üçoluk, Göktürk; Şahin, Erol; Kalkan, Sinan

2015-01-01

Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032×778 resolution) and 150 ms outdoors (1280×720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms. PMID:26393599

Comparison and validation of injury risk classifiers for advanced automated crash notification systems.

PubMed

Kusano, Kristofer; Gabler, Hampton C

2014-01-01

The odds of death for a seriously injured crash victim are drastically reduced if he or she received care at a trauma center. Advanced automated crash notification (AACN) algorithms are postcrash safety systems that use data measured by the vehicles during the crash to predict the likelihood of occupants being seriously injured. The accuracy of these models are crucial to the success of an AACN. The objective of this study was to compare the predictive performance of competing injury risk models and algorithms: logistic regression, random forest, AdaBoost, naïve Bayes, support vector machine, and classification k-nearest neighbors. This study compared machine learning algorithms to the widely adopted logistic regression modeling approach. Machine learning algorithms have not been commonly studied in the motor vehicle injury literature. Machine learning algorithms may have higher predictive power than logistic regression, despite the drawback of lacking the ability to perform statistical inference. To evaluate the performance of these algorithms, data on 16,398 vehicles involved in non-rollover collisions were extracted from the NASS-CDS. Vehicles with any occupants having an Injury Severity Score (ISS) of 15 or greater were defined as those requiring victims to be treated at a trauma center. The performance of each model was evaluated using cross-validation. Cross-validation assesses how a model will perform in the future given new data not used for model training. The crash ΔV (change in velocity during the crash), damage side (struck side of the vehicle), seat belt use, vehicle body type, number of events, occupant age, and occupant sex were used as predictors in each model. Logistic regression slightly outperformed the machine learning algorithms based on sensitivity and specificity of the models. Previous studies on AACN risk curves used the same data to train and test the power of the models and as a result had higher sensitivity compared to the cross-validated results from this study. Future studies should account for future data; for example, by using cross-validation or risk presenting optimistic predictions of field performance. Past algorithms have been criticized for relying on age and sex, being difficult to measure by vehicle sensors, and inaccuracies in classifying damage side. The models with accurate damage side and including age/sex did outperform models with less accurate damage side and without age/sex, but the differences were small, suggesting that the success of AACN is not reliant on these predictors.

Vehicle Detection for RCTA/ANS (Autonomous Navigation System)

NASA Technical Reports Server (NTRS)

Brennan, Shane; Bajracharya, Max; Matthies, Larry H.; Howard, Andrew B.

2012-01-01

Using a stereo camera pair, imagery is acquired and processed through the JPLV stereo processing pipeline. From this stereo data, large 3D blobs are found. These blobs are then described and classified by their shape to determine which are vehicles and which are not. Prior vehicle detection algorithms are either targeted to specific domains, such as following lead cars, or are intensity- based methods that involve learning typical vehicle appearances from a large corpus of training data. In order to detect vehicles, the JPL Vehicle Detection (JVD) algorithm goes through the following steps: 1. Take as input a left disparity image and left rectified image from JPLV stereo. 2. Project the disparity data onto a two-dimensional Cartesian map. 3. Perform some post-processing of the map built in the previous step in order to clean it up. 4. Take the processed map and find peaks. For each peak, grow it out into a map blob. These map blobs represent large, roughly vehicle-sized objects in the scene. 5. Take these map blobs and reject those that do not meet certain criteria. Build descriptors for the ones that remain. Pass these descriptors onto a classifier, which determines if the blob is a vehicle or not. The probability of detection is the probability that if a vehicle is present in the image, is visible, and un-occluded, then it will be detected by the JVD algorithm. In order to estimate this probability, eight sequences were ground-truthed from the RCTA (Robotics Collaborative Technology Alliances) program, totaling over 4,000 frames with 15 unique vehicles. Since these vehicles were observed at varying ranges, one is able to find the probability of detection as a function of range. At the time of this reporting, the JVD algorithm was tuned to perform best at cars seen from the front, rear, or either side, and perform poorly on vehicles seen from oblique angles.

On an efficient and effective intelligent transportation system (ITS) safety and traffic efficiency application with corresponding driver behavior

NASA Astrophysics Data System (ADS)

Ekedebe, Nnanna; Yu, Wei; Lu, Chao

2015-06-01

Driver distraction could result in safety compromises attributable to distractions from in-vehicle equipment usage [1]. The effective design of driver-vehicle interfaces (DVIs) and other human-machine interfaces (HMIs) together with their usability, and accessibility while driving become important [2]. Driving distractions can be classified as: visual distractions (any activity that takes your eyes away from the road), cognitive distraction (any activity that takes your mind away from the course of driving), and manual distractions (any activity that takes your hands away from the steering wheel [2]). Besides, multitasking during driving is a distractive activity that can increase the risks of vehicular accidents. To study the driver's behaviors on the safety of transportation system, using an in-vehicle driver notification application, we examined the effects of increasing driver distraction levels on the evaluation metrics of traffic efficiency and safety by using two types of driver models: young drivers (ages 16-25 years) and middle-age drivers (ages 30-45 years). Our evaluation data demonstrates that as a drivers distraction level is increased, less heed is given to change route directives from the in-vehicle on-board unit (OBU) using textual, visual, audio, and haptic notifications. Interestingly, middle-age drivers proved more effective/resilient in mitigating the negative effects of driver distraction over young drivers [2].

Man-rating of a launch vehicle

NASA Astrophysics Data System (ADS)

Soeffker, D.

Analysis techniques for hazard identification, classification, and control, developed for Spacelab, are presented. Hazards were classified as catastrophic (leading to crew or vehicle loss) critical (could lead to serious injury or damage) and controlled (counteracted by design). All nonmetallic materials were rated for flammability in oxygen enriched atmospheres, toxic offgassing, and odor. Any element with less than 200 mission capability was rated life limited.

Traffic collisions between electric mobility devices (wheelchairs) and motor vehicles: Accidents, hubris, or self-destructive behavior?

PubMed

LaBan, Myron M; Nabity, Thomas S

2010-07-01

This study had its genesis in a personally observed collision between a motor vehicle and a motorized wheelchair (electric mobility device) on a busy street in the middle of the block at an unmarked crossing. To the observer, at the time, this appeared to be a suicidal act. This investigation was initiated to both delineate the number of these crashes nationally and understand this phenomena as a potentially planned act of self-destruction. An initial survey of police reports was immediately frustrated by an inability to separate motor vehicle and electric mobility device collisions from the much larger group that involved ambulatory citizens because both types were classified together as "pedestrian" accidents. Instead, the search engine NexisLexis was used to identify 107 newspaper articles each of which described a motor vehicle and electric mobility device accident. In the motor vehicle and electric mobility device collisions, men predominated women (3:1 ratio) with an average age of 56 yrs. Sixty of these accidents were fatal. Ninety-four percent involved an electric mobility device and 6% a manual wheelchair. In 50% of the cases, the motor vehicle was a truck, van, or sport utility vehicle. Fifty percent occurred at dusk or dawn or at night. The electric mobility device occupant was cited as the guilty party in 39% of the cases and the driver of the motor vehicle in 27%. Twenty percent were unwitnessed hit-and-run accidents, whereas "no fault" was found in 8% of the cases. Although many accidents do happen by chance, when an electric mobility device operator openly challenges busy traffic by attempting to traverse it in the middle of the block at an unmarked crossing, predisposing psychosocial factors must also be considered. Hubris or premeditated self-destructive behavior or both need to be explored as preeminent issues with reference to the prodromal of the "accident process."

41 CFR 102-34.155 - What are the types of motor vehicle identification exemptions?

Code of Federal Regulations, 2011 CFR

2011-01-01

... motor vehicle identification exemptions? 102-34.155 Section 102-34.155 Public Contracts and Property... PROPERTY 34-MOTOR VEHICLE MANAGEMENT Identifying and Registering Motor Vehicles Identification Exemptions § 102-34.155 What are the types of motor vehicle identification exemptions? The types of motor vehicle...

41 CFR 102-34.155 - What are the types of motor vehicle identification exemptions?

Code of Federal Regulations, 2010 CFR

2010-07-01

... motor vehicle identification exemptions? 102-34.155 Section 102-34.155 Public Contracts and Property... PROPERTY 34-MOTOR VEHICLE MANAGEMENT Identifying and Registering Motor Vehicles Identification Exemptions § 102-34.155 What are the types of motor vehicle identification exemptions? The types of motor vehicle...

41 CFR 102-34.155 - What are the types of motor vehicle identification exemptions?

Code of Federal Regulations, 2014 CFR

2014-01-01

... motor vehicle identification exemptions? 102-34.155 Section 102-34.155 Public Contracts and Property... PROPERTY 34-MOTOR VEHICLE MANAGEMENT Identifying and Registering Motor Vehicles Identification Exemptions § 102-34.155 What are the types of motor vehicle identification exemptions? The types of motor vehicle...

41 CFR 102-34.155 - What are the types of motor vehicle identification exemptions?

Code of Federal Regulations, 2013 CFR

2013-07-01

... motor vehicle identification exemptions? 102-34.155 Section 102-34.155 Public Contracts and Property... PROPERTY 34-MOTOR VEHICLE MANAGEMENT Identifying and Registering Motor Vehicles Identification Exemptions § 102-34.155 What are the types of motor vehicle identification exemptions? The types of motor vehicle...

41 CFR 102-34.155 - What are the types of motor vehicle identification exemptions?

Code of Federal Regulations, 2012 CFR

2012-01-01

... motor vehicle identification exemptions? 102-34.155 Section 102-34.155 Public Contracts and Property... PROPERTY 34-MOTOR VEHICLE MANAGEMENT Identifying and Registering Motor Vehicles Identification Exemptions § 102-34.155 What are the types of motor vehicle identification exemptions? The types of motor vehicle...

Survey on the novel hybrid aquatic-aerial amphibious aircraft: Aquatic unmanned aerial vehicle (AquaUAV)

NASA Astrophysics Data System (ADS)

Yang, Xingbang; Wang, Tianmiao; Liang, Jianhong; Yao, Guocai; Liu, Miao

2015-04-01

The aquatic unmanned aerial vehicle (AquaUAV), a kind of vehicle that can operate both in the air and the water, has been regarded as a new breakthrough to broaden the application scenario of UAV. Wide application prospects in military and civil field are more than bright, therefore many institutions have focused on the development of such a vehicle. However, due to the significant difference of the physical properties between the air and the water, it is rather difficult to design a fully-featured AquaUAV. Until now, majority of partially-featured AquaUAVs have been developed and used to verify the feasibility of an aquatic-aerial vehicle. In the present work, we classify the current partially-featured AquaUAV into three categories from the scope of the whole UAV field, i.e., the seaplane UAV, the submarine-launched UAV, and the submersible UAV. Then the recent advancements and common characteristics of the three kinds of AquaUAVs are reviewed in detail respectively. Then the applications of bionics in the design of AquaUAV, the transition mode between the air and the water, the morphing wing structure for air-water adaptation, and the power source and the propulsion type are summarized and discussed. The tradeoff analyses for different transition methods between the air and the water are presented. Furthermore, it indicates that applying the bionics into the design and development of the AquaUAV will be essential and significant. Finally, the significant technical challenges for the AquaUAV to change from a conception to a practical prototype are indicated.

Correlation parameters for the study of leeside heating on a lifting body at hypersonic speeds

NASA Technical Reports Server (NTRS)

Vidal, R. J.

1974-01-01

Leeside heating was studied with the aim of gaining some insight into: (1) the magnitude of the leeside heating rates and (2) the methods to be used to extrapolate wind tunnel leeside heating rates to the full scale flight condition. This study was based on existing experimental data obtained in a hypersonic shock tunnel on lifting body configurations that are typical of shuttle orbiter vehicles. Heat transfer was first measured on the windward side to determine the boundary layer type. Then the leeside heating was investigated with the classified boundary layer. Correlation data are given on the windward turbulent boundary layer, the windward laminar boundary layer, and the leeside surfaces.

Novelty Detection Classifiers in Weed Mapping: Silybum marianum Detection on UAV Multispectral Images.

PubMed

Alexandridis, Thomas K; Tamouridou, Afroditi Alexandra; Pantazi, Xanthoula Eirini; Lagopodi, Anastasia L; Kashefi, Javid; Ovakoglou, Georgios; Polychronos, Vassilios; Moshou, Dimitrios

2017-09-01

In the present study, the detection and mapping of Silybum marianum (L.) Gaertn. weed using novelty detection classifiers is reported. A multispectral camera (green-red-NIR) on board a fixed wing unmanned aerial vehicle (UAV) was employed for obtaining high-resolution images. Four novelty detection classifiers were used to identify S. marianum between other vegetation in a field. The classifiers were One Class Support Vector Machine (OC-SVM), One Class Self-Organizing Maps (OC-SOM), Autoencoders and One Class Principal Component Analysis (OC-PCA). As input features to the novelty detection classifiers, the three spectral bands and texture were used. The S. marianum identification accuracy using OC-SVM reached an overall accuracy of 96%. The results show the feasibility of effective S. marianum mapping by means of novelty detection classifiers acting on multispectral UAV imagery.

Unmanned Ground Vehicle

DTIC Science & Technology

2001-11-01

Systems ( JAUGS ). JAUGS is a JRP technology initiative under the cognizance of the Aviation and Missile Command Research, Development and Engineering Center...AMRDEC). The JAUGS focus is on developing a high-level command and control architecture for UGVs. As defined in the JRP Glossary, “ JAUGS is an upper...vehicle platforms and missions. JAUGS uses the Society of Automotive Engineers Generic Open Architecture framework to classify UGV interfaces and

Vehicle Engine Classification Using Spectral Tone-Pitch Vibration Indexing and Neural Network*

PubMed Central

Wei, Jie; Vongsy, Karmon; Mendoza-Schrock, Olga; Liu, Chi-Him

2015-01-01

As a non-invasive and remote sensor, the Laser Doppler Vibrometer (LDV) has found a broad spectrum of applications in various areas such as civil engineering, biomedical engineering, and even security and restoration within art museums. LDV is an ideal sensor to detect threats earlier and provide better protection to society, which is of utmost importance to military and law enforcement institutions. However, the use of LDV in situational surveillance, in particular vehicle classification, is still in its infancy due to the lack of systematic investigations on its behavioral properties. In this work, as a result of the pilot project initiated by Air Force Research Laboratory, the innate features of LDV data from many vehicles are examined, beginning with an investigation of feature differences compared to human speech signals. A spectral tone-pitch vibration indexing scheme is developed to capture the engine’s periodic vibrations and the associated fundamental frequencies over the vehicles’ surface. A two-layer feed-forward neural network with 20 intermediate neurons is employed to classify vehicles’ engines based on their spectral tone-pitch indices. The classification results using the proposed approach over the complete LDV dataset collected by the project are exceedingly encouraging; consistently higher than 96% accuracies are attained for all four types of engines collected from this project. PMID:26788417

Anomaly detection driven active learning for identifying suspicious tracks and events in WAMI video

NASA Astrophysics Data System (ADS)

Miller, David J.; Natraj, Aditya; Hockenbury, Ryler; Dunn, Katherine; Sheffler, Michael; Sullivan, Kevin

2012-06-01

We describe a comprehensive system for learning to identify suspicious vehicle tracks from wide-area motion (WAMI) video. First, since the road network for the scene of interest is assumed unknown, agglomerative hierarchical clustering is applied to all spatial vehicle measurements, resulting in spatial cells that largely capture individual road segments. Next, for each track, both at the cell (speed, acceleration, azimuth) and track (range, total distance, duration) levels, extreme value feature statistics are both computed and aggregated, to form summary (p-value based) anomaly statistics for each track. Here, to fairly evaluate tracks that travel across different numbers of spatial cells, for each cell-level feature type, a single (most extreme) statistic is chosen, over all cells traveled. Finally, a novel active learning paradigm, applied to a (logistic regression) track classifier, is invoked to learn to distinguish suspicious from merely anomalous tracks, starting from anomaly-ranked track prioritization, with ground-truth labeling by a human operator. This system has been applied to WAMI video data (ARGUS), with the tracks automatically extracted by a system developed in-house at Toyon Research Corporation. Our system gives promising preliminary results in highly ranking as suspicious aerial vehicles, dismounts, and traffic violators, and in learning which features are most indicative of suspicious tracks.

Application of lifting wavelet and random forest in compound fault diagnosis of gearbox

NASA Astrophysics Data System (ADS)

Chen, Tang; Cui, Yulian; Feng, Fuzhou; Wu, Chunzhi

2018-03-01

Aiming at the weakness of compound fault characteristic signals of a gearbox of an armored vehicle and difficult to identify fault types, a fault diagnosis method based on lifting wavelet and random forest is proposed. First of all, this method uses the lifting wavelet transform to decompose the original vibration signal in multi-layers, reconstructs the multi-layer low-frequency and high-frequency components obtained by the decomposition to get multiple component signals. Then the time-domain feature parameters are obtained for each component signal to form multiple feature vectors, which is input into the random forest pattern recognition classifier to determine the compound fault type. Finally, a variety of compound fault data of the gearbox fault analog test platform are verified, the results show that the recognition accuracy of the fault diagnosis method combined with the lifting wavelet and the random forest is up to 99.99%.

Incidence, Patterns, and Factors Predicting Mortality of Abdominal Injuries in Trauma Patients

PubMed Central

Gad, Mohammad A; Saber, Aly; Farrag, Shereif; Shams, Mohamed E; Ellabban, Goda M

2012-01-01

Background: Abdominal trauma is a major public health problem for all nations and all socioeconomic strata. Aim: This study was designed to determine the incidence and patterns of abdominal injuries in trauma patients. Materials and Methods: We classified and identified the incidence and subtype of abdominal injuries and associated trauma, and identified variables related to morbidity and mortality. Results: Abdominal trauma was present in 248 of 300 cases; 172 patients with blunt abdominal trauma and 76 with penetrating. The most frequent type of abdominal trauma was blunt trauma; its most common cause was motor vehicle accident. Among patients with penetrating abdominal trauma, the most common cause was stabbing. Most abdominal trauma patients presented with other injuries, especially patients with blunt abdominal trauma. Mortality was higher among penetrating abdominal trauma patients. Conclusions: Type of abdominal trauma, associated injuries, and Revised Trauma Score are independent risk factors for mortality in abdominal trauma patients. PMID:22454826

Alternative Fuels Data Center: Maps and Data

Science.gov Websites

vehicles with unidentified fuel types. Data consists of registered vehicles in operation in the United fuel types with small populations, such as methanol and hydrogen vehicles. See relative vehicle completed a conversion. "undefined" values are vehicles with unidentified fuel types. Data

46 CFR 108.187 - Ventilation for brush type electric motors in classified spaces.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Ventilation for brush type electric motors in classified... Ventilation for brush type electric motors in classified spaces. Ventilation for brush type electric motors in classified locations must meet N.F.P.A. 496-1974 “Standard for Purged and Pressurized Enclosures for...

Bayes classifiers for imbalanced traffic accidents datasets.

PubMed

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.

Fusing Laser Reflectance and Image Data for Terrain Classification for Small Autonomous Robots

DTIC Science & Technology

2014-12-01

limit us to low power, lightweight sensors , and a maximum range of approximately 5 meters. Contrast these robot characteristics to typical terrain...classifi- cation work which uses large autonomous ground vehicles with sensors mounted high above the ground. Terrain classification for small autonomous...into predefined classes [10], [11]. However, wheeled vehicles offer the ability to use non-traditional sensors such as vibration sensors [12] and

Supervised Learning Applied to Air Traffic Trajectory Classification

NASA Technical Reports Server (NTRS)

Bosson, Christabelle S.; Nikoleris, Tasos

2018-01-01

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Implementation and performance evaluation of acoustic denoising algorithms for UAV

NASA Astrophysics Data System (ADS)

Chowdhury, Ahmed Sony Kamal

Unmanned Aerial Vehicles (UAVs) have become popular alternative for wildlife monitoring and border surveillance applications. Elimination of the UAV's background noise and classifying the target audio signal effectively are still a major challenge. The main goal of this thesis is to remove UAV's background noise by means of acoustic denoising techniques. Existing denoising algorithms, such as Adaptive Least Mean Square (LMS), Wavelet Denoising, Time-Frequency Block Thresholding, and Wiener Filter, were implemented and their performance evaluated. The denoising algorithms were evaluated for average Signal to Noise Ratio (SNR), Segmental SNR (SSNR), Log Likelihood Ratio (LLR), and Log Spectral Distance (LSD) metrics. To evaluate the effectiveness of the denoising algorithms on classification of target audio, we implemented Support Vector Machine (SVM) and Naive Bayes classification algorithms. Simulation results demonstrate that LMS and Discrete Wavelet Transform (DWT) denoising algorithm offered superior performance than other algorithms. Finally, we implemented the LMS and DWT algorithms on a DSP board for hardware evaluation. Experimental results showed that LMS algorithm's performance is robust compared to DWT for various noise types to classify target audio signals.

Deep convolutional neural network for classifying Fusarium wilt of radish from unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Ha, Jin Gwan; Moon, Hyeonjoon; Kwak, Jin Tae; Hassan, Syed Ibrahim; Dang, Minh; Lee, O. New; Park, Han Yong

2017-10-01

Recently, unmanned aerial vehicles (UAVs) have gained much attention. In particular, there is a growing interest in utilizing UAVs for agricultural applications such as crop monitoring and management. We propose a computerized system that is capable of detecting Fusarium wilt of radish with high accuracy. The system adopts computer vision and machine learning techniques, including deep learning, to process the images captured by UAVs at low altitudes and to identify the infected radish. The whole radish field is first segmented into three distinctive regions (radish, bare ground, and mulching film) via a softmax classifier and K-means clustering. Then, the identified radish regions are further classified into healthy radish and Fusarium wilt of radish using a deep convolutional neural network (CNN). In identifying radish, bare ground, and mulching film from a radish field, we achieved an accuracy of ≥97.4%. In detecting Fusarium wilt of radish, the CNN obtained an accuracy of 93.3%. It also outperformed the standard machine learning algorithm, obtaining 82.9% accuracy. Therefore, UAVs equipped with computational techniques are promising tools for improving the quality and efficiency of agriculture today.

Recognizing pedestrian's unsafe behaviors in far-infrared imagery at night

NASA Astrophysics Data System (ADS)

Lee, Eun Ju; Ko, Byoung Chul; Nam, Jae-Yeal

2016-05-01

Pedestrian behavior recognition is important work for early accident prevention in advanced driver assistance system (ADAS). In particular, because most pedestrian-vehicle crashes are occurred from late of night to early of dawn, our study focus on recognizing unsafe behavior of pedestrians using thermal image captured from moving vehicle at night. For recognizing unsafe behavior, this study uses convolutional neural network (CNN) which shows high quality of recognition performance. However, because traditional CNN requires the very expensive training time and memory, we design the light CNN consisted of two convolutional layers and two subsampling layers for real-time processing of vehicle applications. In addition, we combine light CNN with boosted random forest (Boosted RF) classifier so that the output of CNN is not fully connected with the classifier but randomly connected with Boosted random forest. We named this CNN as randomly connected CNN (RC-CNN). The proposed method was successfully applied to the pedestrian unsafe behavior (PUB) dataset captured from far-infrared camera at night and its behavior recognition accuracy is confirmed to be higher than that of some algorithms related to CNNs, with a shorter processing time.

Formulation of multifunctional oil-in-water nanosized emulsions for active and passive targeting of drugs to otherwise inaccessible internal organs of the human body.

PubMed

Tamilvanan, Shunmugaperumal

2009-10-20

Oil-in-water (o/w) type nanosized emulsions (NE) have been widely investigated as vehicles/carrier for the formulation and delivery of drugs with a broad range of applications. A comprehensive summary is presented on how to formulate the multifunctional o/w NE for active and passive targeting of drugs to otherwise inaccessible internal organs of the human body. The NE is classified into three generations based on its development over the last couple of decades to make ultimately a better colloidal carrier for a target site within the internal and external organs/parts of the body, thus allowing site-specific drug delivery and/or enhanced drug absorption. The third generation NE has tremendous application for drug absorption enhancement and for 'ferrying' compounds across cell membranes in comparison to its first and second generation counterparts. Furthermore, the third generation NE provides an interesting opportunity for use as drug delivery vehicles for numerous therapeutics that can range in size from small molecules to macromolecules.

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

PubMed Central

Gonzalez, Luis F.; Montes, Glen A.; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J.

2016-01-01

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification. PMID:26784196

Eddy-Current Sensors with Asymmetrical Point Spread Function

PubMed Central

Gajda, Janusz; Stencel, Marek

2016-01-01

This paper concerns a special type of eddy-current sensor in the form of inductive loops. Such sensors are applied in the measuring systems classifying road vehicles. They usually have a rectangular shape with dimensions of 1 × 2 m, and are installed under the surface of the traffic lane. The wide Point Spread Function (PSF) of such sensors causes the information on chassis geometry, contained in the measurement signal, to be strongly averaged. This significantly limits the effectiveness of the vehicle classification. Restoration of the chassis shape, by solving the inverse problem (deconvolution), is also difficult due to the fact that it is ill-conditioned. An original approach to solving this problem is presented in this paper. It is a hardware-based solution and involves the use of inductive loops with an asymmetrical PSF. Laboratory experiments and simulation tests, conducted with models of an inductive loop, confirmed the effectiveness of the proposed solution. In this case, the principle applies that the higher the level of sensor spatial asymmetry, the greater the effectiveness of the deconvolution algorithm. PMID:27782033

Difference in rural and urban driver-injury severities in highway-rail grade crossing accidents.

PubMed

Hao, Wei; Kamga, Camille

2017-06-01

Based on the Federal Railway Administration (FRA) database, there were 25,945 highway-rail crossing accidents in the United States between 2002 and 2011. With an extensive research, analysis results showed that there were substantial differences between rural and urban areas at highway-rail grade crossings. However, there is no published study specific on driver's injury severity at highway-rail grade crossings classified by area types. Using an ordered probit modelling approach, the study explores the determinants of driver-injury severity at rural highway-rail grade crossings compared with urban highway-rail grade crossings. The analysis found that motor vehicle driver's injury level at rural highway-rail grade crossing is extremely higher than urban area. Compared to collisions at urban area, collisions happened at rural area tend to result in more severe injuries. These crashes were more prevalent if vehicle drivers are driving at a high speed or the oncoming trains are high-speed. Moreover, highway-rail grade crossing accidents were more likely to occur at rural area without pavement and lighting.

Eddy-Current Sensors with Asymmetrical Point Spread Function.

PubMed

Gajda, Janusz; Stencel, Marek

2016-10-04

This paper concerns a special type of eddy-current sensor in the form of inductive loops. Such sensors are applied in the measuring systems classifying road vehicles. They usually have a rectangular shape with dimensions of 1 × 2 m, and are installed under the surface of the traffic lane. The wide Point Spread Function (PSF) of such sensors causes the information on chassis geometry, contained in the measurement signal, to be strongly averaged. This significantly limits the effectiveness of the vehicle classification. Restoration of the chassis shape, by solving the inverse problem (deconvolution), is also difficult due to the fact that it is ill-conditioned. An original approach to solving this problem is presented in this paper. It is a hardware-based solution and involves the use of inductive loops with an asymmetrical PSF. Laboratory experiments and simulation tests, conducted with models of an inductive loop, confirmed the effectiveness of the proposed solution. In this case, the principle applies that the higher the level of sensor spatial asymmetry, the greater the effectiveness of the deconvolution algorithm.

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

PubMed

Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

2016-01-14

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Intelligent vehicle initiative : business plan

DOT National Transportation Integrated Search

1996-06-01

This report identifies specific intermodal performance measures developed by 15 State departments of transportation. The performance measures are classified by goals and analyzed by frequency of use. The report discusses the role of performance measu...

Rural ITS user needs

DOT National Transportation Integrated Search

1999-07-01

The Truck Characteristics Study seeks to develop a better understanding of the physical characteristics of the national truck fleet. With automatic vehicle classifiers (AVC) and weigh-in-motion devices (WIM), only axle spacing and weight information ...

Accurate determination of surface reference data in digital photographs in ice-free surfaces of Maritime Antarctica.

PubMed

Pina, Pedro; Vieira, Gonçalo; Bandeira, Lourenço; Mora, Carla

2016-12-15

The ice-free areas of Maritime Antarctica show complex mosaics of surface covers, with wide patches of diverse bare soils and rock, together with various vegetation communities dominated by lichens and mosses. The microscale variability is difficult to characterize and quantify, but is essential for ground-truthing and for defining classifiers for large areas using, for example high resolution satellite imagery, or even ultra-high resolution unmanned aerial vehicle (UAV) imagery. The main objective of this paper is to verify the ability and robustness of an automated approach to discriminate the variety of surface types in digital photographs acquired at ground level in ice-free regions of Maritime Antarctica. The proposed method is based on an object-based classification procedure built in two main steps: first, on the automated delineation of homogeneous regions (the objects) of the images through the watershed transform with adequate filtering to avoid an over-segmentation, and second, on labelling each identified object with a supervised decision classifier trained with samples of representative objects of ice-free surface types (bare rock, bare soil, moss and lichen formations). The method is evaluated with images acquired in summer campaigns in Fildes and Barton peninsulas (King George Island, South Shetlands). The best performances for the datasets of the two peninsulas are achieved with a SVM classifier with overall accuracies of about 92% and kappa values around 0.89. The excellent performances allow validating the adequacy of the approach for obtaining accurate surface reference data at the complete pixel scale (sub-metric) of current very high resolution (VHR) satellite images, instead of a common single point sampling. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparison of real-world and certification emission rates for light duty gasoline vehicles.

PubMed

Khan, Tanzila; Frey, H Christopher

2018-05-01

U.S. light duty vehicles are subject to the U.S. Environmental Protection Agency (EPA) emission standards. Emission compliance is determined by certification testing of selected emissions from representative vehicles on standard driving cycles using chassis dynamometers. Test results are also used in many emission inventories. The dynamometer based emission rates are adjusted to provide the certification levels (CL), which must be lower than the standards for compliance. Although standard driving cycles are based on specific observations of real-world driving, they are not necessarily real-world representative. A systematic comparison of the real-world emission rates of U.S. light duty gasoline vehicles (LDGVs) versus CL, and emission standards has not been previously reported. The purpose of this work is to compare regulatory limits (both CLs and emission standards) and the real-world emissions of LDGVs. The sensitivity of the comparisons to cold start emission was assessed. Portable Emission Measurement Systems (PEMS) were used to measure hot stabilized exhaust emissions of 122 LDGVs on a specified 110 mile test route. Cold start emissions were measured with PEMS for a selected vehicle sample of 32 vehicles. Emissions were measured for carbon dioxide (CO 2 ), carbon monoxide (CO), hydrocarbons (HC) and nitrogen oxides (NO x ). For each vehicle, a Vehicle Specific Power (VSP) modal emission rate model was developed. The VSP modal rates were weighted by the standard driving cycles and real-world driving cycles to estimate the respective cycle average emission rates (CAERs). Measured vehicles were matched with certification test vehicles for comparison. For systematic trends in comparison, vehicles were classified into four groups based on the Tier 1 and Tier 2 emission regulation, and the vehicle type such as passenger car and passenger truck. Depending on the cycle-pollutant and the vehicle groups, hot stabilized CAERs are on average either statistically significantly higher than or significantly not different from the CLs, with the exception of CO on the US06 cycle, for which real-world rates are lower than CLs. Compared to the emission standards, hot stabilized CAERs are on average significantly lower. However, comparisons of CAERs and standards are sensitive to cold start emissions. For some combinations of pollutants and vehicle groups, cold start inclusive CAERs are higher than the corresponding CLs and as high as the standards. The CLs, which are based on standard driving cycles, tend to underestimate real-world emission rates. Therefore, emission inventory estimates using certification test results are potentially underestimated. Copyright © 2017 Elsevier B.V. All rights reserved.

14 CFR 420.19 - Launch site location review-general.

Code of Federal Regulations, 2010 CFR

2010-01-01

... site, at least one type of expendable or reusable launch vehicle can be flown from the launch point... × 10−6). (2) Types of launch vehicles include orbital expendable launch vehicles, guided sub-orbital expendable launch vehicles, unguided sub-orbital expendable launch vehicles, and reusable launch vehicles...

Naturalistic Cycling Study: Identifying Risk Factors for On-Road Commuter Cyclists

PubMed Central

Johnson, Marilyn; Charlton, Judith; Oxley, Jennifer; Newstead, Stuart

2010-01-01

The study aim was to identify risk factors for collisions/near-collisions involving on-road commuter cyclists and drivers. A naturalistic cycling study was conducted in Melbourne, Australia, with cyclists wearing helmet-mounted video cameras. Video recordings captured cyclists’ perspective of the road and traffic behaviours including head checks, reactions and manoeuvres. The 100-car naturalistic driving study analysis technique was adapted for data analysis and events were classified by severity: collision, near-collision and incident. Participants were adult cyclists and each filmed 12 hours of commuter cycling trips over a 4-week period. In total, 127 hours and 38 minutes were analysed for 13 participants, 54 events were identified: 2 collisions, 6 near-collisions and 46 incidents. Prior to events, 88.9% of cyclists travelled in a safe/legal manner. Sideswipe was the most frequent event type (40.7%). Most events occurred at an intersection/intersection-related location (70.3%). The vehicle driver was judged at fault in the majority of events (87.0%) and no post-event driver reaction was observed (83.3%). Cross tabulations revealed significant associations between event severity and: cyclist reaction, cyclist post-event manoeuvre, pre-event driver behaviour, other vehicle involved, driver reaction, visual obstruction, cyclist head check (left), event type and vehicle location (p<0.05). Frequent head checks suggest cyclists had high situational awareness and their reactive behaviour to driver actions led to successful avoidance of collisions/near-collisions. Strategies to improve driver awareness of on-road cyclists and to indicate early before turning/changing lanes when sharing the roadway with cyclists are discussed. Findings will contribute to the development of effective countermeasures to reduce cyclist trauma. PMID:21050610

Naturalistic cycling study: identifying risk factors for on-road commuter cyclists.

PubMed

Johnson, Marilyn; Charlton, Judith; Oxley, Jennifer; Newstead, Stuart

2010-01-01

The study aim was to identify risk factors for collisions/near-collisions involving on-road commuter cyclists and drivers. A naturalistic cycling study was conducted in Melbourne, Australia, with cyclists wearing helmet-mounted video cameras. Video recordings captured cyclists' perspective of the road and traffic behaviours including head checks, reactions and manoeuvres. The 100-car naturalistic driving study analysis technique was adapted for data analysis and events were classified by severity: collision, near-collision and incident. Participants were adult cyclists and each filmed 12 hours of commuter cycling trips over a 4-week period. In total, 127 hours and 38 minutes were analysed for 13 participants, 54 events were identified: 2 collisions, 6 near-collisions and 46 incidents. Prior to events, 88.9% of cyclists travelled in a safe/legal manner. Sideswipe was the most frequent event type (40.7%). Most events occurred at an intersection/intersection-related location (70.3%). The vehicle driver was judged at fault in the majority of events (87.0%) and no post-event driver reaction was observed (83.3%). Cross tabulations revealed significant associations between event severity and: cyclist reaction, cyclist post-event manoeuvre, pre-event driver behaviour, other vehicle involved, driver reaction, visual obstruction, cyclist head check (left), event type and vehicle location (p<0.05). Frequent head checks suggest cyclists had high situational awareness and their reactive behaviour to driver actions led to successful avoidance of collisions/near-collisions. Strategies to improve driver awareness of on-road cyclists and to indicate early before turning/changing lanes when sharing the roadway with cyclists are discussed. Findings will contribute to the development of effective countermeasures to reduce cyclist trauma.

Mobile Information Systems Impact Study

DOT National Transportation Integrated Search

1988-08-01

THE REPORT PRESENTS A REVIEW OF THE STATE-OF-THE-ART OF IN-VEHICLE NAVIGATION AND MOBILE COMMUNICATIONS TECHNIQUES AND EQUIPMENT. A FEATURES MATRIX IS USED TO CLASSIFY THE EQUIPMENT IN TERMS OF INFRASTRUCTURE RELATIONSHIP, NAVIGATION TECHNOLOGY, SYST...

Selection of comparison crash types for quasi-induced exposure risk estimation.

PubMed

Keall, Michael; Newstead, Stuart

2009-03-01

The objective of this study was to find a comparison crash type that best represented exposure on the road and to identify situations where the induced exposure risk estimates were likely to be biased. Counts of crash involvements were compared with distance driven estimates derived from a register of licensed motor vehicles to identify the most appropriate comparison crash type for induced exposure estimation, which is the crash type whose counts are best correlated with vehicle distance driven. The best sets of comparison crashes for disaggregations by driver age and gender and vehicle type were found to be multi-vehicle crashes in which the vehicle was damaged in the rear or multi-vehicle crashes in which the driver was adjudged to be not at fault. Likely bias of induced exposure risk estimates was identified, even for these best sets of comparison crashes, according to vehicle size (with large vehicles underrepresented) and owner age and gender (with young owners and female owners overrepresented). This research identified some important features of crash occurrence useful for making choices of comparison crash types when controlling for exposure. None of the crash types considered as comparison crashes performed perfectly. Even the crash types that seemed to best reflect exposure on the road still appeared to over- or underestimate distance driven according to owner age group, gender, and vehicle size.

An Investigation to Improve Classifier Accuracy for Myo Collected Data

DTIC Science & Technology

2017-02-01

distribution is unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT A naïve Bayes classifier trained with 1,360 samples from 17 volunteers performs at...movement data from 17 volunteers . Each volunteer performed 8 gestures (Freeze, Rally Point, Hurry Up, Down, Come, Stop, Line Abreast Formation, and Vehicle...line chart was plotted for each gesture’s feature (e.g., Pitch, xAcc) per user. All 10 recorded samples of a particular gesture for a single volunteer

40 CFR 86.1726-99 - Mileage and service accumulation; emission measurements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... of hybrid electric vehicles shall be conducted with the battery pack at the manufacturer's indicated... Type A hybrid electric vehicle, 75,000 miles for a Type B hybrid electric vehicle, and 100,000 miles for a Type C hybrid electric vehicle. (iv) Alternative durability plans may also be used if the...

Enhanced Vehicle Simulation Tool Enables Wider Array of Analyses | News |

Science.gov Websites

of vehicle types, including conventional vehicles, electric-drive vehicles, and fuel cell vehicles types," said NREL Senior Engineer Aaron Brooker. FASTSim facilitates large-scale evaluation of and on-road performance. Learn more about NREL's sustainable transportation research.

46 CFR 108.187 - Ventilation for brush type electric motors in classified spaces.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Ventilation for brush type electric motors in classified... Ventilation for brush type electric motors in classified spaces. Ventilation for brush type electric motors in... Electrical Equipment in Hazardous Locations”, except audible and visual alarms may be used if shutting down...

Vehicle response-based track geometry assessment using multi-body simulation

NASA Astrophysics Data System (ADS)

Kraft, Sönke; Causse, Julien; Coudert, Frédéric

2018-02-01

The assessment of the geometry of railway tracks is an indispensable requirement for safe rail traffic. Defects which represent a risk for the safety of the train have to be identified and the necessary measures taken. According to current standards, amplitude thresholds are applied to the track geometry parameters measured by recording cars. This geometry-based assessment has proved its value but suffers from the low correlation between the geometry parameters and the vehicle reactions. Experience shows that some defects leading to critical vehicle reactions are underestimated by this approach. The use of vehicle responses in the track geometry assessment process allows identifying critical defects and improving the maintenance operations. This work presents a vehicle response-based assessment method using multi-body simulation. The choice of the relevant operation conditions and the estimation of the simulation uncertainty are outlined. The defects are identified from exceedances of track geometry and vehicle response parameters. They are then classified using clustering methods and the correlation with vehicle response is analysed. The use of vehicle responses allows the detection of critical defects which are not identified from geometry parameters.

Meteorological conditions during the formation of ice on aircraft

NASA Technical Reports Server (NTRS)

Samuels, L T

1932-01-01

These are the results of a number of records recently secured from autographic meteorological instruments mounted on airplanes at times when ice formed. Ice is found to collect on an airplane only when the airplane is in some form of visible moisture, such as cloud, fog, mist, rain. etc., and the air temperature is within certain critical limits. Described here are the characteristics of clear ice and rime ice and the specific types of hazards they present to airplanes and lighter than air vehicles. The weather records are classified according to the two general types of formation (clear ice and rime) together with the respective temperatures, relative humidities, clouds, and elevations above ground at which formations occurred. This classification includes 108 cases where rime formed, 43 cases in which clear ice formed, and 4 cases when both rime and clear ice formed during the same flight. It is evident from the above figures that there was a preponderance of rime by the ratio of 2.5 to 1, while in only a few cases both types of ice formation occurred during the same flight.

Confidence level estimation in multi-target classification problems

NASA Astrophysics Data System (ADS)

Chang, Shi; Isaacs, Jason; Fu, Bo; Shin, Jaejeong; Zhu, Pingping; Ferrari, Silvia

2018-04-01

This paper presents an approach for estimating the confidence level in automatic multi-target classification performed by an imaging sensor on an unmanned vehicle. An automatic target recognition algorithm comprised of a deep convolutional neural network in series with a support vector machine classifier detects and classifies targets based on the image matrix. The joint posterior probability mass function of target class, features, and classification estimates is learned from labeled data, and recursively updated as additional images become available. Based on the learned joint probability mass function, the approach presented in this paper predicts the expected confidence level of future target classifications, prior to obtaining new images. The proposed approach is tested with a set of simulated sonar image data. The numerical results show that the estimated confidence level provides a close approximation to the actual confidence level value determined a posteriori, i.e. after the new image is obtained by the on-board sensor. Therefore, the expected confidence level function presented in this paper can be used to adaptively plan the path of the unmanned vehicle so as to optimize the expected confidence levels and ensure that all targets are classified with satisfactory confidence after the path is executed.

The Potential of AutoClass as an Asteroidal Data Mining Tool

NASA Astrophysics Data System (ADS)

Walker, Matthew; Ziffer, J.; Harvell, T.; Fernandez, Y. R.; Campins, H.

2011-05-01

AutoClass-C, an artificial intelligence program designed to classify large data sets, was developed by NASA to classify stars based upon their infrared colors. Wanting to investigate its ability to classify asteroidal data, we conducted a preliminary test to determine if it could accurately reproduce the Tholen taxonomy using the data from the Eight Color Asteroid Survey (ECAS). For our initial test, we limited ourselves to those asteroids belonging to S, C, or X classes, and to asteroids with a color difference error of less than +/- 0.05 magnitudes. Of those 406 asteroids, AutoClass was able to confidently classify 85%: identifying the remaining asteroids as belonging to more than one class. Of the 346 asteroids that AutoClass classified, all but 3 (<1%) were classified as they had been in the Tholen classification scheme. Inspired by our initial success, we reran AutoClass, this time including IRAS albedos and limiting the asteroids to those that had also been observed and classified in the Bus taxonomy. Of those 258 objects, AutoClass was able to classify 248 with greater than 75% certainty, and ranked albedo, not color, as the most influential factor. Interestingly, AutoClass consistently put P type objects in with the C class (there were 19 P types and 7 X types mixed in with the other 154 C types), and omitted P types from the group associated with the other X types (which had only one rogue B type in with its other 49 X-types). Autoclass classified the remaining classes with a high accuracy: placing one A and one CU type in with an otherwise perfect S group; placing three P type and one T type in an otherwise perfect D group; and placing the four remaining asteroids (V, A, R, and Q) into a class together.

19 CFR 115.63 - Application for approval.

Code of Federal Regulations, 2012 CFR

2012-04-01

... of the design type and the serial number of the vehicle in the type series manufacturer's number; and... Procedures for Approval of Road Vehicles by Design Type § 115.63 Application for approval. Each application by a manufacturer for certification of a road vehicle by design type must include: (a) Three copies...

19 CFR 115.63 - Application for approval.

Code of Federal Regulations, 2013 CFR

2013-04-01

... of the design type and the serial number of the vehicle in the type series manufacturer's number; and... Procedures for Approval of Road Vehicles by Design Type § 115.63 Application for approval. Each application by a manufacturer for certification of a road vehicle by design type must include: (a) Three copies...

19 CFR 115.63 - Application for approval.

Code of Federal Regulations, 2014 CFR

2014-04-01

... of the design type and the serial number of the vehicle in the type series manufacturer's number; and... Procedures for Approval of Road Vehicles by Design Type § 115.63 Application for approval. Each application by a manufacturer for certification of a road vehicle by design type must include: (a) Three copies...

19 CFR 115.63 - Application for approval.

Code of Federal Regulations, 2010 CFR

2010-04-01

... of the design type and the serial number of the vehicle in the type series manufacturer's number; and... Procedures for Approval of Road Vehicles by Design Type § 115.63 Application for approval. Each application by a manufacturer for certification of a road vehicle by design type must include: (a) Three copies...

19 CFR 115.63 - Application for approval.

Code of Federal Regulations, 2011 CFR

2011-04-01

... of the design type and the serial number of the vehicle in the type series manufacturer's number; and... Procedures for Approval of Road Vehicles by Design Type § 115.63 Application for approval. Each application by a manufacturer for certification of a road vehicle by design type must include: (a) Three copies...

Dependence of driving characteristics upon follower-leader combination

NASA Astrophysics Data System (ADS)

Nagahama, Akihito; Yanagisawa, Daichi; Nishinari, Katsuhiro

2017-10-01

The analysis of the microscopic view of mixed traffic offers a basis for resolving traffic jams which are inhomogeneous due to several types of vehicles. In this study, we research the dependence of driving characteristics upon vehicle order in a platoon. By focusing particularly upon the manner in which the driving characteristics of a follower are affected by both their own vehicle type and that of their leader, we measured the trajectories of platoons comprising two vehicles selected from motorcycles, passenger cars, and trucks on a test course. Analysis based on vehicle order showed that the vehicle types of both the leader and the follower as well as the leader's driving characteristics affected the velocity, acceleration, deceleration, operational delay of followers, and the distance gap between leaders and followers in different ways. In addition, we investigated the factors affecting driving characteristics by multiple regression analysis. We revealed that the operational delay and the maximum distance gap tend to be large when the length of leaders is large. Furthermore, as long as a follower can follow, we need not consider vehicle types among the parameters determining maximum velocity in car-following models. The vehicle types of the leader and the follower should be considered to determine maximum acceleration. When determining maximum deceleration, the vehicle types of the follower should be considered.

Development of car theft crime index in peninsular Malaysia

NASA Astrophysics Data System (ADS)

Zulkifli, Malina; Ismail, Noriszura; Razali, Ahmad Mahir; Kasim, Maznah Mat

2014-06-01

Vehicle theft is classified as property crime and is considered as the most frequently reported crime in Malaysia. The rising number of vehicle thefts requires proper control by relevant authorities, especially through planning and implementation of strategic and effective measures. Nevertheless, the effort to control this crime would be much easier if there is an indication or index which is more specific to vehicle theft. This study aims to build an index crime which is specific to vehicle theft. The development of vehicle theft index proposed in this study requires three main steps; the first involves identification of criteria related to vehicle theft, the second requires calculation of degrees of importance, or weighting criteria, which involves application of correlation and entropy methods, and the final involves building of vehicle theft index using method of linear combination, or weighted arithmetic average. The results show that the two methods used for determining weights of vehicle theft index are similar. Information generated from the results can be used as a primary source for local authorities to plan strategies for reduction of vehicle theft and for insurance companies to determine premium rates of automobile insurance.

Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

NASA Astrophysics Data System (ADS)

Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

2017-09-01

Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Transportation Modes Classification Using Sensors on Smartphones.

PubMed

Fang, Shih-Hau; Liao, Hao-Hsiang; Fei, Yu-Xiang; Chen, Kai-Hsiang; Huang, Jen-Wei; Lu, Yu-Ding; Tsao, Yu

2016-08-19

This paper investigates the transportation and vehicular modes classification by using big data from smartphone sensors. The three types of sensors used in this paper include the accelerometer, magnetometer, and gyroscope. This study proposes improved features and uses three machine learning algorithms including decision trees, K-nearest neighbor, and support vector machine to classify the user's transportation and vehicular modes. In the experiments, we discussed and compared the performance from different perspectives including the accuracy for both modes, the executive time, and the model size. Results show that the proposed features enhance the accuracy, in which the support vector machine provides the best performance in classification accuracy whereas it consumes the largest prediction time. This paper also investigates the vehicle classification mode and compares the results with that of the transportation modes.

Transportation Modes Classification Using Sensors on Smartphones

PubMed Central

Fang, Shih-Hau; Liao, Hao-Hsiang; Fei, Yu-Xiang; Chen, Kai-Hsiang; Huang, Jen-Wei; Lu, Yu-Ding; Tsao, Yu

2016-01-01

This paper investigates the transportation and vehicular modes classification by using big data from smartphone sensors. The three types of sensors used in this paper include the accelerometer, magnetometer, and gyroscope. This study proposes improved features and uses three machine learning algorithms including decision trees, K-nearest neighbor, and support vector machine to classify the user’s transportation and vehicular modes. In the experiments, we discussed and compared the performance from different perspectives including the accuracy for both modes, the executive time, and the model size. Results show that the proposed features enhance the accuracy, in which the support vector machine provides the best performance in classification accuracy whereas it consumes the largest prediction time. This paper also investigates the vehicle classification mode and compares the results with that of the transportation modes. PMID:27548182

Mobility Analyses of Standard- and High-Mobility Tactical Support Vehicles (HIMO Study)

DTIC Science & Technology

1976-02-01

l, APPENDIX G: PARTICIPANTS IN SCENARIO EXERCISES ... ....... Gl I ?S LIST OF TABLES Table Page I Summary of Vehicle Caracteristics and Some...15 1 :1010 2 :1111 Organid silts and clays ( plastic ) >7-30 0 11212 1 1 1313Peat (nou plastic ) _._>_3_0 0 .1414 Li Groups with Different Materiai in 0...diameter LL = Liquid limit PI - Plasticity index Drainage potential classified by occurrence of water table as follows: Class 0 Water table occurs at

Comparisons of Traffic Collisions between Expressways and Rural Roads in Truck Drivers.

PubMed

Lee, Sangbok; Jeong, Byung Yong

2016-03-01

Truck driving is known as one of the occupations with the highest accident rate. This study investigates the characteristics of traffic collisions according to road types (expressway and rural road). Classifying 267 accidents into expressway and rural road, we analyzed them based on driver characteristics (age, working experience, size of employment), time characteristics (day of accident, time, weather), and accident characteristics (accident causes, accident locations, accident types, driving conditions). When we compared the accidents by road conditions, no differences were found between the driver characteristics. However, from the accident characteristics, the injured person distributions were different by the road conditions. In particular, driving while drowsy is shown to be highly related with the accident characteristics. This study can be used as a guideline and a base line to develop a plan of action to prevent traffic accidents. It can also help to prepare formal regulations about a truck driver's vehicle maintenance and driving attitude for a precaution on road accidents.

Comparisons of Traffic Collisions between Expressways and Rural Roads in Truck Drivers

PubMed Central

Lee, Sangbok; Jeong, Byung Yong

2015-01-01

Background Truck driving is known as one of the occupations with the highest accident rate. This study investigates the characteristics of traffic collisions according to road types (expressway and rural road). Methods Classifying 267 accidents into expressway and rural road, we analyzed them based on driver characteristics (age, working experience, size of employment), time characteristics (day of accident, time, weather), and accident characteristics (accident causes, accident locations, accident types, driving conditions). Results When we compared the accidents by road conditions, no differences were found between the driver characteristics. However, from the accident characteristics, the injured person distributions were different by the road conditions. In particular, driving while drowsy is shown to be highly related with the accident characteristics. Conclusion This study can be used as a guideline and a base line to develop a plan of action to prevent traffic accidents. It can also help to prepare formal regulations about a truck driver's vehicle maintenance and driving attitude for a precaution on road accidents. PMID:27014489

49 CFR 571.219 - Standard No. 219; Windshield zone intrusion.

Code of Federal Regulations, 2012 CFR

2012-10-01

... forward control vehicles, walk-in van-type vehicles, or to open-body-type vehicles with fold-down or... tire-ground interface is in proportion to its GAWR. If the mass on any axle when the vehicle is loaded...

49 CFR 571.219 - Standard No. 219; Windshield zone intrusion.

Code of Federal Regulations, 2011 CFR

2011-10-01

... forward control vehicles, walk-in van-type vehicles, or to open-body-type vehicles with fold-down or... tire-ground interface is in proportion to its GAWR. If the mass on any axle when the vehicle is loaded...

49 CFR 571.219 - Standard No. 219; Windshield zone intrusion.

Code of Federal Regulations, 2013 CFR

2013-10-01

... forward control vehicles, walk-in van-type vehicles, or to open-body-type vehicles with fold-down or... tire-ground interface is in proportion to its GAWR. If the mass on any axle when the vehicle is loaded...

49 CFR 571.219 - Standard No. 219; Windshield zone intrusion.

Code of Federal Regulations, 2014 CFR

2014-10-01

... forward control vehicles, walk-in van-type vehicles, or to open-body-type vehicles with fold-down or... tire-ground interface is in proportion to its GAWR. If the mass on any axle when the vehicle is loaded...

Time-varying mixed logit model for vehicle merging behavior in work zone merging areas.

PubMed

Weng, Jinxian; Du, Gang; Li, Dan; Yu, Yao

2018-08-01

This study aims to develop a time-varying mixed logit model for the vehicle merging behavior in work zone merging areas during the merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. From the safety perspective, vehicle crash probability and severity between the merging vehicle and its surrounding vehicles are regarded as major factors influencing vehicle merging decisions. Model results show that the model with the use of vehicle crash risk probability and severity could provide higher prediction accuracy than previous models with the use of vehicle speeds and gap sizes. It is found that lead vehicle type, through lead vehicle type, through lag vehicle type, crash probability of the merging vehicle with respect to the through lag vehicle, crash severities of the merging vehicle with respect to the through lead and lag vehicles could exhibit time-varying effects on the merging behavior. One important finding is that the merging vehicle could become more and more aggressive in order to complete the merging maneuver as quickly as possible over the elapsed time, even if it has high vehicle crash risk with respect to the through lead and lag vehicles. Copyright © 2018 Elsevier Ltd. All rights reserved.

Application of the SNoW machine learning paradigm to a set of transportation imaging problems

NASA Astrophysics Data System (ADS)

Paul, Peter; Burry, Aaron M.; Wang, Yuheng; Kozitsky, Vladimir

2012-01-01

Machine learning methods have been successfully applied to image object classification problems where there is clear distinction between classes and where a comprehensive set of training samples and ground truth are readily available. The transportation domain is an area where machine learning methods are particularly applicable, since the classification problems typically have well defined class boundaries and, due to high traffic volumes in most applications, massive roadway data is available. Though these classes tend to be well defined, the particular image noises and variations can be challenging. Another challenge is the extremely high accuracy typically required in most traffic applications. Incorrect assignment of fines or tolls due to imaging mistakes is not acceptable in most applications. For the front seat vehicle occupancy detection problem, classification amounts to determining whether one face (driver only) or two faces (driver + passenger) are detected in the front seat of a vehicle on a roadway. For automatic license plate recognition, the classification problem is a type of optical character recognition problem encompassing multiple class classification. The SNoW machine learning classifier using local SMQT features is shown to be successful in these two transportation imaging applications.

Elevated production of NH4NO3 from the photochemical processing of vehicle exhaust: Implications for air quality in the Seoul Metropolitan Region

NASA Astrophysics Data System (ADS)

Link, Michael F.; Kim, Jounghwa; Park, Gyutae; Lee, Taehyoung; Park, Taehyun; Babar, Zaeem Bin; Sung, Kijae; Kim, Pilho; Kang, Seokwon; Kim, Jeong Soo; Choi, Yongjoo; Son, Jihawn; Lim, Ho-Jin; Farmer, Delphine K.

2017-05-01

A vehicle fleet representative of passenger vehicles driven in the Seoul Metropolitan Region was investigated for primary emissions and secondary chemistry. Exhaust was photochemically oxidized in a flow reactor to determine the ammonium nitrate (NH4NO3) aerosol formation potential from vehicles of gasoline, diesel and liquid petroleum gasoline (LPG) fuel types. Secondary formation of aerosol NH4NO3, was larger than primary emissions for all vehicle fuel types except diesel, for which negligible secondary NH4NO3 production was observed. Although diesel vehicles emitted more primary nitrogen oxides than other vehicle types, ammonia emitted from gasoline and liquid petroleum gasoline fuels types limited the secondary production of NH4NO3. The results suggest that gasoline and liquid petroleum gasoline vehicles with three-way catalysts could be an important source of ammonia for NH4NO3 aerosol formation in ammonia-limited environments, including the Seoul Metropolitan Region.

Categorization and Characterization of American Driving Conditions (Phase I)

DOT National Transportation Integrated Search

1978-11-01

The objectives of the study were: (1) to develop a multidimensional matrix as an analysis framework to classify travel of personal motor vehicles according to fuel consumption, (2) to identify and assess available information on travel and fuel consu...

Behavioral distinctions : the use of light-duty trucks and passenger cars

DOT National Transportation Integrated Search

2000-12-01

Pickup trucks, sport utility vehicles (SUVs), and minivans are classified as light duty trucks (LDTs) in the United States, resulting in a variety of regulatory protections. According to production and purchase trends, Americans have shifted toward a...

Wheelset curving guidance using H∞ control

NASA Astrophysics Data System (ADS)

Qazizadeh, Alireza; Stichel, Sebastian; Feyzmahdavian, Hamid Reza

2018-03-01

This study shows how to design an active suspension system for guidance of a rail vehicle wheelset in curve. The main focus of the study is on designing the controller and afterwards studying its effect on the wheel wear behaviour. The controller is designed based on the closed-loop transfer function shaping method and ? control strategy. The study discusses designing of the controller for both nominal and uncertain plants and considers both stability and performance. The designed controllers in Simulink are then applied to the vehicle model in Simpack to study the wheel wear behaviour in curve. The vehicle type selected for this study is a two-axle rail vehicle. This is because this type of vehicle is known to have very poor curving performance and high wheel wear. On the other hand, the relative simpler structure of this type of vehicle compared to bogie vehicles make it a more economic choice. Hence, equipping this type of vehicle with the active wheelset steering is believed to show high enough benefit to cost ratio to remain attractive to rail vehicle manufacturers and operators.

Comparison of Classification Methods for P300 Brain-Computer Interface on Disabled Subjects

PubMed Central

Manyakov, Nikolay V.; Chumerin, Nikolay; Combaz, Adrien; Van Hulle, Marc M.

2011-01-01

We report on tests with a mind typing paradigm based on a P300 brain-computer interface (BCI) on a group of amyotrophic lateral sclerosis (ALS), middle cerebral artery (MCA) stroke, and subarachnoid hemorrhage (SAH) patients, suffering from motor and speech disabilities. We investigate the achieved typing accuracy given the individual patient's disorder, and how it correlates with the type of classifier used. We considered 7 types of classifiers, linear as well as nonlinear ones, and found that, overall, one type of linear classifier yielded a higher classification accuracy. In addition to the selection of the classifier, we also suggest and discuss a number of recommendations to be considered when building a P300-based typing system for disabled subjects. PMID:21941530

Unsupervised learning of discriminative edge measures for vehicle matching between nonoverlapping cameras.

PubMed

Shan, Ying; Sawhney, Harpreet S; Kumar, Rakesh

2008-04-01

This paper proposes a novel unsupervised algorithm learning discriminative features in the context of matching road vehicles between two non-overlapping cameras. The matching problem is formulated as a same-different classification problem, which aims to compute the probability of vehicle images from two distinct cameras being from the same vehicle or different vehicle(s). We employ a novel measurement vector that consists of three independent edge-based measures and their associated robust measures computed from a pair of aligned vehicle edge maps. The weight of each measure is determined by an unsupervised learning algorithm that optimally separates the same-different classes in the combined measurement space. This is achieved with a weak classification algorithm that automatically collects representative samples from same-different classes, followed by a more discriminative classifier based on Fisher' s Linear Discriminants and Gibbs Sampling. The robustness of the match measures and the use of unsupervised discriminant analysis in the classification ensures that the proposed method performs consistently in the presence of missing/false features, temporally and spatially changing illumination conditions, and systematic misalignment caused by different camera configurations. Extensive experiments based on real data of over 200 vehicles at different times of day demonstrate promising results.

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

PubMed

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

Use and user patterns among Michigan licensed off-highway vehicles ownership types

Treesearch

Joel A. Lynch; Charles M. Nelson

2002-01-01

Conventional off-highway vehicles (OHVs) range from small personal vehicles, such as motorcycles and all terrain vehicles to full-size passenger vehicles such as four-wheel drive trucks. The market and general recreational use of OHVs has changed markedly over the past thirty years. While many studies of OHV enthusiasts generalize to all OHV types, little research has...

Economic analysis of a Japanese air pollution regulation : an optimal retirement problem under vehicle type regulation in the NOx-particulate matter law

DOT National Transportation Integrated Search

2008-06-01

This paper empirically examines the vehicle type regulation that was introduced under the : Automobile Nitrogen OxidesParticulate Matter Law to mitigate air pollution problems in Japanese metropolitan areas. The vehicle type regulation effectively...

[Life cycle assessment of the infrastructure for hydrogen sources of fuel cell vehicles].

PubMed

Feng, Wen; Wang, Shujuan; Ni, Weidou; Chen, Changhe

2003-05-01

In order to promote the application of life cycle assessment and provide references for China to make the project of infrastructure for hydrogen sources of fuel cell vehicles in the near future, 10 feasible plans of infrastructure for hydrogen sources of fuel cell vehicles were designed according to the current technologies of producing, storing and transporting hydrogen. Then life cycle assessment was used as a tool to evaluate the environmental performances of the 10 plans. The standard indexes of classified environmental impacts of every plan were gotten and sensitivity analysis for several parameters were carried out. The results showed that the best plan was that hydrogen will be produced by natural gas steam reforming in central factory, then transported to refuelling stations through pipelines, and filled to fuel cell vehicles using hydrogen gas at last.

Error minimizing algorithms for nearest eighbor classifiers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Porter, Reid B; Hush, Don; Zimmer, G. Beate

2011-01-03

Stack Filters define a large class of discrete nonlinear filter first introd uced in image and signal processing for noise removal. In recent years we have suggested their application to classification problems, and investigated their relationship to other types of discrete classifiers such as Decision Trees. In this paper we focus on a continuous domain version of Stack Filter Classifiers which we call Ordered Hypothesis Machines (OHM), and investigate their relationship to Nearest Neighbor classifiers. We show that OHM classifiers provide a novel framework in which to train Nearest Neighbor type classifiers by minimizing empirical error based loss functions. Wemore » use the framework to investigate a new cost sensitive loss function that allows us to train a Nearest Neighbor type classifier for low false alarm rate applications. We report results on both synthetic data and real-world image data.« less

Vehicle detection from very-high-resolution (VHR) aerial imagery using attribute belief propagation (ABP)

NASA Astrophysics Data System (ADS)

Wang, Yanli; Li, Ying; Zhang, Li; Huang, Yuchun

2016-10-01

With the popularity of very-high-resolution (VHR) aerial imagery, the shape, color, and context attribute of vehicles are better characterized. Due to the various road surroundings and imaging conditions, vehicle attributes could be adversely affected so that vehicle is mistakenly detected or missed. This paper is motivated to robustly extract the rich attribute feature for detecting the vehicles of VHR imagery under different scenarios. Based on the hierarchical component tree of vehicle context, attribute belief propagation (ABP) is proposed to detect salient vehicles from the statistical perspective. With the Max-tree data structure, the multi-level component tree around the road network is efficiently created. The spatial relationship between vehicle and its belonging context is established with the belief definition of vehicle attribute. To effectively correct single-level belief error, the inter-level belief linkages enforce consistency of belief assignment between corresponding components at different levels. ABP starts from an initial set of vehicle belief calculated by vehicle attribute, and then iterates through each component by applying inter-level belief passing until convergence. The optimal value of vehicle belief of each component is obtained via minimizing its belief function iteratively. The proposed algorithm is tested on a diverse set of VHR imagery acquired in the city and inter-city areas of the West and South China. Experimental results show that the proposed algorithm can detect vehicle efficiently and suppress the erroneous effectively. The proposed ABP framework is promising to robustly classify the vehicles from VHR Aerial imagery.

Estimation of CO2 reduction by parallel hard-type power hybridization for gasoline and diesel vehicles.

PubMed

Oh, Yunjung; Park, Junhong; Lee, Jong Tae; Seo, Jigu; Park, Sungwook

2017-10-01

The purpose of this study is to investigate possible improvements in ICEVs by implementing fuzzy logic-based parallel hard-type power hybrid systems. Two types of conventional ICEVs (gasoline and diesel) and two types of HEVs (gasoline-electric, diesel electric) were generated using vehicle and powertrain simulation tools and a Matlab-Simulink application programming interface. For gasoline and gasoline-electric HEV vehicles, the prediction accuracy for four types of LDV models was validated by conducting comparative analysis with the chassis dynamometer and OBD test data. The predicted results show strong correlation with the test data. The operating points of internal combustion engines and electric motors are well controlled in the high efficiency region and battery SOC was well controlled within ±1.6%. However, for diesel vehicles, we generated virtual diesel-electric HEV vehicle because there is no available vehicles with similar engine and vehicle specifications with ICE vehicle. Using a fuzzy logic-based parallel hybrid system in conventional ICEVs demonstrated that HEVs showed superior performance in terms of fuel consumption and CO 2 emission in most driving modes. Copyright © 2017 Elsevier B.V. All rights reserved.

Emissions Associated with Electric Vehicle Charging: Impact of Electricity Generation Mix, Charging Infrastructure Availability, and Vehicle Type

DOE Office of Scientific and Technical Information (OSTI.GOV)

McLaren, Joyce; Miller, John; O'Shaughnessy, Eric

With the aim of reducing greenhouse gas emissions associated with the transportation sector, policy-makers are supporting a multitude of measures to increase electric vehicle adoption. The actual level of emission reduction associated with the electrification of the transport sector is dependent on the contexts that determine when and where drivers charge electric vehicles. This analysis contributes to our understanding of the degree to which a particular electricity grid profile, vehicle type, and charging patterns impact CO2 emissions from light-duty, plug-in electric vehicles. We present an analysis of emissions resulting from both battery electric and plug-in hybrid electric vehicles for fourmore » charging scenarios and five electricity grid profiles. A scenario that allows drivers to charge electric vehicles at the workplace yields the lowest level of emissions for the majority of electricity grid profiles. However, vehicle emissions are shown to be highly dependent on the percentage of fossil fuels in the grid mix, with different vehicle types and charging scenarios resulting in fewer emissions when the carbon intensity of the grid is above a defined level. Restricting charging to off-peak hours results in higher total emissions for all vehicle types, as compared to other charging scenarios.« less

Economic analysis of Japanese air pollution regulation : an optimal retirement problem under the vehicle type regulation in the NOx-particulate matter law

DOT National Transportation Integrated Search

2009-05-01

This paper examines the vehicle type regulation that was introduced under the Automobile : Nitrogen OxidesParticulate Matter Law to mitigate air pollution in Japanese metropolitan : areas. The vehicle type regulation effectively sets the timing fo...

Analysis of driver merging behavior at lane drops on freeways.

DOT National Transportation Integrated Search

2013-12-01

Lane changing assistance systems advise drivers on safe gaps for making mandatory lane changes at lane drops. In this : study, such a system was developed using a Bayes classifier and a decision tree to model lane changes. Detailed vehicle : trajecto...

Learning to classify wakes from local sensory information

NASA Astrophysics Data System (ADS)

Alsalman, Mohamad; Colvert, Brendan; Kanso, Eva; Kanso Team

2017-11-01

Aquatic organisms exhibit remarkable abilities to sense local flow signals contained in their fluid environment and to surmise the origins of these flows. For example, fish can discern the information contained in various flow structures and utilize this information for obstacle avoidance and prey tracking. Flow structures created by flapping and swimming bodies are well characterized in the fluid dynamics literature; however, such characterization relies on classical methods that use an external observer to reconstruct global flow fields. The reconstructed flows, or wakes, are then classified according to the unsteady vortex patterns. Here, we propose a new approach for wake identification: we classify the wakes resulting from a flapping airfoil by applying machine learning algorithms to local flow information. In particular, we simulate the wakes of an oscillating airfoil in an incoming flow, extract the downstream vorticity information, and train a classifier to learn the different flow structures and classify new ones. This data-driven approach provides a promising framework for underwater navigation and detection in application to autonomous bio-inspired vehicles.

Analyses of rear-end crashes based on classification tree models.

PubMed

Yan, Xuedong; Radwan, Essam

2006-09-01

Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.

Multi-class biological tissue classification based on a multi-classifier: Preliminary study of an automatic output power control for ultrasonic surgical units.

PubMed

Youn, Su Hyun; Sim, Taeyong; Choi, Ahnryul; Song, Jinsung; Shin, Ki Young; Lee, Il Kwon; Heo, Hyun Mu; Lee, Daeweon; Mun, Joung Hwan

2015-06-01

Ultrasonic surgical units (USUs) have the advantage of minimizing tissue damage during surgeries that require tissue dissection by reducing problems such as coagulation and unwanted carbonization, but the disadvantage of requiring manual adjustment of power output according to the target tissue. In order to overcome this limitation, it is necessary to determine the properties of in vivo tissues automatically. We propose a multi-classifier that can accurately classify tissues based on the unique impedance of each tissue. For this purpose, a multi-classifier was built based on single classifiers with high classification rates, and the classification accuracy of the proposed model was compared with that of single classifiers for various electrode types (Type-I: 6 mm invasive; Type-II: 3 mm invasive; Type-III: surface). The sensitivity and positive predictive value (PPV) of the multi-classifier by cross checks were determined. According to the 10-fold cross validation results, the classification accuracy of the proposed model was significantly higher (p<0.05 or <0.01) than that of existing single classifiers for all electrode types. In particular, the classification accuracy of the proposed model was highest when the 3mm invasive electrode (Type-II) was used (sensitivity=97.33-100.00%; PPV=96.71-100.00%). The results of this study are an important contribution to achieving automatic optimal output power adjustment of USUs according to the properties of individual tissues. Copyright © 2015 Elsevier Ltd. All rights reserved.

Driving context influences drivers' decision to engage in visual-manual phone tasks: Evidence from a naturalistic driving study.

PubMed

Tivesten, Emma; Dozza, Marco

2015-06-01

Visual-manual (VM) phone tasks (i.e., texting, dialing, reading) are associated with an increased crash/near-crash risk. This study investigated how the driving context influences drivers' decisions to engage in VM phone tasks in naturalistic driving. Video-recordings of 1,432 car trips were viewed to identify VM phone tasks and passenger presence. Video, vehicle signals, and map data were used to classify driving context (i.e., curvature, other vehicles) before and during the VM phone tasks (N=374). Vehicle signals (i.e., speed, yaw rate, forward radar) were available for all driving. VM phone tasks were more likely to be initiated while standing still, and less likely while driving at high speeds, or when a passenger was present. Lead vehicle presence did not influence how likely it was that a VM phone task was initiated, but the drivers adjusted their task timing to situations when the lead vehicle was increasing speed, resulting in increasing time headway. The drivers adjusted task timing until after making sharp turns and lane change maneuvers. In contrast to previous driving simulator studies, there was no evidence of drivers reducing speed as a consequence of VM phone task engagement. The results show that experienced drivers use information about current and upcoming driving context to decide when to engage in VM phone tasks. However, drivers may fail to sufficiently increase safety margins to allow time to respond to possible unpredictable events (e.g., lead vehicle braking). Advanced driver assistance systems should facilitate and possibly boost drivers' self-regulating behavior. For instance, they might recognize when appropriate adaptive behavior is missing and advise or alert accordingly. The results from this study could also inspire training programs for novice drivers, or locally classify roads in terms of the risk associated with secondary task engagement while driving. Copyright © 2015. Published by Elsevier Ltd.

Motion-mode energy method for vehicle dynamics analysis and control

NASA Astrophysics Data System (ADS)

Zhang, Nong; Wang, Lifu; Du, Haiping

2014-01-01

Vehicle motion and vibration control is a fundamental motivation for the development of advanced vehicle suspension systems. In a vehicle-fixed coordinate system, the relative motions of the vehicle between body and wheel can be classified into several dynamic stages based on energy intensity, and can be decomposed into sets of uncoupled motion-modes according to modal parameters. Vehicle motions are coupled, but motion-modes are orthogonal. By detecting and controlling the predominating vehicle motion-mode, the system cost and energy consumption of active suspensions could be reduced. A motion-mode energy method (MEM) is presented in this paper to quantify the energy contribution of each motion-mode to vehicle dynamics in real time. The control of motion-modes is prioritised according to the level of motion-mode energy. Simulation results on a 10 degree-of-freedom nonlinear full-car model with the magic-formula tyre model illustrate the effectiveness of the proposed MEM. The contribution of each motion-mode to the vehicle's dynamic behaviour is analysed under different excitation inputs from road irregularities, directional manoeuvres and braking. With the identified dominant motion-mode, novel cost-effective suspension systems, such as active reconfigurable hydraulically interconnected suspension, can possibly be used to control full-car motions with reduced energy consumption. Finally, discussion, conclusions and suggestions for future work are provided.

Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

PubMed

Sankari, E Siva; Manimegalai, D

2017-12-21

Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

A comparison of safety belt use between commercial and noncommercial light-vehicle occupants.

PubMed

Eby, David W; Fordyce, Tiffani A; Vivoda, Jonathon M

2002-05-01

The purpose of this study was to conduct an observational survey of safety belt use to determine the use rate of commercial versus noncommercial light-vehicle occupants. Observations were conducted on front-outboard vehicle occupants in eligible commercial and noncommercial vehicles in Michigan (i.e.. passenger cars, vans/minivans, sport-utility vehicles, and pickup trucks). Commercial vehicles that did not fit into one of the four vehicle type categories, such as tractor-trailers, buses, or heavy trucks, were not included in the survey. The study found that the restraint use rate for commercial light-vehicle occupants was 55.8% statewide. The statewide safety belt use rate for commercial light-vehicles was significantly lower than the rate of 71.2% for noncommercial light-vehicles. The safety belt use rate for commercial vehicles was also significantly different as a function of region, vehicle type, seating position, age group, and road type. The results provide important preliminary data about safety belt use in commercial versus noncommercial light-vehicles and indicate that further effort is needed to promote safety belt use in the commercial light-vehicle occupant population. The study also suggests that additional research is required in order to develop effective programs that address low safety belt use in the commercial light-vehicle occupant population.

Evaluation of US rear underride guard regulation for large trucks using real-world crashes.

PubMed

Brumbelow, Matthew L; Blanar, Laura

2010-11-01

Current requirements for rear underride guards on large trucks are set by the National Highway Traffic Safety Administration in Federal Motor Vehicle Safety Standards (FMVSS) 223 and 224. The standards have been in place since 1998, but their adequacy has not been evaluated apart from two series of controlled crash tests. The current study used detailed reviews of real-world crashes from the Large Truck Crash Causation Study to assess the ability of guards that comply with certain aspects of the regulation to mitigate passenger vehicle underride. It also evaluated the dangers posed by underride of large trucks that are exempt from guard requirements. For the 115 cases meeting the inclusion criteria, coded data, case narratives, photographs, and measurements were used to examine the interaction between study vehicles. The presence and type of underride guard was determined, and its performance in mitigating underride was categorized. Overall, almost one-half of the passenger vehicles had underride damage classified as severe or catastrophic. These vehicles accounted for 23 of the 28 in which occupants were killed. For the cases involving trailers with underride guards compliant with one or both FMVSS, guard deformation or complete failure was frequent and most commonly due to weak attachments, buckling of the trailer chassis, or bending of the lateral end of the guard under narrow overlap loading. Most of the truck units studied qualified for at least one of the FMVSS exemptions. The two largest groups were trailers with small wheel setbacks and single-unit straight trucks. Dump trucks represented a particularly hazardous category of straight truck. The current study suggests several weaknesses in the rear underride guard regulation. The standard allows too much ground clearance, the quasi-static test conditions allow guard designs that fail in narrow overlap crashes, and certifying guards independent of trailers leads to systems with inadequate attachment and chassis strength. Additionally, the regulation should be expanded to cover a higher percentage of the large truck fleet.

Moving object localization using optical flow for pedestrian detection from a moving vehicle.

PubMed

Hariyono, Joko; Hoang, Van-Dung; Jo, Kang-Hyun

2014-01-01

This paper presents a pedestrian detection method from a moving vehicle using optical flows and histogram of oriented gradients (HOG). A moving object is extracted from the relative motion by segmenting the region representing the same optical flows after compensating the egomotion of the camera. To obtain the optical flow, two consecutive images are divided into grid cells 14 × 14 pixels; then each cell is tracked in the current frame to find corresponding cell in the next frame. Using at least three corresponding cells, affine transformation is performed according to each corresponding cell in the consecutive images, so that conformed optical flows are extracted. The regions of moving object are detected as transformed objects, which are different from the previously registered background. Morphological process is applied to get the candidate human regions. In order to recognize the object, the HOG features are extracted on the candidate region and classified using linear support vector machine (SVM). The HOG feature vectors are used as input of linear SVM to classify the given input into pedestrian/nonpedestrian. The proposed method was tested in a moving vehicle and also confirmed through experiments using pedestrian dataset. It shows a significant improvement compared with original HOG using ETHZ pedestrian dataset.

14 CFR 431.3 - Types of reusable launch vehicle mission licenses.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 4 2013-01-01 2013-01-01 false Types of reusable launch vehicle mission licenses. 431.3 Section 431.3 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION...) General § 431.3 Types of reusable launch vehicle mission licenses. (a) Mission-specific license. A mission...

14 CFR 431.3 - Types of reusable launch vehicle mission licenses.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 4 2011-01-01 2011-01-01 false Types of reusable launch vehicle mission licenses. 431.3 Section 431.3 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION...) General § 431.3 Types of reusable launch vehicle mission licenses. (a) Mission-specific license. A mission...

14 CFR 431.3 - Types of reusable launch vehicle mission licenses.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Types of reusable launch vehicle mission licenses. 431.3 Section 431.3 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION...) General § 431.3 Types of reusable launch vehicle mission licenses. (a) Mission-specific license. A mission...

14 CFR 431.3 - Types of reusable launch vehicle mission licenses.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 4 2014-01-01 2014-01-01 false Types of reusable launch vehicle mission licenses. 431.3 Section 431.3 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION...) General § 431.3 Types of reusable launch vehicle mission licenses. (a) Mission-specific license. A mission...

14 CFR 431.3 - Types of reusable launch vehicle mission licenses.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 4 2012-01-01 2012-01-01 false Types of reusable launch vehicle mission licenses. 431.3 Section 431.3 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION...) General § 431.3 Types of reusable launch vehicle mission licenses. (a) Mission-specific license. A mission...

EPRI/SCE testing and evaluation of electric work vehicles: Jet 500, Volkswagen Type 2, DAUG Type GM2, and Battronic Minivan

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCluskey, R.K.; Arias, J.L.

1979-12-01

During the first 11 months of the EPRI/SCE Electric Vehicle Project, four electric vehicles (EVs) were tested and evaluated: the Jet Industries Electra-Van Model 500, the Volkswagen (VW) Type 2 Electrotransporter, a VW Type GM2 Transporter with DAUG electric drive, and the Battronic Minivan. The project emphasized road-testing of these vehicles to acquire data on their useful driving range, performance, and reliability. Each vehicle was driven more than 1000 miles along SCE-selected test routes to determine the effects of different terrains (level, slight grades, and steep grades), traffic conditions (one, two, three, and four stops/mile and freeway), and payload. Themore » vehicle component failures that occurred during testing are itemized and described briefly, and assessments of expected field reliability are made. Other vehicle characteristics and measurements of interest are presented. The data base on these test vehicles is intended to provide the reader an overview of the real world performance that can be expected from present-day state-of-the-art EVs.« less

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

PubMed Central

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions. PMID:26089862

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

PubMed

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

Evaluation of automobiles with alternative fuels utilizing multicriteria techniques

NASA Astrophysics Data System (ADS)

Brey, J. J.; Contreras, I.; Carazo, A. F.; Brey, R.; Hernández-Díaz, A. G.; Castro, A.

This work applies the non-parametric technique of Data Envelopment Analysis (DEA) to conduct a multicriteria comparison of some existing and under development technologies in the automotive sector. The results indicate that some of the technologies under development, such as hydrogen fuel cell vehicles, can be classified as efficient when evaluated in function of environmental and economic criteria, with greater importance being given to the environmental criteria. The article also demonstrates the need to improve the hydrogen-based technology, in comparison with the others, in aspects such as vehicle sale costs and fuel price.

Real-time people and vehicle detection from UAV imagery

NASA Astrophysics Data System (ADS)

Gaszczak, Anna; Breckon, Toby P.; Han, Jiwan

2011-01-01

A generic and robust approach for the real-time detection of people and vehicles from an Unmanned Aerial Vehicle (UAV) is an important goal within the framework of fully autonomous UAV deployment for aerial reconnaissance and surveillance. Here we present an approach for the automatic detection of vehicles based on using multiple trained cascaded Haar classifiers with secondary confirmation in thermal imagery. Additionally we present a related approach for people detection in thermal imagery based on a similar cascaded classification technique combining additional multivariate Gaussian shape matching. The results presented show the successful detection of vehicle and people under varying conditions in both isolated rural and cluttered urban environments with minimal false positive detection. Performance of the detector is optimized to reduce the overall false positive rate by aiming at the detection of each object of interest (vehicle/person) at least once in the environment (i.e. per search patter flight path) rather than every object in each image frame. Currently the detection rate for people is ~70% and cars ~80% although the overall episodic object detection rate for each flight pattern exceeds 90%.

Reactive navigation for autonomous guided vehicle using neuro-fuzzy techniques

NASA Astrophysics Data System (ADS)

Cao, Jin; Liao, Xiaoqun; Hall, Ernest L.

1999-08-01

A Neuro-fuzzy control method for navigation of an Autonomous Guided Vehicle robot is described. Robot navigation is defined as the guiding of a mobile robot to a desired destination or along a desired path in an environment characterized by as terrain and a set of distinct objects, such as obstacles and landmarks. The autonomous navigate ability and road following precision are mainly influenced by its control strategy and real-time control performance. Neural network and fuzzy logic control techniques can improve real-time control performance for mobile robot due to its high robustness and error-tolerance ability. For a mobile robot to navigate automatically and rapidly, an important factor is to identify and classify mobile robots' currently perceptual environment. In this paper, a new approach of the current perceptual environment feature identification and classification, which are based on the analysis of the classifying neural network and the Neuro- fuzzy algorithm, is presented. The significance of this work lies in the development of a new method for mobile robot navigation.

Treatment of Temporal Bone Fractures

PubMed Central

Diaz, Rodney C.; Cervenka, Brian; Brodie, Hilary A.

2016-01-01

Traumatic injury to the temporal bone can lead to significant morbidity or mortality and knowledge of the pertinent anatomy, pathophysiology of injury, and appropriate management strategies is critical for successful recovery and rehabilitation of such injured patients. Most temporal bone fractures are caused by motor vehicle accidents. Temporal bone fractures are best classified as either otic capsule sparing or otic capsule disrupting-type fractures, as such classification correlates well with risk of concomitant functional complications. The most common complications of temporal bone fractures are facial nerve injury, cerebrospinal fluid (CSF) leak, and hearing loss. Assessment of facial nerve function as soon as possible following injury greatly facilitates clinical decision making. Use of prophylactic antibiotics in the setting of CSF leak is controversial; however, following critical analysis and interpretation of the existing classic and contemporary literature, we believe its use is absolutely warranted. PMID:27648399

Treatment of Temporal Bone Fractures.

PubMed

Diaz, Rodney C; Cervenka, Brian; Brodie, Hilary A

2016-10-01

Traumatic injury to the temporal bone can lead to significant morbidity or mortality and knowledge of the pertinent anatomy, pathophysiology of injury, and appropriate management strategies is critical for successful recovery and rehabilitation of such injured patients. Most temporal bone fractures are caused by motor vehicle accidents. Temporal bone fractures are best classified as either otic capsule sparing or otic capsule disrupting-type fractures, as such classification correlates well with risk of concomitant functional complications. The most common complications of temporal bone fractures are facial nerve injury, cerebrospinal fluid (CSF) leak, and hearing loss. Assessment of facial nerve function as soon as possible following injury greatly facilitates clinical decision making. Use of prophylactic antibiotics in the setting of CSF leak is controversial; however, following critical analysis and interpretation of the existing classic and contemporary literature, we believe its use is absolutely warranted.

Hitching a ride: Seed accrual rates on different types of vehicles.

PubMed

Rew, Lisa J; Brummer, Tyler J; Pollnac, Fredric W; Larson, Christian D; Taylor, Kimberley T; Taper, Mark L; Fleming, Joseph D; Balbach, Harold E

2018-01-15

Human activities, from resource extraction to recreation, are increasing global connectivity, especially to less-disturbed and previously inaccessible places. Such activities necessitate road networks and vehicles. Vehicles can transport reproductive plant propagules long distances, thereby increasing the risk of invasive plant species transport and dispersal. Subsequent invasions by less desirable species have significant implications for the future of threatened species and habitats. The goal of this study was to understand vehicle seed accrual by different vehicle types and under different driving conditions, and to evaluate different mitigation strategies. Using studies and experiments at four sites in the western USA we addressed three questions: How many seeds and species accumulate and are transported on vehicles? Does this differ with vehicle type, driving surface, surface conditions, and season? What is our ability to mitigate seed dispersal risk by cleaning vehicles? Our results demonstrated that vehicles accrue plant propagules, and driving surface, surface conditions, and season affect the rate of accrual: on- and off-trail summer seed accrual on all-terrain vehicles was 13 and 3508 seeds km -1 , respectively, and was higher in the fall than in the summer. Early season seed accrual on 4-wheel drive vehicles averaged 7 and 36 seeds km -1 on paved and unpaved roads respectively, under dry conditions. Furthermore, seed accrual on unpaved roads differed by vehicle type, with tracked vehicles accruing more than small and large 4-wheel drives; and small 4-wheel drives more than large. Rates were dramatically increased under wet surface conditions. Vehicles indiscriminately accrue a wide diversity of seeds (different life histories, forms and seed lengths); total richness, richness of annuals, biennials, forbs and shrubs, and seed length didn't differ among vehicle types, or additional seed bank samples. Our evaluation of portable vehicle wash units showed that approximately 80% of soil and seed was removed from dirty vehicles. This suggests that interception programs to reduce vehicular seed transportation risk are feasible and should be developed for areas of high conservation value, or where the spread of invasive species is of special concern. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

A spring-mass-damper system dynamics-based driver-vehicle integrated model for representing heterogeneous traffic

NASA Astrophysics Data System (ADS)

Munigety, Caleb Ronald

2018-04-01

The traditional traffic microscopic simulation models consider driver and vehicle as a single unit to represent the movements of drivers in a traffic stream. Due to this very fact, the traditional car-following models have the driver behavior related parameters, but ignore the vehicle related aspects. This approach is appropriate for homogeneous traffic conditions where car is the major vehicle type. However, in heterogeneous traffic conditions where multiple vehicle types are present, it becomes important to incorporate the vehicle related parameters exclusively to account for the varying dynamic and static characteristics. Thus, this paper presents a driver-vehicle integrated model hinged on the principles involved in physics-based spring-mass-damper mechanical system. While the spring constant represents the driver’s aggressiveness, the damping constant and the mass component take care of the stability and size/weight related aspects, respectively. The proposed model when tested, behaved pragmatically in representing the vehicle-type dependent longitudinal movements of vehicles.

A Review of Evidence-Based Traffic Engineering Measures Designed to Reduce Pedestrian–Motor Vehicle Crashes

PubMed Central

Retting, Richard A.; Ferguson, Susan A.; McCartt, Anne T.

2003-01-01

We provide a brief critical review and assessment of engineering modifications to the built environment that can reduce the risk of pedestrian injuries. In our review, we used the Transportation Research Information Services database to conduct a search for studies on engineering countermeasures documented in the scientific literature. We classified countermeasures into 3 categories—speed control, separation of pedestrians from vehicles, and measures that increase the visibility and conspicuity of pedestrians. We determined the measures and settings with the greatest potential for crash prevention. Our review, which emphasized inclusion of studies with adequate methodological designs, showed that modification of the built environment can substantially reduce the risk of pedestrian–vehicle crashes. PMID:12948963

Measuring concentrations of selected air pollutants inside California vehicles. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodes, C.; Sheldon, L.; Whitaker, D.

1999-01-01

This project measured 2-hour integrated concentrations of PM10, PM2.5, metals and a number of organic chemicals including benzene and MTBE inside vehicles on California roadways. Using continuous samplers, particle counts, black carbon, and CO were also measured. In addition to measuring in-vehicle levels, the investigators measured pollutant levels just outside the vehicle, at roadside stations, and ambient air monitoring stations. Different driving scenarios were designed to assess the effects of a number of factors on in-vehicle pollutant levels. These factors included roadway type, carpool lanes, traffic conditions, geographical locations, vehicle type, and vehicle ventilation conditions. The statewide average in-vehicle concentrationsmore » of benzene, MTBE, and formaldehyde ranged from 3--22 {micro}g/m{sup 3}, 3--90 {micro}g/m{sup 3}, and 0---22 {micro}g/m{sup 3}, respectively. The ranges of mean PM10 and PM2.5 in-vehicle levels in Sacramento were 20--40 {micro}g/m{sup 3} and 6--22 {micro}g/m{sup 3}, respectively. In general, pollutant levels inside or just outside the vehicles were higher than those measured at the roadside stations or the ambient air stations. In-vehicle pollutant levels were consistently higher in Los Angeles than Sacramento. Pollutant levels measured inside vehicles traveling in a carpool lane were much lower than those in the right-hand, slower lanes. Under the study conditions, factors such as vehicle type and ventilation and little effect on in-vehicle pollutant levels. Other factors, such as roadway type, freeway congestion level, and time-of-day had some influence on in-vehicle pollution levels.« less

41 CFR 102-34.325 - What type of fuel do I use in Government motor vehicles?

Code of Federal Regulations, 2011 CFR

2011-01-01

... Management Federal Property Management Regulations System (Continued) FEDERAL MANAGEMENT REGULATION PERSONAL PROPERTY 34-MOTOR VEHICLE MANAGEMENT Motor Vehicle Fueling § 102-34.325 What type of fuel do I use in... 41 Public Contracts and Property Management 3 2011-01-01 2011-01-01 false What type of fuel do I...

49 CFR 571.212 - Standard No. 212; Windshield mounting.

Code of Federal Regulations, 2013 CFR

2013-10-01

... forward control vehicles, walk-in van-type vehicles, or to open-body type vehicles with fold-down or... so that the weight on each axle as measured at the tire-ground interface is in proportion to its GAWR...

49 CFR 571.212 - Standard No. 212; Windshield mounting.

Code of Federal Regulations, 2011 CFR

2011-10-01

... forward control vehicles, walk-in van-type vehicles, or to open-body type vehicles with fold-down or... so that the weight on each axle as measured at the tire-ground interface is in proportion to its GAWR...

49 CFR 571.212 - Standard No. 212; Windshield mounting.

Code of Federal Regulations, 2010 CFR

2010-10-01

... forward control vehicles, walk-in van-type vehicles, or to open-body type vehicles with fold-down or... so that the weight on each axle as measured at the tire-ground interface is in proportion to its GAWR...

49 CFR 571.212 - Standard No. 212; Windshield mounting.

Code of Federal Regulations, 2014 CFR

2014-10-01

... forward control vehicles, walk-in van-type vehicles, or to open-body type vehicles with fold-down or... so that the weight on each axle as measured at the tire-ground interface is in proportion to its GAWR...

49 CFR 571.212 - Standard No. 212; Windshield mounting.

Code of Federal Regulations, 2012 CFR

2012-10-01

... forward control vehicles, walk-in van-type vehicles, or to open-body type vehicles with fold-down or... so that the weight on each axle as measured at the tire-ground interface is in proportion to its GAWR...

Aircrew perceived stress: examining crew performance, crew position and captains personality.

PubMed

Bowles, S; Ursin, H; Picano, J

2000-11-01

This study was conducted at NASA Ames Research Center as a part of a larger research project assessing the impact of captain's personality on crew performance and perceived stress in 24 air transport crews (5). Three different personality types for captains were classified based on a previous cluster analysis (3). Crews were comprised of three crewmembers: captain, first officer, and second officer/flight engineer. A total of 72 pilots completed a 1.5-d full-mission simulation of airline operations including emergency situations in the Ames Manned Vehicle System Research Facility B-727 simulator. Crewmembers were tested for perceived stress on four dimensions of the NASA Task Load Index after each of five flight legs. Crews were divided into three groups based on rankings from combined error and rating scores. High performance crews (who committed the least errors in flight) reported experiencing less stress in simulated flight than either low or medium crews. When comparing crew positions for perceived stress over all the simulated flights no significant differences were found. However, the crews led by the "Right Stuff" (e.g., active, warm, confident, competitive, and preferring excellence and challenges) personality type captains typically reported less stress than crewmembers led by other personality types.

Comparison of Different Battery Types for Electric Vehicles

NASA Astrophysics Data System (ADS)

Iclodean, C.; Varga, B.; Burnete, N.; Cimerdean, D.; Jurchiş, B.

2017-10-01

Battery powered Electric Vehicles are starting to play a significant role in today’s automotive industry. There are many types of batteries found in the construction of today’s Electric Vehicles, being hard to decide which one fulfils best all the most important characteristics, from different viewpoints, such as energy storage efficiency, constructive characteristics, cost price, safety and utilization life. This study presents the autonomy of an Electric Vehicle that utilizes four different types of batteries: Lithium Ion (Li-Ion), Molten Salt (Na-NiCl2), Nickel Metal Hydride (Ni-MH) and Lithium Sulphur (Li-S), all of them having the same electric energy storage capacity. The novelty of this scientific work is the implementation of four different types of batteries for Electric Vehicles on the same model to evaluate the vehicle’s autonomy and the efficiency of these battery types on a driving cycle, in real time, digitized by computer simulation.

Alternative Fuels Data Center

Science.gov Websites

Fuel-Efficient Green Fleets Policy and Fleet Management Program Development The Alabama Green Fleets Review Committee (Committee) established a Green Fleets Policy (Policy) outlining a procedure for managers must classify their vehicle inventory for compliance with the Policy and submit annual plans for

Safety and operational impacts of differential speed limits on two-lane rural highways in Montana.

DOT National Transportation Integrated Search

2016-07-01

Speed limit policies can be broadly classified into two categories. Uniform speed limit policies establish the same maximum limit for all vehicles, while differential speed limit policies set a lower limit for heavy trucks in comparison to cars and l...

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system

PubMed Central

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness. PMID:28296902

Obesity and vehicle type as risk factors for injury caused by motor vehicle collision.

PubMed

Donnelly, John P; Griffin, Russell Lee; Sathiakumar, Nalini; McGwin, Gerald

2014-04-01

This study sought to describe variations in the risk of motor vehicle collision (MVC) injury and death by occupant body mass index (BMI) class and vehicle type. We hypothesized that the relationship between BMI and the risk of MVC injury or mortality would be modified by vehicle type. This is a retrospective cohort study of occupants involved in MVCs using data from the Crash Injury Research and Engineering Network and the National Automotive Sampling System Crashworthiness Data System. Occupants were grouped based on vehicle body style (passenger car, sport utility vehicle, or light truck) and vehicle size (compact or normal, corresponding to below- or above-average curb weight). The relationship between occupant BMI class (underweight, normal weight, overweight, or obese) and risk of injury or mortality was examined for each vehicle type. Odds ratios (ORs) adjusted for various occupant and collision characteristics were estimated. Of an estimated 44 million occupants of MVCs sampled from 2000 to 2009, 37.1% sustained an injury. We limited our analysis to injuries achieving an Abbreviated Injury Scale (AIS) score of 2 or more severe, totaling 17 million injuries. Occupants differed substantially in terms of demographic and collision characteristics. After adjustment for confounding factors, we found that obesity was a risk factor for mortality caused by MVC (OR, 1.6; 95% confidence interval [CI], 1.2-2.0). When stratified by vehicle type, we found that obesity was a risk factor for mortality in larger vehicles, including any-sized light trucks (OR, 2.1; 95% CI, 1.3-3.5), normal-sized passenger cars (OR, 1.6; 95% CI, 1.1-2.3), and normal-sized sports utility vehicles or vans (OR, 2.0; 95% CI, 1.0-3.8). Being overweight was a risk factor in any-sized light trucks (OR, 1.5; 95% CI, 1.1-2.1). We identified a significant interaction between occupant BMI class and vehicle type in terms of MVC-related mortality risk. Both factors should be taken into account when considering occupant safety, and additional study is needed to determine underlying causes of the observed relationships. Epidemiologic study, level III.

A Summary of the NASA Design Environment for Novel Vertical Lift Vehicles (DELIVER) Project

NASA Technical Reports Server (NTRS)

Theodore, Colin R.

2018-01-01

The number of new markets and use cases being developed for vertical take-off and landing vehicles continues to explode, including the highly publicized urban air taxi and package deliver applications. There is an equally exploding variety of novel vehicle configurations and sizes that are being proposed to fill these new market applications. The challenge for vehicle designers is that there is currently no easy and consistent way to go from a compelling mission or use case to a vehicle that is best configured and sized for the particular mission. This is because the availability of accurate and validated conceptual design tools for these novel types and sizes of vehicles have not kept pace with the new markets and vehicles themselves. The Design Environment for Novel Vertical Lift Vehicles (DELIVER) project was formulated to address this vehicle design challenge by demonstrating the use of current conceptual design tools, that have been used for decades to design and size conventional rotorcraft, applied to these novel vehicle types, configurations and sizes. In addition to demonstrating the applicability of current design and sizing tools to novel vehicle configurations and sizes, DELIVER also demonstrated the addition of key transformational technologies of noise, autonomy, and hybrid-electric and all-electric propulsion into the vehicle conceptual design process. Noise is key for community acceptance, autonomy and the need to operate autonomously are key for efficient, reliable and safe operations, and electrification of the propulsion system is a key enabler for these new vehicle types and sizes. This paper provides a summary of the DELIVER project and shows the applicability of current conceptual design and sizing tools novel vehicle configurations and sizes that are being proposed for urban air taxi and package delivery type applications.

Fuzzy risk explicit interval linear programming model for end-of-life vehicle recycling planning in the EU.

PubMed

Simic, Vladimir

2015-01-01

End-of-life vehicles (ELVs) are vehicles that have reached the end of their useful lives and are no longer registered or licensed for use. The ELV recycling problem has become very serious in the last decade and more and more efforts are made in order to reduce the impact of ELVs on the environment. This paper proposes the fuzzy risk explicit interval linear programming model for ELV recycling planning in the EU. It has advantages in reflecting uncertainties presented in terms of intervals in the ELV recycling systems and fuzziness in decision makers' preferences. The formulated model has been applied to a numerical study in which different decision maker types and several ELV types under two EU ELV Directive legislative cases were examined. This study is conducted in order to examine the influences of the decision maker type, the α-cut level, the EU ELV Directive and the ELV type on decisions about vehicle hulks procuring, storing unprocessed hulks, sorting generated material fractions, allocating sorted waste flows and allocating sorted metals. Decision maker type can influence quantity of vehicle hulks kept in storages. The EU ELV Directive and decision maker type have no influence on which vehicle hulk type is kept in the storage. Vehicle hulk type, the EU ELV Directive and decision maker type do not influence the creation of metal allocation plans, since each isolated metal has its regular destination. The valid EU ELV Directive eco-efficiency quotas can be reached even when advanced thermal treatment plants are excluded from the ELV recycling process. The introduction of the stringent eco-efficiency quotas will significantly reduce the quantities of land-filled waste fractions regardless of the type of decision makers who will manage vehicle recycling system. In order to reach these stringent quotas, significant quantities of sorted waste need to be processed in advanced thermal treatment plants. Proposed model can serve as the support for the European vehicle recycling managers in creating more successful ELV recycling plans. Copyright © 2014 Elsevier Ltd. All rights reserved.

Emergency Response Manual

NASA Technical Reports Server (NTRS)

Barnett, Traci M.

2004-01-01

Safety and security is very important at NASA. The Security Management and Safeguards Office goal is ensure safety and security for all NASA Lewis and Plum Brook Station visitors and workers. The office protects against theft, sabotage, malicious damage, espionage, and other threats or acts of violence. There are three types of security at NASA: physical, IT, and personnel. IT is concerned with sensitive and classified information and computers. Physical security includes the officers who check visitors and workers in and patrol the facility. Personnel security is concerned with background checks during hiring. During my internship, I met people from and gained knowledge about all three types of security. I primarily worked with Dr. Richard Soppet in physical security. During my experience with physical security, I observed and worked with many aspects of it. I attended various security meetings at both NASA Lewis and Plum Brook. The meetings were about homeland security and other improvements that will be made to both facilities. I also spent time with a locksmith. The locksmith makes copies of keys and unlocks doors for people who need them. I rode around in a security vehicle with an officer as he patrolled. I also observed the officer make a search of a visitor s vehicle. All visitors vehicles are searched upon entering NASA. I spent time and observed in the dispatch office. The officer answers calls and sends out officers when needed. The officer also monitors the security cameras. My primary task was completing an emergency response manual. This manual would assist local law enforcement and fire agencies in case of an emergency. The manual has pictures and descriptions of the buildings. It also contains the information about hazards inside of the buildings. This information will be very helpul to law enforcement so that when called upon during an emergency, they will not create an even bigger problem with collateral damage.

Phase 1 of the near term hybrid passenger vehicle development program

NASA Technical Reports Server (NTRS)

Montalenti, P.; Piccolo, R.

1979-01-01

In order to meet project requirements and be competitive in the 1985 market, the proposed six-passenger vehicle incorporates a high power type Ni-Zn battery, which by making electric-only traction possible, permits the achievement of an optimized control strategy based on electric-only traction to a set battery depth of discharge, followed by hybrid operation with thermal primary energy. This results in a highly efficient hybrid propulsion subsystem. Technical solutions are available to contain energy waste by reducing vehicle weight, rolling resistance, and drag coefficient. Reproaching new 1985 full size vehicles of the conventional type with hybrids of the proposed type would result in a U.S. average gasoline saving per vehicle of 1,261 liters/year and an average energy saving per vehicle of 27,133 MJ/year.

An expert computer program for classifying stars on the MK spectral classification system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gray, R. O.; Corbally, C. J.

2014-04-01

This paper describes an expert computer program (MKCLASS) designed to classify stellar spectra on the MK Spectral Classification system in a way similar to humans—by direct comparison with the MK classification standards. Like an expert human classifier, the program first comes up with a rough spectral type, and then refines that spectral type by direct comparison with MK standards drawn from a standards library. A number of spectral peculiarities, including barium stars, Ap and Am stars, λ Bootis stars, carbon-rich giants, etc., can be detected and classified by the program. The program also evaluates the quality of the delivered spectralmore » type. The program currently is capable of classifying spectra in the violet-green region in either the rectified or flux-calibrated format, although the accuracy of the flux calibration is not important. We report on tests of MKCLASS on spectra classified by human classifiers; those tests suggest that over the entire HR diagram, MKCLASS will classify in the temperature dimension with a precision of 0.6 spectral subclass, and in the luminosity dimension with a precision of about one half of a luminosity class. These results compare well with human classifiers.« less

Performance and technical feasibility comparison of reusable launch systems: A synthesis of the ESA winged launcher studies

NASA Astrophysics Data System (ADS)

Berry, W.; Grallert, H.

1996-02-01

The paper presents a synthesis of the performance and technical feasibility assessment of 7 reusable launcher types, comprising 13 different vehicles, studied by European Industry for ESA in the ESA Winged Launcher Study in the period January 1988 to May 1994. The vehicles comprised single-stage-to-orbit (SSTO) and two-stage-to-orbit (TSTO) vehicles, propelled by either air-breathing/rocket propulsion or entirely by rocket propulsion. The results showed that an SSTO vehicle of the HOTOL-type, propelled by subsonic combustion air-breathing/rocket engines could barely deliver the specified payload mass and was aerodynamically unstable; that a TSTO vehicle of the Saenger type, employing subsonic combustion airbreathing propulsion in its first stage and rocket propulsion in its second stage, could readily deliver the specified payload mass and was found to be technically feasible and versatile; that an SSTO vehicle of the NASP type, propelled by supersonic combustion airbreathing/rocket propulsion was able to deliver a reduced payload mass, was very complex and required very advanced technologies; that an air-launched rocket propelled vehicle of the Interim HOTOL type, although technically feasible, could deliver only a reduced payload mass, being constrained by the lifting capability of the carrier airplane; that three different, entirely rocket-propelled vehicles could deliver the specified payload mass, were technically feasible but required relatively advanced technologies.

Noise abatement and traffic safety: The trade-off of quieter engines and pavements on vehicle detection.

PubMed

Mendonça, C; Freitas, E; Ferreira, J P; Raimundo, I D; Santos, J A

2013-03-01

Road traffic sounds are a major source of noise pollution in urban areas. But recent developments such as low noise pavements and hybrid/electric engine vehicles cast an optimistic outlook over such an environmental problem. However, it can be argued that engine, tire, and road noise could be relevant sources of information to avoid road traffic conflicts and accidents. In this paper, we analyze the potential trade-offs of traffic-noise abatement approaches in an experimental study, focusing for the first time on the impact and interaction of relevant factors such as pavement type, vehicle type, listener's age, and background noise, on vehicle detection levels. Results reveal that vehicle and pavement type significantly affect vehicle detection. Age is a significant factor, as both younger and older people exhibit lower detection levels of incoming vehicles. Low noise pavements combined with all-electric and hybrid vehicles might pose a severe threat to the safety of vulnerable road users. All factors interact simultaneously, and vehicle detection is best predicted by the loudness signal-to-noise ratio. Copyright © 2012 Elsevier Ltd. All rights reserved.

Safety and operational impacts of differential speed limits on two-lane rural highways in Montana : project summary.

DOT National Transportation Integrated Search

2016-07-01

Speed limit policies can be broadly classified into two categories. Uniform speed limit policies establish the same maximum limit for all vehicles, while differential speed limit policies set a lower limit for heavy trucks in comparison to cars and l...

To Prevent Harm.

ERIC Educational Resources Information Center

Insurance Inst. for Highway Safety, Washington, DC.

Since 1969 the Insurance Institute of Highway Safety has concentrated on researching, demonstrating, and communicating to the public methods of reducing highway losses. The Institute has established a framework to classify the nature of each kind of loss (human, vehicle and equipment, and environment) in relation to the three phases of the crash…

Car App's Persuasive Design Principles and Behavior Change

ERIC Educational Resources Information Center

Zhang, Chao; Wan, Lili; Min, Daihwan

2016-01-01

The emphasis of this study lies in behavior change after using car apps that assist users in using their vehicles and establishing a process for examining the interrelationship between car app's persuasive characteristics and behavior change. A categorizing method was developed and 697 car apps were investigated and classified into eight…

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

PubMed

Rodriguez Gutierrez, D; Awwad, A; Meijer, L; Manita, M; Jaspan, T; Dineen, R A; Grundy, R G; Auer, D P

2014-05-01

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology. © 2014 by American Journal of Neuroradiology.

Prototyping a GNSS-Based Passive Radar for UAVs: An Instrument to Classify the Water Content Feature of Lands

PubMed Central

Troglia Gamba, Micaela; Marucco, Gianluca; Pini, Marco; Ugazio, Sabrina; Falletti, Emanuela; Lo Presti, Letizia

2015-01-01

Global Navigation Satellite Systems (GNSS) broadcast signals for positioning and navigation, which can be also employed for remote sensing applications. Indeed, the satellites of any GNSS can be seen as synchronized sources of electromagnetic radiation, and specific processing of the signals reflected back from the ground can be used to estimate the geophysical properties of the Earth’s surface. Several experiments have successfully demonstrated GNSS-reflectometry (GNSS-R), whereas new applications are continuously emerging and are presently under development, either from static or dynamic platforms. GNSS-R can be implemented at a low cost, primarily if small devices are mounted on-board unmanned aerial vehicles (UAVs), which today can be equipped with several types of sensors for environmental monitoring. So far, many instruments for GNSS-R have followed the GNSS bistatic radar architecture and consisted of custom GNSS receivers, often requiring a personal computer and bulky systems to store large amounts of data. This paper presents the development of a GNSS-based sensor for UAVs and small manned aircraft, used to classify lands according to their soil water content. The paper provides details on the design of the major hardware and software components, as well as the description of the results obtained through field tests. PMID:26569242

Dynamic response of Hovercraft lift fans

NASA Astrophysics Data System (ADS)

Moran, D. D.

1981-08-01

Hovercraft lift fans are subjected to varying back pressure due to wave action and craft motions when these vehicles are operating in a seaway. The oscillatory back pressure causes the fans to perform dynamically, exhibiting a hysteresis type of response and a corresponding degradation in mean performance. Since Hovercraft motions are influenced by variations in lift fan pressure and discharge, it is important to understand completely the nature of the dynamic performance of lift fans in order to completely solve the Hovercraft seakeeping problem. The present study was performed to determine and classify the instabilities encountered in a centrifugal fan operating against time-varying back pressure. A model-scale experiment was developed in which the fan discharge was directed into a flow-measuring device, terminating in a rotating valve which produced an oscillatory back pressure superimposed upon a mean aerodynamic resistance. Pressure and local velocity were measured as functions of time at several locations in the fan volute. The measurements permitted the identification of rotating (or propagating) stall in the impeller. One cell and two cell configurations were classified and the transient condition connecting these two configurations was observed. The mechanisms which lead to rotating stall in a centrifugal compressor are presented and discussed with specific reference to Hovercraft applications.

Prototyping a GNSS-Based Passive Radar for UAVs: An Instrument to Classify the Water Content Feature of Lands.

PubMed

Gamba, Micaela Troglia; Marucco, Gianluca; Pini, Marco; Ugazio, Sabrina; Falletti, Emanuela; Lo Presti, Letizia

2015-11-10

Global Navigation Satellite Systems (GNSS) broadcast signals for positioning and navigation, which can be also employed for remote sensing applications. Indeed, the satellites of any GNSS can be seen as synchronized sources of electromagnetic radiation, and specific processing of the signals reflected back from the ground can be used to estimate the geophysical properties of the Earth's surface. Several experiments have successfully demonstrated GNSS-reflectometry (GNSS-R), whereas new applications are continuously emerging and are presently under development, either from static or dynamic platforms. GNSS-R can be implemented at a low cost, primarily if small devices are mounted on-board unmanned aerial vehicles (UAVs), which today can be equipped with several types of sensors for environmental monitoring. So far, many instruments for GNSS-R have followed the GNSS bistatic radar architecture and consisted of custom GNSS receivers, often requiring a personal computer and bulky systems to store large amounts of data. This paper presents the development of a GNSS-based sensor for UAVs and small manned aircraft, used to classify lands according to their soil water content. The paper provides details on the design of the major hardware and software components, as well as the description of the results obtained through field tests.

System of technical vision for autonomous unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Bondarchuk, A. S.

2018-05-01

This paper is devoted to the implementation of image recognition algorithm using the LabVIEW software. The created virtual instrument is designed to detect the objects on the frames from the camera mounted on the UAV. The trained classifier is invariant to changes in rotation, as well as to small changes in the camera's viewing angle. Finding objects in the image using particle analysis, allows you to classify regions of different sizes. This method allows the system of technical vision to more accurately determine the location of the objects of interest and their movement relative to the camera.

Inductive Selectivity in Children's Cross-Classified Concepts

ERIC Educational Resources Information Center

Nguyen, Simone P.

2012-01-01

Cross-classified items pose an interesting challenge to children's induction as these items belong to many different categories, each of which may serve as a basis for a different type of inference. Inductive selectivity is the ability to appropriately make different types of inferences about a single cross-classifiable item based on its different…

41 CFR 102-34.325 - What type of fuel do I use in Government motor vehicles?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false What type of fuel do I... PROPERTY 34-MOTOR VEHICLE MANAGEMENT Motor Vehicle Fueling § 102-34.325 What type of fuel do I use in... unless: (1) Such use would be in conflict with country-to-country or multi-national logistics agreements...

Quality Issues in Propulsion

NASA Technical Reports Server (NTRS)

McCarty, John P.; Lyles, Garry M.

1997-01-01

Propulsion system quality is defined in this paper as having high reliability, that is, quality is a high probability of within-tolerance performance or operation. Since failures are out-of-tolerance performance, the probability of failures and their occurrence is the difference between high and low quality systems. Failures can be described at 3 levels: the system failure (which is the detectable end of a failure), the failure mode (which is the failure process), and the failure cause (which is the start). Failure causes can be evaluated & classified by type. The results of typing flight history failures shows that most failures are in unrecognized modes and result from human error or noise, i.e. failures are when engineers learn how things really work. Although the study based on US launch vehicles, a sampling of failures from other countries indicates the finding has broad application. The parameters of the design of a propulsion system are not single valued, but have dispersions associated with the manufacturing of parts. Many tests are needed to find failures, if the dispersions are large relative to tolerances, which could contribute to the large number of failures in unrecognized modes.

Flow visualization of unsteady phenomena in the hypersonic regime using high-speed video camera

NASA Astrophysics Data System (ADS)

Hashimoto, Tokitada; Saito, Tsutomu; Takayama, Kazuyoshi

2004-02-01

Flows over double cones and wedges featured with a large shock induced separation zone are representative of many parts of hypersonic vehicle geometries. To be practically important at shock interactions is phenomena that the shock wave produced from another objects carries out incidence to bow shock around a blunt body in the hypersonic flows, the two shock waves interact each other and various shock interactions occur according to the intensity of the shock wave and depending on the case of the local maximum of pressure and heat flux is locally produced on the body surface. The six types of shock interactions are classified, and particularly in the Type IV, a shear layer generated from the intersection of the two shock reached on the body surface, and locally anomalous pressure increase and aerodynamic heating occurred experimentally. In the present study, unsteady shock oscillations and periodically separation flows were visualized by means of high-speed video camera. Particularly, sequential observations with combination of schlieren methods are very effective because of flow unsteadiness.

SLLE for predicting membrane protein types.

PubMed

Wang, Meng; Yang, Jie; Xu, Zhi-Jie; Chou, Kuo-Chen

2005-01-07

Introduction of the concept of pseudo amino acid composition (PROTEINS: Structure, Function, and Genetics 43 (2001) 246; Erratum: ibid. 44 (2001) 60) has made it possible to incorporate a considerable amount of sequence-order effects by representing a protein sample in terms of a set of discrete numbers, and hence can significantly enhance the prediction quality of membrane protein type. As a continuous effort along such a line, the Supervised Locally Linear Embedding (SLLE) technique for nonlinear dimensionality reduction is introduced (Science 22 (2000) 2323). The advantage of using SLLE is that it can reduce the operational space by extracting the essential features from the high-dimensional pseudo amino acid composition space, and that the cluster-tolerant capacity can be increased accordingly. As a consequence by combining these two approaches, high success rates have been observed during the tests of self-consistency, jackknife and independent data set, respectively, by using the simplest nearest neighbour classifier. The current approach represents a new strategy to deal with the problems of protein attribute prediction, and hence may become a useful vehicle in the area of bioinformatics and proteomics.

Toward reconciling instantaneous roadside measurements of light duty vehicle exhaust emissions with type approval driving cycles.

PubMed

Rhys-Tyler, Glyn A; Bell, Margaret C

2012-10-02

A method is proposed to relate essentially instantaneous roadside measurements of vehicle exhaust emissions, with emission results generated over a type approval driving cycle. An urban remote sensing data set collected in 2008 is used to define the dynamic relationship between vehicle specific power and exhaust emissions, across a range of vehicle ages, engine capacities, and fuel types. The New European Driving Cycle is synthesized from the remote sensing data using vehicle specific power to characterize engine load, and the results compared with official published emissions data from vehicle type approval tests over the same driving cycle. Mean carbon monoxide emissions from gasoline-powered cars ≤ 3 years old measured using remote sensing are found to be 1.3 times higher than published original type approval test values; this factor increases to 2.2 for cars 4-8 years old, and 6.4 for cars 9-12 years old. The corresponding factors for diesel cars are 1.1, 1.4, and 1.2, respectively. Results for nitric oxide, hydrocarbons, and particulate matter are also reported. The findings have potential implications for the design of traffic management interventions aimed at reducing emissions, fleet inspection and maintenance programs, and the specification of vehicle emission models.

Adaptive road crack detection system by pavement classification.

PubMed

Gavilán, Miguel; Balcones, David; Marcos, Oscar; Llorca, David F; Sotelo, Miguel A; Parra, Ignacio; Ocaña, Manuel; Aliseda, Pedro; Yarza, Pedro; Amírola, Alejandro

2011-01-01

This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement.

Adaptive Road Crack Detection System by Pavement Classification

PubMed Central

Gavilán, Miguel; Balcones, David; Marcos, Oscar; Llorca, David F.; Sotelo, Miguel A.; Parra, Ignacio; Ocaña, Manuel; Aliseda, Pedro; Yarza, Pedro; Amírola, Alejandro

2011-01-01

This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement. PMID:22163717

Vehicle track segmentation using higher order random fields

DOE PAGES

Quach, Tu -Thach

2017-01-09

Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure onmore » a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.« less

Vehicle track segmentation using higher order random fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quach, Tu -Thach

Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure onmore » a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.« less

Air ion concentrations in various urban outdoor environments

NASA Astrophysics Data System (ADS)

Ling, Xuan; Jayaratne, Rohan; Morawska, Lidia

2010-06-01

Atmospheric ions are produced by many natural and anthropogenic sources and their concentrations vary widely between different environments. There is very little information on their concentrations in different types of urban environments, how they compare across these environments and their dominant sources. In this study, we measured airborne concentrations of small ions, particles and net particle charge at 32 different outdoor sites in and around a major city in Australia and identified the main ion sources. Sites were classified into seven groups as follows: park, woodland, city centre, residential, freeway, power lines and power substation. Generally, parks were situated away from ion sources and represented the urban background value of about 270 ions cm -3. Median concentrations at all other groups were significantly higher than in the parks. We show that motor vehicles and power transmission systems are two major ion sources in urban areas. Power lines and substations constituted strong unipolar sources, while motor vehicle exhaust constituted strong bipolar sources. The small ion concentration in urban residential areas was about 960 cm -3. At sites where ion sources were co-located with particle sources, ion concentrations were inhibited due to the ion-particle attachment process. These results improved our understanding on air ion distribution and its interaction with particles in the urban outdoor environment.

Effects of strain differences and vehicles on results of local lymph node assays.

PubMed

Anzai, Takayuki; Ullmann, Ludwig G; Hayashi, Daisuke; Satoh, Tetsuo; Kumazawa, Takeshi; Sato, Keizo

2010-01-01

The Local Lymph Node Assay (LLNA) is now regarded as the worldwide standard. The analysis of accumulated LLNA data reveals that the animal strains and vehicles employed are likely to affect LLNA results. Here we show that an obvious strain difference in the local lymph node response was observed between DMSO-treated CBA/CaOlaHsd and CBA/CaHsdRcc mice. We also show that a vehicle difference in the response was observed when CBA/CaHsdRcc mice were exposed to 6 vehicles; 4:1 v/v acetone/olive oil (AOO), ethanol/water (70% EtOH), N,N-dimethylformamide (DMF), 2-butanone (BN), propylene glycol (PG), and dimethylsulfoxide (DMSO). The dpm/LN level was lowest in the 70% EtOH group and highest in the DMSO group. When alpha-hexylcinnamaldehyde (HCA) was used as a sensitizer for the LLNA, HCA was a weak sensitizer when AOO or DMSO was used as a vehicle, but a moderate sensitizer when the other 4 vehicles were used. This study showed that there are vehicle differences in the local lymph node response (dpm/LN level) in the LLNA and that the sensitization potency of HCA may be classified in different categories when using different vehicles. This suggests that careful consideration should be exercised in selecting a vehicle for the LLNA. A further comprehensive study will be needed to investigate why vehicle differences are observed in the LLNA.

Analyses of factors of crash avoidance maneuvers using the general estimates system.

PubMed

Yan, Xuedong; Harb, Rami; Radwan, Essam

2008-06-01

Taking an effective corrective action to a critical traffic situation provides drivers an opportunity to avoid crash occurrence and minimize crash severity. The objective of this study is to investigate the relationship between the probability of taking corrective actions and the characteristics of drivers, vehicles, and driving environments. Using the 2004 GES crash database, this study classified drivers who encountered critical traffic events (identified as P_CRASH3 in the GES database) into two pre-crash groups: corrective avoidance actions group and no corrective avoidance actions group. Single and multiple logistic regression analyses were performed to identify potential traffic factors associated with the probability of drivers taking corrective actions. The regression results showed that the driver/vehicle factors associated with the probability of taking corrective actions include: driver age, gender, alcohol use, drug use, physical impairments, distraction, sight obstruction, and vehicle type. In particular, older drivers, female drivers, drug/alcohol use, physical impairment, distraction, or poor visibility may increase the probability of failing to attempt to avoid crashes. Moreover, drivers of larger size vehicles are 42.5% more likely to take corrective avoidance actions than passenger car drivers. On the other hand, the significant environmental factors correlated with the drivers' crash avoidance maneuver include: highway type, number of lanes, divided/undivided highway, speed limit, highway alignment, highway profile, weather condition, and surface condition. Some adverse highway environmental factors, such as horizontal curves, vertical curves, worse weather conditions, and slippery road surface conditions are correlated with a higher probability of crash avoidance maneuvers. These results may seem counterintuitive but they can be explained by the fact that motorists may be more likely to drive cautiously in those adverse driving environments. The analyses revealed that drivers' distraction could be the highest risk factor leading to the failure of attempting to avoid crashes. Further analyses entailing distraction causes (e.g., cellular phone use) and their possible countermeasures need to be conducted. The age and gender factors are overrepresented in the "no avoidance maneuver." A possible solution could involve the integration of a new function in the current ITS technologies. A personalized system, which could be related to the expected type of maneuver for a driver with certain characteristics, would assist different drivers with different characteristics to avoid crashes. Further crash database studies are recommended to investigate the association of drivers' emergency maneuvers such as braking, steering, or their combination with crash severity.

The role of intersection and street design on severity of bicycle-motor vehicle crashes

PubMed Central

Verma, Santosh; Mekary, Rania A; Courtney, Theodore K; Christiani, David C

2017-01-01

Background Safety concerns are a major barrier to cycling. Intersection and street design variables such as intersection angles and street width might contribute to the severity of crashes and the safety concerns. In this study we examined whether these design variables were associated with bicycle-motor vehicle crashes (BMVC) severity. Methods Using the geographical information system and latitudes/longitudes recorded by the police using a global positioning device, we extracted intersection angles, street width, bicycle facilities, posted speed limits and annual average daily traffic from 3266 BMVC data from New York City police records. Additional variables about BMVC, including age and sex of the bicyclist, time of the day, road surface conditions, road character, vehicle type and injury severity, were obtained from police reports. Injury severity was classified as severe (incapacitating or killed) or non-severe (non-incapacitating, possible injury). The associations between injury severity and environment design variables were examined using multivariate log-binomial regression model. Findings Compared with crashes at orthogonal intersections, crashes at non-orthogonal intersections had 1.37 times (95% CI 1.05 to 1.80) and non-intersection street segments had 1.31 times (95% CI 1.01 to 1.70) higher risk of a severe injury. Crashes that involved a truck or a bus were twice as likely to result in a severe injury outcome; street width was not significantly associated with injury severity. Conclusion Crashes at non-orthogonal intersections and non-intersection segments are more likely to result in higher injury severity. The findings can be used to improve road design and develop effective safety interventions. PMID:27881469

Determinants of seat belt use behaviour: a protocol for a systematic review

PubMed Central

Ghaffari, Mohtasham; Armoon, Bahram; Rakhshanderou, Sakineh; Mehrabi, Yadollah; Soori, Hamid; Simsekoghlu, Ozelem; Harooni, Javad

2018-01-01

Introduction The use of seat belts could prevent severe collision damage to people in vehicle accidents and keep passengers safe from sustaining serious injuries; for instance, it could prevent passengers from being thrown out of a vehicle after the collision. The current systematic review will identify and analyse the determinants of seat belt use behaviour. Methods and analysis We will include qualitative, quantitative and mixed methods studies reporting the acquired data from passengers aged more than 12 years and drivers, from both commercial and personal vehicles. Online databases including MEDLINE/PubMed, Scopus, Web of Science, Embase, Cochrane Database of Systematic Reviews and PsycINFO will be investigated in the current study. Published and available articles will be evaluated according to their titles and abstracts. Published papers conforming to the inclusion criteria will be organised for a complete review. Next, the full text of the remaining articles will be studied independently for eligibility by two authors. The quality of the selected studies will be assessed with appropriate tools. Based on the information obtained from the data extraction, the type of determinants of seat belt use will be classified. Ethics and dissemination Ethics approval is not required, because this is a protocol for a systematic review and no primary data will be collected. The authors will ensure to maintain the rights of the used and included articles in the present systematic review. The findings of this review will be published in a relevant peer-reviewed journal. PROSPERO registration number CRD42017067511. PMID:29724739

Liquid Propulsion: Propellant Feed System Design. Chapter 2.3.11

NASA Technical Reports Server (NTRS)

Cannon, James L.

2010-01-01

The propellant feed system of a liquid rocket engine determines how the propellants are delivered from the tanks to the thrust chamber. They are generally classified as either pressure fed or pump fed. The pressure-fed system is simple and relies on tank pressures to feed the propellants into the thrust chamber. This type of system is typically used for space propulsion applications and auxiliary propulsion applications requiring low system pressures and small quantities of propellants. In contrast, the pump-fed system is used for high pressure, high performance applications. The selection of one propellant feed system over another is determined based on design trade studies at both the engine and vehicle levels. This chapter first provides a brief overview of the basic configurations of pressure-fed systems. Pump-fed systems are then discussed with greater detail given to the turbomachinery design. Selected design requirements and configurations are provided.

A Generalized Formulation of Demand Response under Market Environments

NASA Astrophysics Data System (ADS)

Nguyen, Minh Y.; Nguyen, Duc M.

2015-06-01

This paper presents a generalized formulation of Demand Response (DR) under deregulated electricity markets. The problem is scheduling and controls the consumption of electrical loads according to the market price to minimize the energy cost over a day. Taking into account the modeling of customers' comfort (i.e., preference), the formulation can be applied to various types of loads including what was traditionally classified as critical loads (e.g., air conditioning, lights). The proposed DR scheme is based on Dynamic Programming (DP) framework and solved by DP backward algorithm in which the stochastic optimization is used to treat the uncertainty, if any occurred in the problem. The proposed formulation is examined with the DR problem of different loads, including Heat Ventilation and Air Conditioning (HVAC), Electric Vehicles (EVs) and a newly DR on the water supply systems of commercial buildings. The result of simulation shows significant saving can be achieved in comparison with their traditional (On/Off) scheme.

23 CFR 500.202 - TMS definitions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... particular location on a highway. These types of data support the estimation of the number of vehicles... used in this part: Highway traffic data means data used to develop estimates of the amount of person or... portion of such vehicles that may be of a particular type (vehicle classification), the weights of such...

23 CFR 500.202 - TMS definitions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... particular location on a highway. These types of data support the estimation of the number of vehicles... used in this part: Highway traffic data means data used to develop estimates of the amount of person or... portion of such vehicles that may be of a particular type (vehicle classification), the weights of such...

Sparse representation based SAR vehicle recognition along with aspect angle.

PubMed

Xing, Xiangwei; Ji, Kefeng; Zou, Huanxin; Sun, Jixiang

2014-01-01

As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle's aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle's aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

PHEV-EV Charger Technology Assessment with an Emphasis on V2G Operation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kisacikoglu, Mithat C; Bedir, Abdulkadir; Ozpineci, Burak

2012-03-01

More battery powered electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) will be introduced to the market in 2011 and beyond. Since these vehicles have large batteries that need to be charged from an external power source or directly from the grid, their batteries, charging circuits, charging stations/infrastructures, and grid interconnection issues are garnering more attention. This report summarizes information regarding the batteries used in PHEVs, different types of chargers, charging standards and circuits, and compares different topologies. Furthermore, it includes a list of vehicles that are going to be in the market soon with information on their chargingmore » and energy storage equipment. A summary of different standards governing charging circuits and charging stations concludes the report. There are several battery types that are available for PHEVs; however, the most popular ones have nickel metal hydride (NiMH) and lithium-ion (Li-ion) chemistries. The former one is being used in current hybrid electric vehicles (HEVs), but the latter will be used in most of the PHEVs and EVs due to higher energy densities and higher efficiencies. The chargers can be classified based on the circuit topologies (dedicated or integrated), location of the charger (either on or off the vehicle), connection (conductive, inductive/wireless, and mechanical), electrical waveform (direct current (dc) or alternating current (ac)), and the direction of power flow (unidirectional or bidirectional). The first PHEVs typically will have dedicated, on-board, unidirectional chargers that will have conductive connections to the charging stations or wall outlets and will be charged using either dc or ac. In the near future, bidirectional chargers might also be used in these vehicles once the benefits of practical vehicle to grid applications are realized. The terms charger and charging station cause terminology confusion. To prevent misunderstandings, a more descriptive term of electric vehicle supply equipment (EVSE) is used instead of charging station. The charger is the power conversion equipment that connects the battery to the grid or another power source, while EVSE refers to external equipment between the grid or other power source and the vehicle. EVSE might include conductors, connectors, attachment plugs, microprocessors, energy measurement devices, transformers, etc. Presently, there are more than 40 companies that are producing EVSEs. There are several standards and codes regarding conductive and inductive chargers and EVSEs from the Society of Automotive Engineers (SAE), the Underwriter Laboratories (UL), the International Electrotechnical Commission (IEC), and the National Electric Code (NEC). The two main standards from SAE describe the requirements for conductive and inductive coupled chargers and the charging levels. For inductive coupled charging, three levels are specified: Level 1 (120 V and 12 A, single-phase), Level 2 (208 V-240 V and 32 A, single-phase), and Level 3 (208-600 V and 400 A, three-phase) . The standard for the conductive-coupled charger also has similar charging ratings for Levels 1 and 2, but it allows higher current ratings for Level 2 charging up to 80 A. Level 3 charging for this standard is still under development and considers dc charging instead of three-phase ac. More details in these areas and related references can be found in this Oak Ridge National Laboratory (ORNL) report on PHEV-EV charger technology assessment.« less

Judging arrival times of incoming traffic vehicles is not a prerequisite for safely crossing an intersection: Differential effects of vehicle size and type in passive judgment and active driving tasks.

PubMed

Mathieu, Julie; Bootsma, Reinoud J; Berthelon, Catherine; Montagne, Gilles

2017-02-01

Using a fixed-base driving simulator we compared the effects of the size and type of traffic vehicles (i.e., normal-sized or double-sized cars or motorcycles) approaching an intersection in two different tasks. In the perceptual judgment task, passively moving participants estimated when a traffic vehicle would reach the intersection for actual arrival times (ATs) of 1, 2, or 3s. In line with earlier findings, ATs were generally underestimated, the more so the longer the actual AT. Results revealed that vehicle size affected judgments in particular for the larger actual ATs (2 and 3s), with double-sized vehicles then being judged as arriving earlier than normal-sized vehicles. Vehicle type, on the other hand, affected judgments at the smaller actual ATs (1 and 2s), with cars then being judged as arriving earlier than motorcycles. In the behavioral task participants actively drove the simulator to cross the intersection by passing through a gap in a train of traffic. Analyses of the speed variations observed during the active intersection-crossing task revealed that the size and type of vehicles in the traffic train did not affect driving behavior in the same way as in the AT judgment task. First, effects were considerably smaller, affecting driving behavior only marginally. Second, effects were opposite to expectations based on AT judgments: driver approach speeds were smaller (rather than larger) when confronted with double-sized vehicles as compared to their normal-sized counterparts and when confronted with cars as compared to motorcycles. Finally, the temporality of the effects was different on the two tasks: vehicle size affected driver approach speed in the final stages of approach rather than early on, while vehicle type affected driver approach speed early on rather than later. Overall, we conclude that the active control of approach to the intersection is not based on successive judgments of traffic vehicle arrival times. These results thereby question the general belief that arrival time estimates are crucial for safe interaction with traffic. Copyright © 2016 Elsevier B.V. All rights reserved.

Dates fruits classification using SVM

NASA Astrophysics Data System (ADS)

Alzu'bi, Reem; Anushya, A.; Hamed, Ebtisam; Al Sha'ar, Eng. Abdelnour; Vincy, B. S. Angela

2018-04-01

In this paper, we used SVM in classifying various types of dates using their images. Dates have interesting different characteristics that can be valuable to distinguish and determine a particular date type. These characteristics include shape, texture, and color. A system that achieves 100% accuracy was built to classify the dates which can be eatable and cannot be eatable. The built system helps the food industry and customer in classifying dates depending on specific quality measures giving best performance with specific type of dates.

Diagnosis of early gastric cancer using narrow band imaging and acetic acid

PubMed Central

Matsuo, Ken; Takedatsu, Hidetoshi; Mukasa, Michita; Sumie, Hiroaki; Yoshida, Hikaru; Watanabe, Yasutomo; Akiba, Jun; Nakahara, Keita; Tsuruta, Osamu; Torimura, Takuji

2015-01-01

AIM: To determine whether the endoscopic findings of depressed-type early gastric cancers (EGCs) could precisely predict the histological type. METHODS: Ninety depressed-type EGCs in 72 patients were macroscopically and histologically identified. We evaluated the microvascular (MV) and mucosal surface (MS) patterns of depressed-type EGCs using magnifying endoscopy (ME) with narrow-band imaging (NBI) (NBI-ME) and ME enhanced by 1.5% acetic acid, respectively. First, depressed-type EGCs were classified according to MV pattern by NBI-ME. Subsequently, EGCs unclassified by MV pattern were classified according to MS pattern by enhanced ME (EME) images obtained from the same angle. RESULTS: We classified the depressed-type EGCs into the following 2 MV patterns using NBI-ME: a fine-network pattern that indicated differentiated adenocarcinoma (25/25, 100%) and a corkscrew pattern that likely indicated undifferentiated adenocarcinoma (18/23, 78.3%). However, 42 of the 90 (46.7%) lesions could not be classified into MV patterns by NBI-ME. These unclassified lesions were then evaluated for MS patterns using EME, which classified 33 (81.0%) lesions as MS patterns, diagnosed as differentiated adenocarcinoma. As a result, 76 of the 90 (84.4%) lesions were matched with histological diagnoses using a combination of NBI-ME and EME. CONCLUSION: A combination of NBI-ME and EME was useful in predicting the histological type of depressed-type EGC. PMID:25632201

Evaluation of weapons' combustion products in armored vehicles. Final report, 30 September 1986-14 December 1988

DOE Office of Scientific and Technical Information (OSTI.GOV)

Menzies, K.T.; Randel, M.A.; Quill, A.L.

1989-01-01

The U.S. Army Biomedical Research and Development Laboratory defined an extensive research program to address the generation of potentially toxic propellant combustion products in crew compartments of armored vehicles during weapons firing. The major objectives of the research were: (1) to determine the presence and concentration of propellant combustion products, (2) to determine potential crew exposure to these combustion products, and (3) to assess the efficacy of field monitoring in armored vehicles. To achieve these goals, air monitoring was conducted in selected armored vehicle types, i.e., M109, M60, M3, M1, at several Army installations. Auxiliary information concerning the specific munitionsmore » fired and the Training and Doctrine Command (TRADOC) or Forces Command (FORSCOM) firing scenarios was collected so that a comparison of pollutant concentrations generated by specific weapons both within vehicle types and between vehicle types could be made.« less

Analysis of Defense Products Contract Trends, 1990-2014

DTIC Science & Technology

2015-04-30

contract obligations) are not properly classified under their parent programs. Electronics & Communications Contract obligations for Electronics...Electronics & Communications , Engines & Power Plants, Fuels, Ground Vehicles, Launchers & Munitions, Missiles & Space, Ships, and “Other.”3 This...mostly comprised of platforms and programs related to MDAPs (Clothing & Subsistence, Electronics & Communications , Fuels, Launchers & Munitions, and

Fresh Start: A Model for Success and Sustainable Change

ERIC Educational Resources Information Center

Matthews, Susan; Kinchington, Francia

2006-01-01

This article examines the rationale and debate of the "Fresh Start" schools policy introduced by the New Labour Government in 1997 as a vehicle for improvement in schools that historically had been classified as "failing". Underpinning the policy is the assumption that Fresh Start can act as a catalytic agent of positive change…

An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions Using Inaccurate or Scarce Information

NASA Technical Reports Server (NTRS)

Smith, Kelly M.; Gay, Robert S.; Stachowiak, Susan J.

2013-01-01

In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

An Alternative Flight Software Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

NASA Technical Reports Server (NTRS)

Smith, Kelly; Gay, Robert; Stachowiak, Susan

2013-01-01

In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles

An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

NASA Technical Reports Server (NTRS)

Smith, Kelly M.; Gay, Robert S.; Stachowiak, Susan J.

2013-01-01

In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter. In order to increase overall robustness, the vehicle also has an alternate method of triggering the drogue parachute deployment based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this velocity-based trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers excellent performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

Chitosan preparations for wounds and burns: antimicrobial and wound-healing effects

PubMed Central

Dai, Tianhong; Tanaka, Masamitsu; Huang, Ying-Ying; Hamblin, Michael R

2011-01-01

Since its discovery approximately 200 years ago, chitosan, as a cationic natural polymer, has been widely used as a topical dressing in wound management owing to its hemostatic, stimulation of healing, antimicrobial, nontoxic, biocompatible and biodegradable properties. This article covers the antimicrobial and wound-healing effects of chitosan, as well as its derivatives and complexes, and its use as a vehicle to deliver biopharmaceuticals, antimicrobials and growth factors into tissue. Studies covering applications of chitosan in wounds and burns can be classified into in vitro, animal and clinical studies. Chitosan preparations are classified into native chitosan, chitosan formulations, complexes and derivatives with other substances. Chitosan can be used to prevent or treat wound and burn infections not only because of its intrinsic antimicrobial properties, but also by virtue of its ability to deliver extrinsic antimicrobial agents to wounds and burns. It can also be used as a slow-release drug-delivery vehicle for growth factors to improve wound healing. The large number of publications in this area suggests that chitosan will continue to be an important agent in the management of wounds and burns. PMID:21810057

19 CFR 115.65 - Technical requirements for road vehicles by design type.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 1 2012-04-01 2012-04-01 false Technical requirements for road vehicles by design type. 115.65 Section 115.65 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY CARGO CONTAINER AND ROAD VEHICLE CERTIFICATION PURSUANT TO...

19 CFR 115.65 - Technical requirements for road vehicles by design type.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 1 2011-04-01 2011-04-01 false Technical requirements for road vehicles by design type. 115.65 Section 115.65 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY CARGO CONTAINER AND ROAD VEHICLE CERTIFICATION PURSUANT TO...

19 CFR 115.65 - Technical requirements for road vehicles by design type.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 1 2013-04-01 2013-04-01 false Technical requirements for road vehicles by design type. 115.65 Section 115.65 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY CARGO CONTAINER AND ROAD VEHICLE CERTIFICATION PURSUANT TO...

19 CFR 115.65 - Technical requirements for road vehicles by design type.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 19 Customs Duties 1 2014-04-01 2014-04-01 false Technical requirements for road vehicles by design type. 115.65 Section 115.65 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY CARGO CONTAINER AND ROAD VEHICLE CERTIFICATION PURSUANT TO...

19 CFR 115.65 - Technical requirements for road vehicles by design type.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 1 2010-04-01 2010-04-01 false Technical requirements for road vehicles by design type. 115.65 Section 115.65 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY CARGO CONTAINER AND ROAD VEHICLE CERTIFICATION PURSUANT TO...

26 CFR 48.4073-3 - Exemption of tread rubber used for recapping nonhighway tires.

Code of Federal Regulations, 2010 CFR

2010-04-01

... TREASURY (CONTINUED) MISCELLANEOUS EXCISE TAXES MANUFACTURERS AND RETAILERS EXCISE TAXES Motor Vehicles... person otherwise than in the recapping or retreading of tires of the type used on highway vehicles. In determining whether tread rubber is sold for a taxable or nontaxable use, the type of vehicle on which the...

Severity of child pedestrian injuries due to bonnet-type-vehicle collision.

PubMed

Hitosugi, Masahito; Kawato, Hitoshi; Gomei, Sayaka; Mizuno, Koji; Tokudome, Shogo

2013-10-01

The aim of this study was to clarify the pattern of child pedestrian injury, injury severity, and its relation to collision velocity in bonnet-type-vehicle collision. In-depth data were retrospectively collected from the Institute for Traffic Accident Research and Data Analysis on pedestrians younger than 13 years old with any bodily injuries from collisions with bonnet-type vehicles between 1993 and 2004. Forty-seven patients from 43 collisions with a mean age of 6.9 ± 2.5 years were included in the study. Injury severity was not significantly different between patients who were hit by the front of the vehicle and those who were hit by the side of the vehicle. In front collisions, impact with the vehicle was associated with significantly higher Abbreviated Injury Scale (AIS) scores than those for impact with the road, especially for the lower extremities (mean: 1.2 vs 0.2, P < 0.001). Injury severity of the lower extremities and collision velocity were examined. The estimated collision velocity of the vehicle was not significantly different between patients with lower extremity AIS scores of 0 or 1 and those of 2 or 3. Some pediatric pedestrians suffer from collisions with bonnet-type vehicles without lower extremity fractures owing to the characteristics of child pedestrians. Providing injury prevention programs for children in communities and schools, developing active safety devices in the vehicle, and modifying the vehicle body to a pediatric pedestrian-friendly structure may increase pedestrian protection. © 2013 The Authors. Pediatrics International © 2013 Japan Pediatric Society.

Musculoskeletal disorder risk during automotive assembly: current vs. seated

PubMed Central

Ferguson, Sue A.; Marras, William S.; Allread, W. Gary; Knapik, Gregory G.; Splittstoesser, Riley E.

2013-01-01

Musculoskeletal disorder risk was assessed during automotive assembly processes. The risk associated with current assembly processes was compared to using a cantilever chair intervention. Spine loads and normalized shoulder muscle activity were evaluated during assembly in eight regions of the vehicle. Eight interior cabin regions of the vehicle were classified by reach distance, height from vehicle floor and front to back. The cantilever chair intervention tool was most effective in the far reach regions regardless of the height. In the front far reach regions both spine loads and normalized shoulder muscle activity levels were reduced. In the middle and close reach regions spine loads were reduced, however, shoulder muscle activity was not, thus an additional intervention would be necessary to reduce shoulder risk. In the back far reach region, spine loads were not significantly different between the current and cantilever chair conditions. Thus, the effectiveness of the cantilever chair was dependent on the region of the vehicle. PMID:22036450

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

PubMed

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-08-19

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

Impacts of pavement types on in-vehicle noise and human health.

PubMed

Li, Qing; Qiao, Fengxiang; Yu, Lei

2016-01-01

Noise is a major source of pollution that can affect the human physiology and living environment. According to the World Health Organization (WHO), an exposure for longer than 24 hours to noise levels above 70 dB(A) may damage human hearing sensitivity, induce adverse health effects, and cause anxiety to residents nearby roadways. Pavement type with different roughness is one of the associated sources that may contribute to in-vehicle noise. Most previous studies have focused on the impact of pavement type on the surrounding acoustic environment of roadways, and given little attention to in-vehicle noise levels. This paper explores the impacts of different pavement types on in-vehicle noise levels and the associated adverse health effects. An old concrete pavement and a pavement with a thin asphalt overlay were chosen as the test beds. The in-vehicle noise caused by the asphalt and concrete pavements were measured, as well as the drivers' corresponding heart rates and reported riding comfort. Results show that the overall in-vehicle sound levels are higher than 70 dB(A) even at midnight. The newly overlaid asphalt pavement reduced in-vehicle noise at a driving speed of 96.5 km/hr by approximately 6 dB(A). Further, on the concrete pavement with higher roughness, driver heart rates were significantly higher than on the asphalt pavement. Drivers reported feeling more comfortable when driving on asphalt than on concrete pavement. Further tests on more drivers with different demographic characteristics, along highways with complicated configurations, and an examination of more factors contributing to in-vehicle noise are recommended, in addition to measuring additional physical symptoms of both drivers and passengers. While there have been many previous noise-related studies, few have addressed in-vehicle noise. Most studies have focused on the noise that residents have complained about, such as neighborhood traffic noise. As yet, there have been no complaints by drivers that their own in-vehicle noise is too loud. Nevertheless, it is a fact that in-vehicle noise can also result in adverse health effects if it exceeds 85 dB(A). Results of this study show that in-vehicle noise was strongly associated with pavement type and roughness; also, driver heart rate patterns presented statistically significant differences on different types of pavement with different roughness.

Ablative Heat Shield Studies for NASA Mars/Earth Return Entry Vehicles

DTIC Science & Technology

1990-09-01

RETURN ENTRY VEHICLES by Michael K. Hamm September, 1990 NASA Thesis Advisor: William D. Henline Thesis Co-Advisor: Max F. Platzer Approved for public...STUDIES FOR NASA MARS/EARTH RETURN ENTRY VEHICLES (UNCLASSIFIED) 12. PERSONAL AUTHOR(S) Harm, Michael, K. 13a TYPE OF REPORT 13b TIME COVERED 14 DATE OF...theoretical values. The tests were performed to ascertain if RSI type materials could be used for entry vehicles proposed in NASA Mars missions. 20

49 CFR 383.119 - Requirements for tank vehicle endorsement.

Code of Federal Regulations, 2011 CFR

2011-10-01

... vehicles; (d) Differences in tank vehicle type and construction; (e) Differences in cargo surge for liquids of varying product densities; (f) Effects of road grade and curvature on motor vehicle handling with...

Acoustic target detection and classification using neural networks

NASA Technical Reports Server (NTRS)

Robertson, James A.; Conlon, Mark

1993-01-01

A neural network approach to the classification of acoustic emissions of ground vehicles and helicopters is demonstrated. Data collected during the Joint Acoustic Propagation Experiment conducted in July of l991 at White Sands Missile Range, New Mexico was used to train a classifier to distinguish between the spectrums of a UH-1, M60, M1 and M114. An output node was also included that would recognize background (i.e. no target) data. Analysis revealed specific hidden nodes responding to the features input into the classifier. Initial results using the neural network were encouraging with high correct identification rates accompanied by high levels of confidence.

Vehicle Color Recognition with Vehicle-Color Saliency Detection and Dual-Orientational Dimensionality Reduction of CNN Deep Features

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Li, Jiafeng; Zhuo, Li; Zhang, Hui; Li, Xiaoguang

2017-12-01

Color is one of the most stable attributes of vehicles and often used as a valuable cue in some important applications. Various complex environmental factors, such as illumination, weather, noise and etc., result in the visual characteristics of the vehicle color being obvious diversity. Vehicle color recognition in complex environments has been a challenging task. The state-of-the-arts methods roughly take the whole image for color recognition, but many parts of the images such as car windows; wheels and background contain no color information, which will have negative impact on the recognition accuracy. In this paper, a novel vehicle color recognition method using local vehicle-color saliency detection and dual-orientational dimensionality reduction of convolutional neural network (CNN) deep features has been proposed. The novelty of the proposed method includes two parts: (1) a local vehicle-color saliency detection method has been proposed to determine the vehicle color region of the vehicle image and exclude the influence of non-color regions on the recognition accuracy; (2) dual-orientational dimensionality reduction strategy has been designed to greatly reduce the dimensionality of deep features that are learnt from CNN, which will greatly mitigate the storage and computational burden of the subsequent processing, while improving the recognition accuracy. Furthermore, linear support vector machine is adopted as the classifier to train the dimensionality reduced features to obtain the recognition model. The experimental results on public dataset demonstrate that the proposed method can achieve superior recognition performance over the state-of-the-arts methods.

Preliminary Assessment of Overweight Mainline Vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Siekmann, Adam; Capps, Gary J; Lascurain, Mary Beth

2011-11-01

The Federal Motor Carrier Safety Administration requested information regarding overweight and oversized vehicle traffic entering inspection stations (ISs) in order to develop strategies for future research efforts and possibly help guide regulatory issues involving overweight commercial motor vehicles (CMVs). For a period of one month, inspection stations in Knox County and Greene County, Tennessee, recorded overweight and oversized vehicles that entered these ISs. During this period, 435 CMVs were recorded using an electronic form filled out by enforcement personnel at the IS. Of the 435 CMVs recorded, 381 had weight information documented with them. The majority (52.2%) of the vehiclesmore » recorded were five-axle combination vehicles, and 50.6% of all the vehicles were permitted to operate above the legal weight limit in Tennessee, which is 80,000 lb for vehicles with five or more axles. Only 16.8% of the CMVs recorded were overweight gross (11.5% of permitted vehicles) and 54.1% were overweight on an axle group. The low percentage of overweight gross CMVs was because only 45 of the vehicles over 80,000 lb. were not permitted. On average, axles that were overweight were 2,000 lb. over the legal limit for an axle or group of axles. Of the vehicles recorded, 172 vehicles were given a North American Standard (NAS) inspection during the assessment. Of those, 69% of the inspections were driver-only inspections (Level III) and only 25% of the inspections had a vehicle component (such as a Level I or Level II). The remaining 6% of inspections did not have valid Aspen numbers; the type of was inspection unknown. Data collected on the types of trailers of each vehicle showed that about half of the recorded CMVs could realistically be given a Level I (full vehicle and driver) inspection; this estimate was solely based on trailer type. Enforcement personnel at ISs without an inspection pit have difficulty fully inspecting certain vehicles due to low clearance below the trailer. Because of this, overweight and oversized vehicles were normally only given a Level III (driver) inspection; thus, little is known about the safety of these vehicles. The out-of-service (OOS) rate of all the inspected vehicles (driver and vehicle inspections) was 18.6%, while the OOS rate for vehicle inspections (Level I and II) was 52.4%. Future work will focus on performing Level I inspections on five-axle combination tractor-trailers and the types of violations that overweight vehicles may have. This research will be conducted in Tennessee and possibly in other states as well.« less

Thermal signature characteristics of vehicle/terrain interaction disturbances: implications for battlefield vehicle classification.

PubMed

Eastes, John W; Mason, George L; Kusinger, Alan E

2004-05-01

Thermal emissivity spectra (8-14 microm) of track impressions/background were determined in conjunction with operation of six military vehicle types, T-72 and M1 Tanks, an M2 Bradley Fighting Vehicle, a 5-ton truck, a D7 tractor, and a High Mobility Multipurpose Wheeled Vehicle (HMMWV), over diverse soil surfaces to determine if vehicle type could be related to track thermal signatures. Results suggest soil compaction and fragmentation/pulverization are primary parameters affecting track signatures and that soil and vehicle/terrain-contact type determine which parameter dominates. Steel-tracked vehicles exert relatively low ground-contact pressure but tend to fragment/pulverize soil more so than do rubber-tired vehicles, which tend mainly to compact. In quartz-rich, lean clay soil tracked vehicles produced impressions with spectral contrast of the quartz reststrahlen features decreased from that of the background. At the same time, 5-ton truck tracks exhibited increased contrast on the same surface, suggesting that steel tracks fragmented soil while rubber tires mainly produced compaction. The structure of materials such as sand and moist clay-rich river sediment makes them less subject to further fragmentation/pulverization; thus, compaction was the main factor affecting signatures in these media, and both tracked and wheeled vehicles created impressions with increased spectral contrast on these surfaces. These results suggest that remotely sensed thermal signatures could differentiate tracked and wheeled vehicles on terrain in many areas of the world of strategic interest. Significant applications include distinguishing visually/spectrally identical lightweight decoys from actual threat vehicles.

Interpretation of laser/multi-sensor data for short range terrain modeling and hazard detection

NASA Technical Reports Server (NTRS)

Messing, B. S.

1980-01-01

A terrain modeling algorithm that would reconstruct the sensed ground images formed by the triangulation scheme, and classify as unsafe any terrain feature that would pose a hazard to a roving vehicle is described. This modeler greatly reduces quantization errors inherent in a laser/sensing system through the use of a thinning algorithm. Dual filters are employed to separate terrain steps from the general landscape, simplifying the analysis of terrain features. A crosspath analysis is utilized to detect and avoid obstacles that would adversely affect the roll of the vehicle. Computer simulations of the rover on various terrains examine the performance of the modeler.

Large school bus design vehicle dimensions

DOT National Transportation Integrated Search

1998-09-01

A survey of United States school bus operators and manufacturers was conducted to define the larger sizes of school buses in regular use. A mid-60 passenger type-c bus (SB-C) and a mid-80 passenger type-D bus (SB-D) were selected as design vehicles. ...

Medical Requirements for Ambulance Design and Equipment. Emergency Health Series.

ERIC Educational Resources Information Center

National Academy of Sciences - National Research Council, Washington, DC. Div. of Medical Sciences.

A vehicle must meet certain specific requirements to be classified as an ambulance if it is to satisfy the demands of the physician in terms of emergency care for which properly trained ambulance attendants can be held responsible. Developed by professional and lay experts for use by automotive designers and manufacturing, this publication would…

Research study: Space vehicle control systems

NASA Technical Reports Server (NTRS)

Likins, P. W.; Longman, R. W.

1979-01-01

From the control point of view, spacecraft are classified into two main groups: those for which the spacecraft is fully defined before the control system is designed; and those for which the control system must be specified before certain interchangeable parts of a multi-purpose spacecraft are selected for future missions. Consideration is given to both classes of problems.

40 CFR 600.315-08 - Classes of comparable automobiles.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Administrator will classify passenger automobiles by car line into one of the following classes based on... as provided in paragraph (a)(3) of this section. (i) Two seaters. A car line shall be classed as “Two Seater” if the majority of the vehicles in that car line have no more than two designated seating...

40 CFR 600.315-08 - Classes of comparable automobiles.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Administrator will classify passenger automobiles by car line into one of the following classes based on... as provided in paragraph (a)(3) of this section. (i) Two seaters. A car line shall be classed as “Two Seater” if the majority of the vehicles in that car line have no more than two designated seating...

40 CFR 600.315-08 - Classes of comparable automobiles.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Administrator will classify passenger automobiles by car line into one of the following classes based on... as provided in paragraph (a)(3) of this section. (i) Two seaters. A car line shall be classed as “Two Seater” if the majority of the vehicles in that car line have no more than two designated seating...

40 CFR 600.315-08 - Classes of comparable automobiles.

Code of Federal Regulations, 2010 CFR

2010-07-01

... accordance with 49 CFR part 523. (1) The Administrator will classify passenger automobiles by car line into... seaters. A car line shall be classed as “Two Seater” if the majority of the vehicles in that car line have...) Minicompact cars. Interior volume index less than 85 cubic feet. (iii) Subcompact cars. Interior volume index...

40 CFR 600.315-08 - Classes of comparable automobiles.

Code of Federal Regulations, 2011 CFR

2011-07-01

... accordance with 49 CFR part 523. (1) The Administrator will classify passenger automobiles by car line into... seaters. A car line shall be classed as “Two Seater” if the majority of the vehicles in that car line have...) Minicompact cars. Interior volume index less than 85 cubic feet. (iii) Subcompact cars. Interior volume index...

The Construction and Practice of Classified Talent Cultivation System Combining with Professional Certification

ERIC Educational Resources Information Center

Jianwei, Yang; Aihua, Zhu; Yuanyuan, Zhang; Chunqing, Zhao

2016-01-01

According to the idea of CDIO engineering education, this paper, combing with professional certification, makes training plan of Urban Rail Transit Vehicles Engineering direction in our school on the basis of research on universities at home and abroad. It strengthens the teaching of basic subjects and increases the weeks of practice link in the…

A road safety performance indicator for vehicle fleet compatibility.

PubMed

Christoph, Michiel; Vis, Martijn Alexander; Rackliff, Lucy; Stipdonk, Henk

2013-11-01

This paper discusses the development and the application of a safety performance indicator which measures the intrinsic safety of a country's vehicle fleet related to fleet composition. The indicator takes into account both the 'relative severity' of individual collisions between different vehicle types, and the share of those vehicle types within a country's fleet. The relative severity is a measure for the personal damage that can be expected from a collision between two vehicles of any type, relative to that of a collision between passenger cars. It is shown how this number can be calculated using vehicle mass only. A sensitivity analysis is performed to study the dependence of the indicator on parameter values and basic assumptions made. The indicator is easy to apply and satisfies the requirements for appropriate safety performance indicators. It was developed in such a way that it specifically scores the intrinsic safety of a fleet due to its composition, without being influenced by other factors, like helmet wearing. For the sake of simplicity, and since the required data is available throughout Europe, the indicator was applied to the relative share of three of the main vehicle types: passenger cars, heavy goods vehicles and motorcycles. Using the vehicle fleet data from 13EU Member States and Norway, the indicator was used to rank the countries' safety performance. The UK was found to perform best in terms of its fleet composition (value is 1.07), while Greece has the worst performance with the highest indicator value (1.41). Copyright © 2013 Elsevier Ltd. All rights reserved.

Distributed data fusion across multiple hard and soft mobile sensor platforms

NASA Astrophysics Data System (ADS)

Sinsley, Gregory

One of the biggest challenges currently facing the robotics field is sensor data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras, radar, laser range finders, chemical sensors, accelerometers, gyros, and global positioning systems. By effectively fusing the data from these sensors, a robot would be able to form a coherent view of its world that could then be used to facilitate both autonomous and intelligent operation. Another distinct fusion problem is that of fusing data from teammates with data from onboard sensors. If an entire team of vehicles has the same worldview they will be able to cooperate much more effectively. Sharing worldviews is made even more difficult if the teammates have different sensor types. The final fusion challenge the robotics field faces is that of fusing data gathered by robots with data gathered by human teammates (soft sensors). Humans sense the world completely differently from robots, which makes this problem particularly difficult. The advantage of fusing data from humans is that it makes more information available to the entire team, thus helping each agent to make the best possible decisions. This thesis presents a system for fusing data from multiple unmanned aerial vehicles, unmanned ground vehicles, and human observers. The first issue this thesis addresses is that of centralized data fusion. This is a foundational data fusion issue, which has been very well studied. Important issues in centralized fusion include data association, classification, tracking, and robotics problems. Because these problems are so well studied, this thesis does not make any major contributions in this area, but does review it for completeness. The chapter on centralized fusion concludes with an example unmanned aerial vehicle surveillance problem that demonstrates many of the traditional fusion methods. The second problem this thesis addresses is that of distributed data fusion. Distributed data fusion is a younger field than centralized fusion. The main issues in distributed fusion that are addressed are distributed classification and distributed tracking. There are several well established methods for performing distributed fusion that are first reviewed. The chapter on distributed fusion concludes with a multiple unmanned vehicle collaborative test involving an unmanned aerial vehicle and an unmanned ground vehicle. The third issue this thesis addresses is that of soft sensor only data fusion. Soft-only fusion is a newer field than centralized or distributed hard sensor fusion. Because of the novelty of the field, the chapter on soft only fusion contains less background information and instead focuses on some new results in soft sensor data fusion. Specifically, it discusses a novel fuzzy logic based soft sensor data fusion method. This new method is tested using both simulations and field measurements. The biggest issue addressed in this thesis is that of combined hard and soft fusion. Fusion of hard and soft data is the newest area for research in the data fusion community; therefore, some of the largest theoretical contributions in this thesis are in the chapter on combined hard and soft fusion. This chapter presents a novel combined hard and soft data fusion method based on random set theory, which processes random set data using a particle filter. Furthermore, the particle filter is designed to be distributed across multiple robots and portable computers (used by human observers) so that there is no centralized failure point in the system. After laying out a theoretical groundwork for hard and soft sensor data fusion the thesis presents practical applications for hard and soft sensor data fusion in simulation. Through a series of three progressively more difficult simulations, some important hard and soft sensor data fusion capabilities are demonstrated. The first simulation demonstrates fusing data from a single soft sensor and a single hard sensor in order to track a car that could be driving normally or erratically. The second simulation adds the extra complication of classifying the type of target to the simulation. The third simulation uses multiple hard and soft sensors, with a limited field of view, to track a moving target and classify it as a friend, foe, or neutral. The final chapter builds on the work done in previous chapters by performing a field test of the algorithms for hard and soft sensor data fusion. The test utilizes an unmanned aerial vehicle, an unmanned ground vehicle, and a human observer with a laptop. The test is designed to mimic a collaborative human and robot search and rescue problem. This test makes some of the most important practical contributions of the thesis by showing that the algorithms that have been developed for hard and soft sensor data fusion are capable of running in real time on relatively simple hardware.

Evaluation of weapons' combustion products in armored vehicles. Appendix C: Summary of descriptive statistics (proc tabulate). Appendix D: Summary of comparative statistics. Final report, 30 September 1986-14 December 1988

DOE Office of Scientific and Technical Information (OSTI.GOV)

Menzies, K.T.; Randel, M.A.; Quill, A.L.

1989-01-01

The U.S. Army Biomedical Research and Development Laboratory defined an extensive research program to address the generation of potentially toxic propellant combustion products in crew compartments of armored vehicles during weapons firing. The major objectives of the research were (1) to determine the presence and concentration of propellant combustion products, (2) to determine potential crew exposure to these combustion products, and (3) to assess the efficacy of field monitoring in armored vehicles. To achieve these goals, air monitoring was conducted in selected armored vehicle types, i.e., M109, M60, M3, M1, at several Army installations. Auxiliary information concerning the specific munitionsmore » fired and the Training and Doctrine Command (TRADOC) or Forces Command (FORSCOM) firing scenarios was collected so that a comparison of pollutant concentrations generated by specific weapons both within vehicle types and between vehicle types could be made.« less

49 CFR 567.5 - Requirements for manufacturers of vehicles manufactured in two or more stages.

Code of Federal Regulations, 2012 CFR

2012-10-01

...) Vehicle Identification Number. (c) Intermediate manufacturers. (1) Except as provided in paragraphs (f... that identified by the incomplete vehicle manufacturer. (v) Vehicle identification number. (d) Final...), and (d)(1), and 49 CFR 568.4(a)(9). (vi) Vehicle identification number. (vii) The type classification...

49 CFR 580.7 - Disclosure of odometer information for leased motor vehicles.

Code of Federal Regulations, 2014 CFR

2014-10-01

... the vehicle, including its make, model, year, and body type, and its vehicle identification number; (7... motor vehicles. 580.7 Section 580.7 Transportation Other Regulations Relating to Transportation... DISCLOSURE REQUIREMENTS § 580.7 Disclosure of odometer information for leased motor vehicles. (a) Before...

49 CFR 580.7 - Disclosure of odometer information for leased motor vehicles.

Code of Federal Regulations, 2010 CFR

2010-10-01

... the vehicle, including its make, model, year, and body type, and its vehicle identification number; (7... motor vehicles. 580.7 Section 580.7 Transportation Other Regulations Relating to Transportation... DISCLOSURE REQUIREMENTS § 580.7 Disclosure of odometer information for leased motor vehicles. (a) Before...

49 CFR 580.7 - Disclosure of odometer information for leased motor vehicles.

Code of Federal Regulations, 2012 CFR

2012-10-01

... the vehicle, including its make, model, year, and body type, and its vehicle identification number; (7... motor vehicles. 580.7 Section 580.7 Transportation Other Regulations Relating to Transportation... DISCLOSURE REQUIREMENTS § 580.7 Disclosure of odometer information for leased motor vehicles. (a) Before...

49 CFR 567.5 - Requirements for manufacturers of vehicles manufactured in two or more stages.

Code of Federal Regulations, 2011 CFR

2011-10-01

...) Vehicle Identification Number. (c) Intermediate manufacturers. (1) Except as provided in paragraphs (f... that identified by the incomplete vehicle manufacturer. (v) Vehicle identification number. (d) Final...), and (d)(1), and 49 CFR 568.4(a)(9). (vi) Vehicle identification number. (vii) The type classification...

49 CFR 567.5 - Requirements for manufacturers of vehicles manufactured in two or more stages.

Code of Federal Regulations, 2013 CFR

2013-10-01

...) Vehicle Identification Number. (c) Intermediate manufacturers. (1) Except as provided in paragraphs (f... that identified by the incomplete vehicle manufacturer. (v) Vehicle identification number. (d) Final...), and (d)(1), and 49 CFR 568.4(a)(9). (vi) Vehicle identification number. (vii) The type classification...

49 CFR 580.7 - Disclosure of odometer information for leased motor vehicles.

Code of Federal Regulations, 2013 CFR

2013-10-01

... the vehicle, including its make, model, year, and body type, and its vehicle identification number; (7... motor vehicles. 580.7 Section 580.7 Transportation Other Regulations Relating to Transportation... DISCLOSURE REQUIREMENTS § 580.7 Disclosure of odometer information for leased motor vehicles. (a) Before...

49 CFR 567.5 - Requirements for manufacturers of vehicles manufactured in two or more stages.

Code of Federal Regulations, 2014 CFR

2014-10-01

...) Vehicle Identification Number. (c) Intermediate manufacturers. (1) Except as provided in paragraphs (f... that identified by the incomplete vehicle manufacturer. (v) Vehicle identification number. (d) Final...), and (d)(1), and 49 CFR 568.4(a)(9). (vi) Vehicle identification number. (vii) The type classification...

49 CFR 384.225 - CDLIS driver recordkeeping.

Code of Federal Regulations, 2011 CFR

2011-10-01

... violations of any State or local law relating to motor vehicle traffic control (other than parking, vehicle weight, or vehicle defect violations) committed in any type of vehicle. (2) The following medical... actions for violations of any State or local law relating to motor vehicle traffic control (other than...

Sensor Architecture and Task Classification for Agricultural Vehicles and Environments

PubMed Central

Rovira-Más, Francisco

2010-01-01

The long time wish of endowing agricultural vehicles with an increasing degree of autonomy is becoming a reality thanks to two crucial facts: the broad diffusion of global positioning satellite systems and the inexorable progress of computers and electronics. Agricultural vehicles are currently the only self-propelled ground machines commonly integrating commercial automatic navigation systems. Farm equipment manufacturers and satellite-based navigation system providers, in a joint effort, have pushed this technology to unprecedented heights; yet there are many unresolved issues and an unlimited potential still to uncover. The complexity inherent to intelligent vehicles is rooted in the selection and coordination of the optimum sensors, the computer reasoning techniques to process the acquired data, and the resulting control strategies for automatic actuators. The advantageous design of the network of onboard sensors is necessary for the future deployment of advanced agricultural vehicles. This article analyzes a variety of typical environments and situations encountered in agricultural fields, and proposes a sensor architecture especially adapted to cope with them. The strategy proposed groups sensors into four specific subsystems: global localization, feedback control and vehicle pose, non-visual monitoring, and local perception. The designed architecture responds to vital vehicle tasks classified within three layers devoted to safety, operative information, and automatic actuation. The success of this architecture, implemented and tested in various agricultural vehicles over the last decade, rests on its capacity to integrate redundancy and incorporate new technologies in a practical way. PMID:22163522

Sensor architecture and task classification for agricultural vehicles and environments.

PubMed

Rovira-Más, Francisco

2010-01-01

The long time wish of endowing agricultural vehicles with an increasing degree of autonomy is becoming a reality thanks to two crucial facts: the broad diffusion of global positioning satellite systems and the inexorable progress of computers and electronics. Agricultural vehicles are currently the only self-propelled ground machines commonly integrating commercial automatic navigation systems. Farm equipment manufacturers and satellite-based navigation system providers, in a joint effort, have pushed this technology to unprecedented heights; yet there are many unresolved issues and an unlimited potential still to uncover. The complexity inherent to intelligent vehicles is rooted in the selection and coordination of the optimum sensors, the computer reasoning techniques to process the acquired data, and the resulting control strategies for automatic actuators. The advantageous design of the network of onboard sensors is necessary for the future deployment of advanced agricultural vehicles. This article analyzes a variety of typical environments and situations encountered in agricultural fields, and proposes a sensor architecture especially adapted to cope with them. The strategy proposed groups sensors into four specific subsystems: global localization, feedback control and vehicle pose, non-visual monitoring, and local perception. The designed architecture responds to vital vehicle tasks classified within three layers devoted to safety, operative information, and automatic actuation. The success of this architecture, implemented and tested in various agricultural vehicles over the last decade, rests on its capacity to integrate redundancy and incorporate new technologies in a practical way.

A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

PubMed Central

Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

2016-01-01

A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

Experimental modeling of the effect of hurricane wind forces on driving behavior and vehicle performance.

PubMed

Rodriguez, Jose M; Codjoe, Julius; Osman, Osama; Ishak, Sherif; Wolshon, Brian

2015-01-01

While traffic planning is important for developing a hurricane evacuation plan, vehicle performance on the roads during extreme weather conditions is critical to the success of the planning process. This novel study investigates the effect of gusty hurricane wind forces on the driving behavior and vehicle performance. The study explores how the parameters of a driving simulator could be modified to reproduce wind loadings experienced by three vehicle types (passenger car, ambulance, and bus) during gusty hurricane winds, through manipulation of appropriate software. Thirty participants were then tested on the modified driving simulator under five wind conditions (ranging from normal to hurricane category 4). The driving performance measures used were heading error and lateral displacement. The results showed that higher wind forces resulted in more varied and greater heading error and lateral displacement. The ambulance had the greatest heading errors and lateral displacements, which were attributed to its large lateral surface area and light weight. Two mathematical models were developed to estimate the heading error and lateral displacements for each of the vehicle types for a given change in lateral wind force. Through a questionnaire, participants felt the different characteristics while driving each vehicle type. The findings of this study demonstrate the valuable use of a driving simulator to model the behavior of different vehicle types and to develop mathematical models to estimate and quantify driving behavior and vehicle performance under hurricane wind conditions.

Classification of Traffic Related Short Texts to Analyse Road Problems in Urban Areas

NASA Astrophysics Data System (ADS)

Saldana-Perez, A. M. M.; Moreno-Ibarra, M.; Tores-Ruiz, M.

2017-09-01

The Volunteer Geographic Information (VGI) can be used to understand the urban dynamics. In the classification of traffic related short texts to analyze road problems in urban areas, a VGI data analysis is done over a social media's publications, in order to classify traffic events at big cities that modify the movement of vehicles and people through the roads, such as car accidents, traffic and closures. The classification of traffic events described in short texts is done by applying a supervised machine learning algorithm. In the approach users are considered as sensors which describe their surroundings and provide their geographic position at the social network. The posts are treated by a text mining process and classified into five groups. Finally, the classified events are grouped in a data corpus and geo-visualized in the study area, to detect the places with more vehicular problems.

A Comprehensive Examination of Heavy Vehicle Emissions Factors

DOT National Transportation Integrated Search

2010-08-01

This report summarizes the findings from reviewing the literature on several topics that are related to heavy vehicle emissions including engine and fuel types, vehicle technologies that can be used to reduce or mitigate vehicle emissions, the factor...

Personalized Vehicle Energy Efficiency & Range Predictor/MyGreenCar

DOE Office of Scientific and Technical Information (OSTI.GOV)

SAXENA, SAMVEG

MyGreenCar provides users with the ability to predict the range capabilities, fuel economy, and operating costs for any vehicle for their individual driving patterns. Users launce the MyGreeCar mobile app on their smartphones to collect their driving patterns over any duration (e.g. serval days, weeks, months, etc) using a phones's locational capabilities. Using vehicle powertrain models for any user-specified vehicle type, MyGreenCar, calculates the component-level energy and power interactions for the chosen vehicle to predict several important quantities, including: 1. For Evs: Alleviating range anxiety 2. Comparing fuel economy, operating costs, and payback time across models and types.

A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study

NASA Astrophysics Data System (ADS)

Onut, S.; Kamber, M. R.; Altay, G.

2014-03-01

Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time.

European type-approval test procedure for evaporative emissions from passenger cars against real-world mobility data from two Italian provinces.

PubMed

Martini, Giorgio; Paffumi, Elena; De Gennaro, Michele; Mellios, Giorgos

2014-07-15

This paper presents an evaluation of the European type-approval test procedure for evaporative emissions from passenger cars based on real-world mobility data. The study relies on two large databases of driving patterns from conventional fuel vehicles collected by means of on-board GPS systems in the Italian provinces of Modena and Firenze. Approximately 28,000 vehicles were monitored, corresponding to approximately 36 million kilometres over a period of one month. The driving pattern of each vehicle was processed to derive the relation between trip length and parking duration, and the rate of occurrence of parking events against multiple evaporative cycles, defined on the basis of the type-approval test procedure as 12-hour diurnal time windows. These results are used as input for an emission simulation model, which calculates the total evaporative emissions given the characteristics of the evaporative emission control system of the vehicle and the ambient temperature conditions. The results suggest that the evaporative emission control system, fitted to the vehicles from Euro 3 step and optimised for the current type-approval test procedure, could not efficiently work under real-world conditions, resulting in evaporative emissions well above the type-approval limit, especially for small size vehicles and warm climate conditions. This calls for a revision of the type-approval test procedure in order to address real-world evaporative emissions. Copyright © 2014. Published by Elsevier B.V.

Evaluation of traffic exhaust contributions to ambient carbonaceous submicron particulate matter in an urban roadside environment in Hong Kong

NASA Astrophysics Data System (ADS)

Lee, Berto Paul; Kwok Keung Louie, Peter; Luk, Connie; Keung Chan, Chak

2017-12-01

Road traffic has significant impacts on air quality particularly in densely urbanized and populated areas where vehicle emissions are a major local source of ambient particulate matter. Engine type (i.e., fuel use) significantly impacts the chemical characteristics of tailpipe emission, and thus the distribution of engine types in traffic impacts measured ambient concentrations. This study provides an estimation of the contribution of vehicles powered by different fuels (gasoline, diesel, LPG) to carbonaceous submicron aerosol mass (PM1) based on ambient aerosol mass spectrometer (AMS) and elemental carbon (EC) measurements and vehicle count data in an urban inner city environment in Hong Kong with the aim to gauge the importance of different engine types to particulate matter burdens in a typical urban street canyon. On an average per-vehicle basis, gasoline vehicles emitted 75 and 93 % more organics than diesel and LPG vehicles, respectively, while EC emissions from diesel vehicles were 45 % higher than those from gasoline vehicles. LPG vehicles showed no appreciable contributions to EC and thus overall represented a small contributor to traffic-related primary ambient PM1 despite their high abundance (˜ 30 %) in the traffic mix. Total carbonaceous particle mass contributions to ambient PM1 from diesel engines were only marginally higher (˜ 4 %) than those from gasoline engines, which is likely an effect of recently introduced control strategies targeted at commercial vehicles and buses. Overall, gasoline vehicles contributed 1.2 µg m-3 of EC and 1.1 µ m-3 of organics, LPG vehicles 0.6 µg m-3 of organics and diesel vehicles 2.0 µg m-3 of EC and 0.7 µg m-3 of organics to ambient carbonaceous PM1.

Vehicles driven by teenagers in their first year of licensure.

PubMed

Williams, Allan F; Leaf, William A; Simons-Morton, Bruce G; Hartos, Jessica L

2006-03-01

to determine access to vehicles, vehicle ownership and its correlates, and types of vehicles driven by teenagers during their first year of licensure. About 3,500 Connecticut teenagers and their parents recruited at DMV offices participated in a study aimed at persuading parents to impose and maintain driving restrictions on their sons and daughters. Telephone interviews with teens and parents, which included questions on vehicles driven, were conducted upon licensure and at intervals throughout the year. The majority of both male and female teens owned vehicles immediately upon licensure. Family income and number of vehicles in the family were associated with early ownership. A year later 74% owned vehicles. Small cars, which provide inferior crash protection, were the most popular vehicle; the percent driving small cars increased from 36% to 42% over the year. About 25% were driving SUVs, pickups, or sports cars, which may increase crash risk for young beginners. One year after licensure, only 35% of teens were driving midsize or large passenger cars, the types of vehicles recommended for them, and about one-third of these vehicles were 10 or more years old. Owners were more likely than non-owners to drive older and smaller vehicles, to drive more miles, do more risky driving, and to have more traffic violations and crashes. Many teenagers in Connecticut were driving vehicles that rank low in crash protection or may increase crash risk. Attention to the young driver problem has been focused primarily on managing driving risks through graduated licensing systems. More attention needs to be given to the vehicles teens drive, and how decisions about vehicle type and ownership are made. Parents exert control over what vehicles their sons and daughters drive, and may benefit from information on how to make choices that better balance cost, safety, and other factors that go into these decisions.

Determinants of seat belt use behaviour: a protocol for a systematic review.

PubMed

Ghaffari, Mohtasham; Armoon, Bahram; Rakhshanderou, Sakineh; Mehrabi, Yadollah; Soori, Hamid; Simsekoghlu, Ozelem; Harooni, Javad

2018-05-03

The use of seat belts could prevent severe collision damage to people in vehicle accidents and keep passengers safe from sustaining serious injuries; for instance, it could prevent passengers from being thrown out of a vehicle after the collision. The current systematic review will identify and analyse the determinants of seat belt use behaviour. We will include qualitative, quantitative and mixed methods studies reporting the acquired data from passengers aged more than 12 years and drivers, from both commercial and personal vehicles. Online databases including MEDLINE/PubMed, Scopus, Web of Science, Embase, Cochrane Database of Systematic Reviews and PsycINFO will be investigated in the current study. Published and available articles will be evaluated according to their titles and abstracts. Published papers conforming to the inclusion criteria will be organised for a complete review. Next, the full text of the remaining articles will be studied independently for eligibility by two authors. The quality of the selected studies will be assessed with appropriate tools. Based on the information obtained from the data extraction, the type of determinants of seat belt use will be classified. Ethics approval is not required, because this is a protocol for a systematic review and no primary data will be collected. The authors will ensure to maintain the rights of the used and included articles in the present systematic review. The findings of this review will be published in a relevant peer-reviewed journal. CRD42017067511. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Machine learning to classify and predict objective and subjective assessments of vehicle dynamics: the case of steering feel

NASA Astrophysics Data System (ADS)

Gil Gómez, Gaspar L.; Nybacka, Mikael; Drugge, Lars; Bakker, Egbert

2018-01-01

Objective measurements and computer-aided engineering simulations cannot be exploited to their full potential because of the high importance of driver feel in vehicle development. Furthermore, despite many studies, it is not easy to identify the relationship between objective metrics (OM) and subjective assessments (SA), a task further complicated by the fact that SA change between drivers and geographical locations or with time. This paper presents a method which uses two artificial neural networks built on top of each other that helps to close this gap. The first network, based solely on OM, generates a map that groups together similar vehicles, thus allowing a classification of measured vehicles to be visualised. This map objectively demonstrates that there exist brand and vehicle class identities. It also foresees the subjective characteristics of a new vehicle, based on its requirements, simulations and measurements. These characteristics are described by the neighbourhood of the new vehicle in the map, which is made up of known vehicles that are accompanied by word-clouds that enhance this description. This forecast is also extended to perform a sensitivity analysis of the tolerances in the requirements, as well as to validate previously published preferred range of steering feel metrics. The results suggest a few new modifications. Finally, the qualitative information given by this measurement-based classification is complemented with a second superimposed network. This network describes a regression surface that enables quantitative predictions, for example the SA of the steering feel of a new vehicle from its OM.

The Biology of Linguistic Expression Impacts Neural Correlates for Spatial Language

PubMed Central

Emmorey, Karen; McCullough, Stephen; Mehta, Sonya; Ponto, Laura L. B.; Grabowski, Thomas J.

2013-01-01

Biological differences between signed and spoken languages may be most evident in the expression of spatial information. PET was used to investigate the neural substrates supporting the production of spatial language in American Sign Language as expressed by classifier constructions, in which handshape indicates object type and the location/motion of the hand iconically depicts the location/motion of a referent object. Deaf native signers performed a picture description task in which they overtly named objects or produced classifier constructions that varied in location, motion, or object type. In contrast to the expression of location and motion, the production of both lexical signs and object type classifier morphemes engaged left inferior frontal cortex and left inferior temporal cortex, supporting the hypothesis that unlike the location and motion components of a classifier construction, classifier handshapes are categorical morphemes that are retrieved via left hemisphere language regions. In addition, lexical signs engaged the anterior temporal lobes to a greater extent than classifier constructions, which we suggest reflects increased semantic processing required to name individual objects compared with simply indicating the type of object. Both location and motion classifier constructions engaged bilateral superior parietal cortex, with some evidence that the expression of static locations differentially engaged the left intraparietal sulcus. We argue that bilateral parietal activation reflects the biological underpinnings of sign language. To express spatial information, signers must transform visual–spatial representations into a body-centered reference frame and reach toward target locations within signing space. PMID:23249348

78 FR 51381 - Early Warning Reporting, Foreign Defect Reporting, and Motor Vehicle and Equipment Recall...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-20

...NHTSA is adopting amendments to certain provisions of the early warning reporting (EWR) rule and the regulations governing motor vehicle and equipment safety recalls. The amendments to the EWR rule require light vehicle manufacturers to specify the vehicle type and the fuel and/or propulsion system type in their reports and add new component categories of stability control systems for light vehicles, buses, emergency vehicles, and medium-heavy vehicle manufacturers, and forward collision avoidance, lane departure prevention, and backover prevention for light vehicle manufacturers. These amendments will also require light vehicle manufacturers to segregate their Service Brake EWR data into two new discrete component categories. In addition, NHTSA will require motor vehicle manufacturers to report their annual list of substantially similar vehicles via the Internet. As to safety recalls, we will now require certain manufacturers to provide a VIN-based recalls lookup tool on their Web site or the Web site of a third party; require the submission of recalls reports and information via the Internet; and require adjustments to the required content of the owner notification letters and envelopes required to be issued to owners and purchasers of recalled vehicles and equipment.

Scoliosis curve type classification using kernel machine from 3D trunk image

NASA Astrophysics Data System (ADS)

Adankon, Mathias M.; Dansereau, Jean; Parent, Stefan; Labelle, Hubert; Cheriet, Farida

2012-03-01

Adolescent idiopathic scoliosis (AIS) is a deformity of the spine manifested by asymmetry and deformities of the external surface of the trunk. Classification of scoliosis deformities according to curve type is used to plan management of scoliosis patients. Currently, scoliosis curve type is determined based on X-ray exam. However, cumulative exposure to X-rays radiation significantly increases the risk for certain cancer. In this paper, we propose a robust system that can classify the scoliosis curve type from non invasive acquisition of 3D trunk surface of the patients. The 3D image of the trunk is divided into patches and local geometric descriptors characterizing the surface of the back are computed from each patch and forming the features. We perform the reduction of the dimensionality by using Principal Component Analysis and 53 components were retained. In this work a multi-class classifier is built with Least-squares support vector machine (LS-SVM) which is a kernel classifier. For this study, a new kernel was designed in order to achieve a robust classifier in comparison with polynomial and Gaussian kernel. The proposed system was validated using data of 103 patients with different scoliosis curve types diagnosed and classified by an orthopedic surgeon from the X-ray images. The average rate of successful classification was 93.3% with a better rate of prediction for the major thoracic and lumbar/thoracolumbar types.

Typing mineral deposits using their associated rocks, grades and tonnages using a probabilistic neural network

USGS Publications Warehouse

Singer, D.A.

2006-01-01

A probabilistic neural network is employed to classify 1610 mineral deposits into 18 types using tonnage, average Cu, Mo, Ag, Au, Zn, and Pb grades, and six generalized rock types. The purpose is to examine whether neural networks might serve for integrating geoscience information available in large mineral databases to classify sites by deposit type. Successful classifications of 805 deposits not used in training - 87% with grouped porphyry copper deposits - and the nature of misclassifications demonstrate the power of probabilistic neural networks and the value of quantitative mineral-deposit models. The results also suggest that neural networks can classify deposits as well as experienced economic geologists. ?? International Association for Mathematical Geology 2006.

0-6763 : accounting for electric vehicles in air quality conformity.

DOT National Transportation Integrated Search

2014-08-01

Electric vehicles (EVs) are broadly defined as : vehicles that obtain at least a part of the energy : required for their propulsion from electricity. This : research focused on the three main types of EVs: : Hybrid electric vehicles. : Plug-i...

49 CFR 566.5 - Requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

.... (c) Description of each type of motor vehicle or of covered equipment manufactured by the manufacturer, including, for motor vehicles, the approximate ranges of gross vehicle weight ratings for each... vehicles, and each manufacturer of covered equipment, shall furnish the information specified in paragraphs...

DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations.

PubMed

Yuan, Yuchen; Shi, Yi; Li, Changyang; Kim, Jinman; Cai, Weidong; Han, Zeguang; Feng, David Dagan

2016-12-23

With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer types/subtypes, which may contribute to more accurate somatic point mutation based cancer classification (SMCC). However in existing SMCC methods, issues like high data sparsity, small volume of sample size, and the application of simple linear classifiers, are major obstacles in improving the classification performance. To address the obstacles in existing SMCC studies, we propose DeepGene, an advanced deep neural network (DNN) based classifier, that consists of three steps: firstly, the clustered gene filtering (CGF) concentrates the gene data by mutation occurrence frequency, filtering out the majority of irrelevant genes; secondly, the indexed sparsity reduction (ISR) converts the gene data into indexes of its non-zero elements, thereby significantly suppressing the impact of data sparsity; finally, the data after CGF and ISR is fed into a DNN classifier, which extracts high-level features for accurate classification. Experimental results on our curated TCGA-DeepGene dataset, which is a reformulated subset of the TCGA dataset containing 12 selected types of cancer, show that CGF, ISR and DNN all contribute in improving the overall classification performance. We further compare DeepGene with three widely adopted classifiers and demonstrate that DeepGene has at least 24% performance improvement in terms of testing accuracy. Based on deep learning and somatic point mutation data, we devise DeepGene, an advanced cancer type classifier, which addresses the obstacles in existing SMCC studies. Experiments indicate that DeepGene outperforms three widely adopted existing classifiers, which is mainly attributed to its deep learning module that is able to extract the high level features between combinatorial somatic point mutations and cancer types.

Alternative Fuels Data Center

Science.gov Websites

, certain buses, or commercial vehicles that are powered by an alternative fuel, if the vehicles obtain an (GVW) Type of Vehicle Decal Fee 18,000 pounds (lbs.) or less Passenger, School Bus, or Commercial $75 vehicles, buses, or commercial motor vehicles that are powered by compressed natural gas (CNG), liquefied

Colorado Rules and Regulations Governing Operation of School Transportation Vehicles.

ERIC Educational Resources Information Center

Colorado State Dept. of Education, Denver. Office of Field Services.

This document contains the text of the rules and regulations, adopted in 1972 and later amended, governing the operation of student transportation vehicles in the state of Colorado. They define the kinds of vehicles that qualify as school transportation vehicles, outline the requirements for vehicle operator's examination, describe the types of…

Built environment effects on cyclist injury severity in automobile-involved bicycle crashes.

PubMed

Chen, Peng; Shen, Qing

2016-01-01

This analysis uses a generalized ordered logit model and a generalized additive model to estimate the effects of built environment factors on cyclist injury severity in automobile-involved bicycle crashes, as well as to accommodate possible spatial dependence among crash locations. The sample is drawn from the Seattle Department of Transportation bicycle collision profiles. This study classifies the cyclist injury types as property damage only, possible injury, evident injury, and severe injury or fatality. Our modeling outcomes show that: (1) injury severity is negatively associated with employment density; (2) severe injury or fatality is negatively associated with land use mixture; (3) lower likelihood of injuries is observed for bicyclists wearing reflective clothing; (4) improving street lighting can decrease the likelihood of cyclist injuries; (5) posted speed limit is positively associated with the probability of evident injury and severe injury or fatality; (6) older cyclists appear to be more vulnerable to severe injury or fatality; and (7) cyclists are more likely to be severely injured when large vehicles are involved in crashes. One implication drawn from this study is that cities should increase land use mixture and development density, optimally lower posted speed limits on streets with both bikes and motor vehicles, and improve street lighting to promote bicycle safety. In addition, cyclists should be encouraged to wear reflective clothing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integrated use of spatial and semantic relationships for extracting road networks from floating car data

NASA Astrophysics Data System (ADS)

Li, Jun; Qin, Qiming; Xie, Chao; Zhao, Yue

2012-10-01

The update frequency of digital road maps influences the quality of road-dependent services. However, digital road maps surveyed by probe vehicles or extracted from remotely sensed images still have a long updating circle and their cost remain high. With GPS technology and wireless communication technology maturing and their cost decreasing, floating car technology has been used in traffic monitoring and management, and the dynamic positioning data from floating cars become a new data source for updating road maps. In this paper, we aim to update digital road maps using the floating car data from China's National Commercial Vehicle Monitoring Platform, and present an incremental road network extraction method suitable for the platform's GPS data whose sampling frequency is low and which cover a large area. Based on both spatial and semantic relationships between a trajectory point and its associated road segment, the method classifies each trajectory point, and then merges every trajectory point into the candidate road network through the adding or modifying process according to its type. The road network is gradually updated until all trajectories have been processed. Finally, this method is applied in the updating process of major roads in North China and the experimental results reveal that it can accurately derive geometric information of roads under various scenes. This paper provides a highly-efficient, low-cost approach to update digital road maps.

40 CFR 600.209-08 - Calculation of vehicle-specific 5-cycle fuel economy values for a model type.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Calculation of vehicle-specific 5-cycle fuel economy values for a model type. 600.209-08 Section 600.209-08 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) ENERGY POLICY FUEL ECONOMY AND CARBON-RELATED EXHAUST EMISSIONS OF MOTOR VEHICLES Fuel Economy Regulations fo...

Nephrocalcinosis as adult presentation of Bartter syndrome type II.

PubMed

Huang, L; Luiken, G P M; van Riemsdijk, I C; Petrij, F; Zandbergen, A A M; Dees, A

2014-02-01

Bartter syndrome consists a group of rare autosomal-recessive renal tubulopathies characterised by renal salt wasting, hypokalaemic metabolic alkalosis, hypercalciuria and hyperreninaemic hyperaldosteronism. It is classified into five types. Mutations in the KCNJ1 gene (classified as type II) usually cause the neonatal form of Bartter syndrome. We describe an adult patient with a homozygous KCNJ1 mutation resulting in a remarkably mild phenotype of neonatal type Bartter syndrome.

Simvastatin reverses podocyte injury but not mesangial expansion in early stage type 2 diabetes mellitus.

PubMed

Wei, P; Grimm, P R; Settles, D C; Balwanz, C R; Padanilam, B J; Sansom, S C

2009-01-01

Statins may confer renal protection in a variety of glomerular diseases, including diabetic nephropathy (DN). However, various glomerular lesions have different etiologies and may have different responses to statins. This study was performed to determine the differential effects of simvastatin (SMV) on glomerular pathology including mesangial expansion and podocyte injury in a mouse model of early stage type 2 diabetes mellitus (DM). Type 2 DM was induced in male C57BL/6 mice by feeding a high fat diet (HF; 45 kcal% fat). After 22 weeks, one group of HF mice was treated with SMV (HF-SMV; 7 mug/day/g BW) and another group was treated with vehicle (HF-vehicle) for 4 weeks via osmotic mini-pump. A third group served as age-matched normal diet vehicle controls (ND-vehicle; 10 kcal% fat). At the end of treatment, glomerular morphology was evaluated in a blind manner to determine the progression of DN. Body weight, blood glucose, insulin, HDL-cholesterol and triglycerides, but not LDL-cholesterol, were increased in HF mice. Over the course of treatment, the 24-hour urinary albumin excretion (UAE) was unchanged in ND-vehicle. HF mice exhibited elevated UAE, which decreased with SMV, but was unchanged with vehicle. The absolute mesangial volume and the relative mesangial volume per glomerular volume increased in HF-vehicle and remained elevated with SMV treatment. The immuno-staining of nephrin, a protein marker of the integrity of podocyte slit diaphragms, was decreased in HF-vehicle; however, the nephrin quantity of the HF-SMV group was not different from ND-vehicle. It is concluded that SMV reverses podocyte damage, but does not affect mesangial expansion in the kidneys of early stage proteinuria of type 2 DM.

The design of a comprehensive microsimulator of household vehicle fleet composition, utilization, and evolution.

DOT National Transportation Integrated Search

2012-01-01

The report describes a comprehensive vehicle fleet composition, utilization, and evolution : simulator that can be used to forecast household vehicle ownership and mileage by type of : vehicle over time. The components of the simulator are developed ...

Demonstration of an ethane spectrometer for methane source identification.

PubMed

Yacovitch, Tara I; Herndon, Scott C; Roscioli, Joseph R; Floerchinger, Cody; McGovern, Ryan M; Agnese, Michael; Pétron, Gabrielle; Kofler, Jonathan; Sweeney, Colm; Karion, Anna; Conley, Stephen A; Kort, Eric A; Nähle, Lars; Fischer, Marc; Hildebrandt, Lars; Koeth, Johannes; McManus, J Barry; Nelson, David D; Zahniser, Mark S; Kolb, Charles E

2014-07-15

Methane is an important greenhouse gas and tropospheric ozone precursor. Simultaneous observation of ethane with methane can help identify specific methane source types. Aerodyne Ethane-Mini spectrometers, employing recently available mid-infrared distributed feedback tunable diode lasers (DFB-TDL), provide 1 s ethane measurements with sub-ppb precision. In this work, an Ethane-Mini spectrometer has been integrated into two mobile sampling platforms, a ground vehicle and a small airplane, and used to measure ethane/methane enhancement ratios downwind of methane sources. Methane emissions with precisely known sources are shown to have ethane/methane enhancement ratios that differ greatly depending on the source type. Large differences between biogenic and thermogenic sources are observed. Variation within thermogenic sources are detected and tabulated. Methane emitters are classified by their expected ethane content. Categories include the following: biogenic (<0.2%), dry gas (1-6%), wet gas (>6%), pipeline grade natural gas (<15%), and processed natural gas liquids (>30%). Regional scale observations in the Dallas/Fort Worth area of Texas show two distinct ethane/methane enhancement ratios bridged by a transitional region. These results demonstrate the usefulness of continuous and fast ethane measurements in experimental studies of methane emissions, particularly in the oil and natural gas sector.

Epsilon toxin: a fascinating pore-forming toxin.

PubMed

Popoff, Michel R

2011-12-01

Epsilon toxin (ETX) is produced by strains of Clostridium perfringens classified as type B or type D. ETX belongs to the heptameric β-pore-forming toxins including aerolysin and Clostridium septicum alpha toxin, which are characterized by the formation of a pore through the plasma membrane of eukaryotic cells consisting in a β-barrel of 14 amphipatic β strands. By contrast to aerolysin and C. septicum alpha toxin, ETX is a much more potent toxin and is responsible for enterotoxemia in animals, mainly sheep. ETX induces perivascular edema in various tissues and accumulates in particular in the kidneys and brain, where it causes edema and necrotic lesions. ETX is able to pass through the blood-brain barrier and stimulate the release of glutamate, which accounts for the symptoms of nervous excitation observed in animal enterotoxemia. At the cellular level, ETX causes rapid swelling followed by cell death involving necrosis. The precise mode of action of ETX remains to be determined. ETX is a powerful toxin, however, it also represents a unique tool with which to vehicle drugs into the central nervous system or target glutamatergic neurons. © 2011 The Author Journal compilation © 2011 FEBS.

47 CFR 32.2112 - Motor vehicles.

Code of Federal Regulations, 2010 CFR

2010-10-01

... FOR TELECOMMUNICATIONS COMPANIES Instructions for Balance Sheet Accounts § 32.2112 Motor vehicles. This account shall include the original cost of motor vehicles of the type which are designed and...

Measurement of in-vehicle volatile organic compounds under static conditions.

PubMed

You, Ke-wei; Ge, Yun-shan; Hu, Bin; Ning, Zhan-wu; Zhao, Shou-tang; Zhang, Yan-ni; Xie, Peng

2007-01-01

The types and quantities of volatile organic compounds (VOCs) inside vehicles have been determined in one new vehicle and two old vehicles under static conditions using the Thermodesorber-Gas Chromatograph/Mass Spectrometer (TD-GC/MS). Air sampling and analysis was conducted under the requirement of USEPA Method TO-17. A room-size, environment test chamber was utilized to provide stable and accurate control of the required environmental conditions (temperature, humidity, horizontal and vertical airflow velocity, and background VOCs concentration). Static vehicle testing demonstrated that although the amount of total volatile organic compounds (TVOC) detected within each vehicle was relatively distinct (4940 microg/m3 in the new vehicle A, 1240 microg/m3 in used vehicle B, and 132 microg/m3 in used vehicle C), toluene, xylene, some aromatic compounds, and various C7-C12 alkanes were among the predominant VOC species in all three vehicles tested. In addition, tetramethyl succinonitrile, possibly derived from foam cushions was detected in vehicle B. The types and quantities of VOCs varied considerably according to various kinds of factors, such as, vehicle age, vehicle model, temperature, air exchange rate, and environment airflow velocity. For example, if the airflow velocity increases from 0.1 m/s to 0.7 m/s, the vehicle's air exchange rate increases from 0.15 h(-1) to 0.67 h(-1), and in-vehicle TVOC concentration decreases from 1780 to 1201 microg/m3.

Object Classification Based on Analysis of Spectral Characteristics of Seismic Signal Envelopes

NASA Astrophysics Data System (ADS)

Morozov, Yu. V.; Spektor, A. A.

2017-11-01

A method for classifying moving objects having a seismic effect on the ground surface is proposed which is based on statistical analysis of the envelopes of received signals. The values of the components of the amplitude spectrum of the envelopes obtained applying Hilbert and Fourier transforms are used as classification criteria. Examples illustrating the statistical properties of spectra and the operation of the seismic classifier are given for an ensemble of objects of four classes (person, group of people, large animal, vehicle). It is shown that the computational procedures for processing seismic signals are quite simple and can therefore be used in real-time systems with modest requirements for computational resources.

Volatile organic compounds (VOCs) source profiles of on-road vehicle emissions in China.

PubMed

Hong-Li, Wang; Sheng-Ao, Jing; Sheng-Rong, Lou; Qing-Yao, Hu; Li, Li; Shi-Kang, Tao; Cheng, Huang; Li-Ping, Qiao; Chang-Hong, Chen

2017-12-31

Volatile Organic Compounds (VOCs) source profiles of on-road vehicles were widely studied as their critical roles in VOCs source apportionment and abatement measures in megacities. Studies of VOCs source profiles from on-road motor vehicles from 2001 to 2016 were summarized in this study, with a focus on the comparisons among different studies and the potential impact of different factors. Generally, non-methane hydrocarbons dominated the source profile of on-road vehicle emissions. Carbonyls, potential important components of vehicle emission, were seldom considered in VOCs emissions of vehicles in the past and should be paid more attention to in further study. VOCs source profiles showed some variations among different studies, and 6 factors were extracted and studied due to their impact to VOCs source profile of on-road vehicles. Vehicle types, being dependent on engine types, and fuel types were two dominant factors impacting VOCs sources profiles of vehicles. In comparison, impacts of ignitions, driving conditions and accumulated mileage were mainly due to their influence on the combustion efficiency. An opening and interactive database of VOCs from vehicle emissions was critically essential in future, and mechanisms of sharing and inputting relative research results should be formed to encourage researchers join the database establishment. Correspondingly, detailed quality assurance and quality control procedures were also very important, which included the information of test vehicles and test methods as detailed as possible. Based on the community above, a better uncertainty analysis could be carried out for the VOCs emissions profiles, which was critically important to understand the VOCs emission characteristics of the vehicle emissions. Copyright © 2017 Elsevier B.V. All rights reserved.

[Research on carbon reduction potential of electric vehicles for low-carbon transportation and its influencing factors].

PubMed

Shi, Xiao-Qing; Li, Xiao-Nuo; Yang, Jian-Xin

2013-01-01

Transportation is the key industry of urban energy consumption and carbon emissions. The transformation of conventional gasoline vehicles to new energy vehicles is an important initiative to realize the goal of developing low-carbon city through energy saving and emissions reduction, while electric vehicles (EV) will play an important role in this transition due to their advantage in energy saving and lower carbon emissions. After reviewing the existing researches on energy saving and emissions reduction of electric vehicles, this paper analyzed the factors affecting carbon emissions reduction. Combining with electric vehicles promotion program in Beijing, the paper analyzed carbon emissions and reduction potential of electric vehicles in six scenarios using the optimized energy consumption related carbon emissions model from the perspective of fuel life cycle. The scenarios included power energy structure, fuel type (energy consumption per 100 km), car type (CO2 emission factor of fuel), urban traffic conditions (speed), coal-power technologies and battery type (weight, energy efficiency). The results showed that the optimized model was able to estimate carbon emissions caused by fuel consumption more reasonably; electric vehicles had an obvious restrictive carbon reduction potential with the fluctuation of 57%-81.2% in the analysis of six influencing factors, while power energy structure and coal-power technologies play decisive roles in life-cycle carbon emissions of electric vehicles with the reduction potential of 78.1% and 81.2%, respectively. Finally, some optimized measures were proposed to reduce transport energy consumption and carbon emissions during electric vehicles promotion including improving energy structure and coal technology, popularizing energy saving technologies and electric vehicles, accelerating the battery R&D and so on. The research provides scientific basis and methods for the policy development for the transition of new energy vehicles in low-carbon transport.

Evaluation of two transport aircraft and several ground test vehicle friction measurements obtained for various runway surface types and conditions. A summary of test results from joint FAA/NASA Runway Friction Program

NASA Technical Reports Server (NTRS)

Yager, Thomas J.; Vogler, William A.; Baldasare, Paul

1990-01-01

Tests with specially instrumented NASA Boeing 737 and 727 aircraft together with several different ground friction measuring devices were conducted for a variety of runway surface types and conditions. These tests are part of joint FAA/NASA Aircraft/Ground Vehicle Runway Friction Program aimed at obtaining a better understanding of aircraft ground handling performance under adverse weather conditions and defining relationships between aircraft and ground vehicle tire friction measurements. Aircraft braking performance on dry, wet, snow and ice-covered runway conditions is discussed as well as ground vehicle friction data obtained under similar runway conditions. For a given contaminated runway surface condition, the correlation between ground vehicles and aircraft friction data is identified. The influence of major test parameters on friction measurements such as speed, test tire characteristics, type and amount of surface contaminant, and ambient temperature are discussed. The effect of surface type on wet friction levels is also evaluated from comparative data collected on grooved and ungrooved concrete and asphalt surfaces.

28 CFR 29.9 - Motor vehicles for hire.

Code of Federal Regulations, 2010 CFR

2010-07-01

... provision in the rental or lease agreement must utilize a larger font than the standard type in the... possession of the vehicle. (b) The notice required by this section shall be printed in bold type in the...

78 FR 16051 - Vehicle/Track Interaction Safety Standards; High-Speed and High Cant Deficiency Operations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-13

...FRA is amending the Track Safety Standards and Passenger Equipment Safety Standards to promote the safe interaction of rail vehicles with the track over which they operate under a variety of conditions at speeds up to 220 m.p.h. The final rule revises standards for track geometry and safety limits for vehicle response to track conditions, enhances vehicle/track qualification procedures, and adds flexibility for permitting high cant deficiency train operations through curves at conventional speeds. The rule accounts for a range of vehicle types that are currently in operation, as well as vehicle types that may likely be used in future high-speed or high cant deficiency rail operations, or both. The rule is based on the results of simulation studies designed to identify track geometry irregularities associated with unsafe wheel/rail forces and accelerations, thorough reviews of vehicle qualification and revenue service test data, and consideration of international practices.

Alternative Fuels Data Center

Science.gov Websites

continuous regulations and may exempt certain vehicle types from the occupancy requirements.2 Often referred number of states use HOV lane exemptions to encourage acquisition of certain vehicle types, like AFVs, to specific types of AFVs to use this exemption. Some states only exempt PEVs and allow HEVs discounted access

A more accurate method using MOVES (Motor Vehicle Emission Simulator) to estimate emission burden for regional-level analysis.

PubMed

Liu, Xiaobo

2015-07-01

The U.S. Environmental Protection Agency's (EPA) Motor Vehicle Emission Simulator (MOVES) is required by the EPA to replace Mobile 6 as an official on-road emission model. Incorporated with annual vehicle mile traveled (VMT) by Highways Performance Monitoring System (HPMS) vehicle class, MOVES allocates VMT from HPMS to MOVES source (vehicle) types and calculates emission burden by MOVES source type. However, the calculated running emission burden by MOVES source type may be deviated from the actual emission burden because of MOVES source population, specifically the population fraction by MOVES source type in HPMS vehicle class. The deviation is also the result of the use of the universal set of parameters, i.e., relative mileage accumulation rate (relativeMAR), packaged in MOVES default database. This paper presents a novel approach by adjusting the relativeMAR to eliminate the impact of MOVES source population on running exhaust emission and to keep start and evaporative emissions unchanged for both MOVES2010b and MOVES2014. Results from MOVES runs using this approach indicated significant improvements on VMT distribution and emission burden estimation for each MOVES source type. The deviation of VMT by MOVES source type is minimized by using this approach from 12% to less than 0.05% for MOVES2010b and from 50% to less than 0.2% for MOVES2014 except for MOVES source type 53. Source type 53 still remains about 30% variation. The improvement of VMT distribution results in the elimination of emission burden deviation for each MOVES source type. For MOVES2010b, the deviation of emission burdens decreases from -12% for particulate matter less than 2.5 μm (PM2.5) and -9% for carbon monoxide (CO) to less than 0.002%. For MOVES2014, it drops from 80% for CO and 97% for PM2.5 to 0.006%. This approach is developed to more accurately estimate the total emission burdens using EPA's MOVES, both MOVES2010b and MOVES2014, by redistributing vehicle mile traveled (VMT) by Highways Performance Monitoring System (HPMS) class to MOVES source type on the basis of comprehensive traffic study, local link-by-link VMT broken down into MOVES source type.

Understanding, Classifying, and Selecting Environmentally Acceptable Hydraulic Fluids

DTIC Science & Technology

2016-08-01

installed in land facilities or off- road vehicles such as excavators, bulldozers, backhoes, etc.), while others are installed on floating plants...and oily bilge tanks for the collection and proper disposal of oil- contaminated bilge water • Performing routine maintenance , including regular...regulations. Maintenance of machinery systems containing EA hydraulic fluids must strictly follow the hydraulic fluid manufacturer’s recommendations

Detecting Solenoid Valve Deterioration in In-Use Electronic Diesel Fuel Injection Control Systems

PubMed Central

Tsai, Hsun-Heng; Tseng, Chyuan-Yow

2010-01-01

The diesel engine is the main power source for most agricultural vehicles. The control of diesel engine emissions is an important global issue. Fuel injection control systems directly affect fuel efficiency and emissions of diesel engines. Deterioration faults, such as rack deformation, solenoid valve failure, and rack-travel sensor malfunction, are possibly in the fuel injection module of electronic diesel control (EDC) systems. Among these faults, solenoid valve failure is most likely to occur for in-use diesel engines. According to the previous studies, this failure is a result of the wear of the plunger and sleeve, based on a long period of usage, lubricant degradation, or engine overheating. Due to the difficulty in identifying solenoid valve deterioration, this study focuses on developing a sensor identification algorithm that can clearly classify the usability of the solenoid valve, without disassembling the fuel pump of an EDC system for in-use agricultural vehicles. A diagnostic algorithm is proposed, including a feedback controller, a parameter identifier, a linear variable differential transformer (LVDT) sensor, and a neural network classifier. Experimental results show that the proposed algorithm can accurately identify the usability of solenoid valves. PMID:22163597

Active optical sensors for tree stem detection and classification in nurseries.

PubMed

Garrido, Miguel; Perez-Ruiz, Manuel; Valero, Constantino; Gliever, Chris J; Hanson, Bradley D; Slaughter, David C

2014-06-19

Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops.

Detecting solenoid valve deterioration in in-use electronic diesel fuel injection control systems.

PubMed

Tsai, Hsun-Heng; Tseng, Chyuan-Yow

2010-01-01

The diesel engine is the main power source for most agricultural vehicles. The control of diesel engine emissions is an important global issue. Fuel injection control systems directly affect fuel efficiency and emissions of diesel engines. Deterioration faults, such as rack deformation, solenoid valve failure, and rack-travel sensor malfunction, are possibly in the fuel injection module of electronic diesel control (EDC) systems. Among these faults, solenoid valve failure is most likely to occur for in-use diesel engines. According to the previous studies, this failure is a result of the wear of the plunger and sleeve, based on a long period of usage, lubricant degradation, or engine overheating. Due to the difficulty in identifying solenoid valve deterioration, this study focuses on developing a sensor identification algorithm that can clearly classify the usability of the solenoid valve, without disassembling the fuel pump of an EDC system for in-use agricultural vehicles. A diagnostic algorithm is proposed, including a feedback controller, a parameter identifier, a linear variable differential transformer (LVDT) sensor, and a neural network classifier. Experimental results show that the proposed algorithm can accurately identify the usability of solenoid valves.

Dynamic cluster generation for a fuzzy classifier with ellipsoidal regions.

PubMed

Abe, S

1998-01-01

In this paper, we discuss a fuzzy classifier with ellipsoidal regions that dynamically generates clusters. First, for the data belonging to a class we define a fuzzy rule with an ellipsoidal region. Namely, using the training data for each class, we calculate the center and the covariance matrix of the ellipsoidal region for the class. Then we tune the fuzzy rules, i.e., the slopes of the membership functions, successively until there is no improvement in the recognition rate of the training data. Then if the number of the data belonging to a class that are misclassified into another class exceeds a prescribed number, we define a new cluster to which those data belong and the associated fuzzy rule. Then we tune the newly defined fuzzy rules in the similar way as stated above, fixing the already obtained fuzzy rules. We iterate generation of clusters and tuning of the newly generated fuzzy rules until the number of the data belonging to a class that are misclassified into another class does not exceed the prescribed number. We evaluate our method using thyroid data, Japanese Hiragana data of vehicle license plates, and blood cell data. By dynamic cluster generation, the generalization ability of the classifier is improved and the recognition rate of the fuzzy classifier for the test data is the best among the neural network classifiers and other fuzzy classifiers if there are no discrete input variables.

47 CFR 32.2112 - Motor vehicles.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Motor vehicles. 32.2112 Section 32.2112... FOR TELECOMMUNICATIONS COMPANIES Instructions for Balance Sheet Accounts § 32.2112 Motor vehicles. This account shall include the original cost of motor vehicles of the type which are designed and...

47 CFR 32.2112 - Motor vehicles.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 47 Telecommunication 2 2012-10-01 2012-10-01 false Motor vehicles. 32.2112 Section 32.2112... FOR TELECOMMUNICATIONS COMPANIES Instructions for Balance Sheet Accounts § 32.2112 Motor vehicles. This account shall include the original cost of motor vehicles of the type which are designed and...

47 CFR 32.2112 - Motor vehicles.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 2 2014-10-01 2014-10-01 false Motor vehicles. 32.2112 Section 32.2112... FOR TELECOMMUNICATIONS COMPANIES Instructions for Balance Sheet Accounts § 32.2112 Motor vehicles. This account shall include the original cost of motor vehicles of the type which are designed and...

47 CFR 32.2112 - Motor vehicles.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 2 2013-10-01 2013-10-01 false Motor vehicles. 32.2112 Section 32.2112... FOR TELECOMMUNICATIONS COMPANIES Instructions for Balance Sheet Accounts § 32.2112 Motor vehicles. This account shall include the original cost of motor vehicles of the type which are designed and...

16 CFR 309.21 - Labeling requirements for used covered vehicles.

Code of Federal Regulations, 2012 CFR

2012-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figure 6. (c) Type size and setting... vehicles. 309.21 Section 309.21 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

16 CFR 309.21 - Labeling requirements for used covered vehicles.

Code of Federal Regulations, 2013 CFR

2013-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figure 6. (c) Type size and setting... vehicles. 309.21 Section 309.21 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

16 CFR 309.20 - Labeling requirements for new covered vehicles.

Code of Federal Regulations, 2013 CFR

2013-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figures 4, 5, and 5.1. (c) Type... vehicles. 309.20 Section 309.20 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

16 CFR 309.20 - Labeling requirements for new covered vehicles.

Code of Federal Regulations, 2012 CFR

2012-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figures 4, 5, and 5.1. (c) Type... vehicles. 309.20 Section 309.20 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

The Mission Accessibility of Near-Earth Asteroids

NASA Technical Reports Server (NTRS)

Barbee, Brent W.; Abell, Paul A.; Adamo, Daniel R.; Mazanek, Daniel D.; Johnson, Lindley N.; Yeomans, Donald K.; Chodas, Paul W.; Chamberlin, Alan B.; Benner, Lance A. M.; Taylor, Patrick;

Prediction of Driver’s Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques

PubMed Central

Kim, Il-Hwan; Bong, Jae-Hwan; Park, Jooyoung; Park, Shinsuk

2017-01-01

Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS) is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver’s intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver’s intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN) models, and the augmented information is fed to a support vector machine (SVM) to detect the driver’s intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver’s intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics. PMID:28604582

Propulsion and stabilization system for magnetically levitated vehicles

DOEpatents

Coffey, Howard T.

1993-06-29

A propulsion and stabilization system for an inductive repulsion type magnetically levitated vehicle which is propelled and stabilized by a system which includes propulsion windings mounted above and parallel to vehicle-borne suspension magnets. A linear synchronous motor is part of the vehicle guideway and is mounted above and parallel to superconducting magnets attached to the magnetically levitated vehicle.

NREL's EVI-Pro Lite Tool Paves the Way for Future Electric Vehicle

Science.gov Websites

Electric Vehicle Infrastructure Planning NREL's EVI-Pro Lite Tool Paves the Way for Future Electric Vehicle electric vehicle charging station To assist state and local governments anticipating this type of growth in simplified version of the Electric Vehicle Infrastructure Projection Tool (EVI-Pro) model. Combining a sleek

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dowdy, M.; Burke, A.; Schneider, H.

Fuel economy, exhaust emissions, multifuel capability, advanced materials and cost/manufacturability for both conventional and advanced alternative power systems were assessed. To insure valid comparisons of vehicles with alternative power systems, the concept of an Otto-Engine-Equivalent (OEE) vehicle was utilized. Each engine type was sized to provide equivalent vehicle performance. Sensitivity to different performance criteria was evaluated. Fuel economy projections are made for each engine type considering both the legislated emission standards and possible future emissions requirements.

Application of an Integrated HPC Reliability Prediction Framework to HMMWV Suspension System

DTIC Science & Technology

2010-09-13

model number M966 (TOW Missle Carrier, Basic Armor without weapons), since they were available. Tires used for all simulations were the bias-type...vehicle fleet, including consideration of all kinds of uncertainty, especially including model uncertainty. The end result will be a tool to use...building an adequate vehicle reliability prediction framework for military vehicles is the accurate modeling of the integration of various types of

Space vehicle concepts

NASA Technical Reports Server (NTRS)

Tucker, Michael; Meredith, Oliver; Brothers, Bobby

1986-01-01

Several concepts of chemical-propulsion Space Vehicles (SVs) for manned Mars landing missions are presented. For vehicle sizing purposes, several specific missions were chosen from opportunities in the late 1990's and early 2000's, and a vehicle system concept is then described which is applicable to the full range of missions and opportunities available. In general, missions utilizing planetary opposition alignments can be done with smaller vehicles than those utilizing planetary opposition alignments. The conjunction missions have a total mission time of about 3 years, including a required stay-time of about 60 days. Both types of missions might be desirable during a Mars program, the opposition type for early low-risk missions and/or for later unmanned cargo missions, and the conjunction type for more extensive science/exploration missions and/or for Mars base activities. Since the opposition missions appeared to drive the SV size more severely, there were probably more cases examined for them. Some of the concepts presented utilize all-propulsive braking, some utilize and all aerobraking approach, and some are hybrids. Weight statements are provided for various cases. Most of the work was done on 0-g vehicle concepts, but partial-g and 1-g concepts are also provided and discussed. Several options for habitable elements are shown, such as large-diameter modules and space station (SS) types of modules.

Determining the frequency of open windows in motor vehicles: a pilot study using a video camera in Houston, Texas during high temperature conditions.

PubMed

Long, Tom; Johnson, Ted; Ollison, Will

2002-05-01

Researchers have developed a variety of computer-based models to estimate population exposure to air pollution. These models typically estimate exposures by simulating the movement of specific population groups through defined microenvironments. Exposures in the motor vehicle microenvironment are significantly affected by air exchange rate, which in turn is affected by vehicle speed, window position, vent status, and air conditioning use. A pilot study was conducted in Houston, Texas, during September 2000 for a specific set of weather, vehicle speed, and road type conditions to determine whether useful information on the position of windows, sunroofs, and convertible tops could be obtained through the use of video cameras. Monitoring was conducted at three sites (two arterial roads and one interstate highway) on the perimeter of Harris County located in or near areas not subject to mandated Inspection and Maintenance programs. Each site permitted an elevated view of vehicles as they proceeded through a turn, thereby exposing all windows to the stationary video camera. Five videotaping sessions were conducted over a two-day period in which the Heat Index (HI)-a function of temperature and humidity-varied from 80 to 101 degrees F and vehicle speed varied from 30 to 74 mph. The resulting videotapes were processed to create a master database listing vehicle-specific data for site location, date, time, vehicle type (e.g., minivan), color, window configuration (e.g., four windows and sunroof), number of windows in each of three position categories (fully open, partially open, and closed), HI, and speed. Of the 758 vehicles included in the database, 140 (18.5 percent) were labeled as "open," indicating a window, sunroof, or convertible top was fully or partially open. The results of a series of stepwise linear regression analyses indicated that the probability of a vehicle in the master database being "open" was weakly affected by time of day, vehicle type, vehicle color, vehicle speed, and HI. In particular, open windows occurred more frequently when vehicle speed was less than 50 mph during periods when HI exceeded 99.9 degrees F and the vehicle was a minivan or passenger van. Overall, the pilot study demonstrated that data on factors affecting vehicle window position could be acquired through a relatively simple experimental protocol using a single video camera. Limitations of the study requiring further research include the inability to determine the status of the vehicle air conditioning system; lack of a wide range of weather, vehicle speed, and road type conditions; and the need to exclude some vehicles from statistical analyses due to ambiguous window positions.

Validity of PALMS GPS scoring of active and passive travel compared with SenseCam.

PubMed

Carlson, Jordan A; Jankowska, Marta M; Meseck, Kristin; Godbole, Suneeta; Natarajan, Loki; Raab, Fredric; Demchak, Barry; Patrick, Kevin; Kerr, Jacqueline

2015-03-01

The objective of this study is to assess validity of the personal activity location measurement system (PALMS) for deriving time spent walking/running, bicycling, and in vehicle, using SenseCam (Microsoft, Redmond, WA) as the comparison. Forty adult cyclists wore a Qstarz BT-Q1000XT GPS data logger (Qstarz International Co., Taipei, Taiwan) and SenseCam (camera worn around the neck capturing multiple images every minute) for a mean time of 4 d. PALMS used distance and speed between global positioning system (GPS) points to classify whether each minute was part of a trip (yes/no), and if so, the trip mode (walking/running, bicycling, or in vehicle). SenseCam images were annotated to create the same classifications (i.e., trip yes/no and mode). Contingency tables (2 × 2) and confusion matrices were calculated at the minute level for PALMS versus SenseCam classifications. Mixed-effects linear regression models estimated agreement (mean differences and intraclass correlation coefficients) between PALMS and SenseCam with regard to minutes/day in each mode. Minute-level sensitivity, specificity, and negative predictive value were ≥88%, and positive predictive value was ≥75% for non-mode-specific trip detection. Seventy-two percent to 80% of outdoor walking/running minutes, 73% of bicycling minutes, and 74%-76% of in-vehicle minutes were correctly classified by PALMS. For minutes per day, PALMS had a mean bias (i.e., amount of over or under estimation) of 2.4-3.1 min (11%-15%) for walking/running, 2.3-2.9 min (7%-9%) for bicycling, and 4.3-5 min (15%-17%) for vehicle time. Intraclass correlation coefficients were ≥0.80 for all modes. PALMS has validity for processing GPS data to objectively measure time spent walking/running, bicycling, and in vehicle in population studies. Assessing travel patterns is one of many valuable applications of GPS in physical activity research that can improve our understanding of the determinants and health outcomes of active transportation as well as its effect on physical activity.

Comparative Study of Various Types of Vehicle Detectors

DOT National Transportation Integrated Search

1977-09-01

This report is a comparison between the different types of vehicle detectors and associated equipment. It covers practically all of the presence and motion detectors either being sold commercially or actively researched at this time, and includes rad...

Alternative Fuels Data Center: How Do Propane Vehicles Work?

Science.gov Websites

gasoline vehicles with spark-ignited internal combustion engines. There are two types of propane fuel -injection systems available: vapor and liquid injection. In both types, propane is stored as a liquid in a

77 FR 73458 - Vehicle Technologies Program; Request for Information

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-10

... well as vehicles running on alternative fuels such as electricity, ethanol, natural gas, or biodiesel... a specific type of alternative fuel vehicle (biodiesel, compressed natural gas, E85, and electric...

Transformable descent vehicles

NASA Astrophysics Data System (ADS)

Pichkhadze, K. M.; Finchenko, V. S.; Aleksashkin, S. N.; Ostreshko, B. A.

2016-12-01

This article presents some types of planetary descent vehicles, the shape of which varies in different flight phases. The advantages of such vehicles over those with unchangeable form (from launch to landing) are discussed. It is shown that the use of transformable descent vehicles widens the scope of possible tasks to solve.

Vehicle impact simulation for curb and barrier design : volume 1, impact simulation procedures.

DOT National Transportation Integrated Search

1998-10-01

The objectives of this study were to perform computer simulations of vehicle-curb and vehicle-berm impacts, to characterize : the behavior of a wide range of vehicle types after such impacts, and to produce design and evaluation trajectory data for u...

Modeling and Controls Development of 48V Mild Hybrid Electric Vehicles

EPA Science Inventory

The Advanced Light-Duty Powertrain and Hybrid Analysis tool (ALPHA) was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles. It is a physics-based, forward-looking, full vehicle computer simulator capable of analyzing various vehicle types c...

14 CFR 415.105 - Pre-application consultation.

Code of Federal Regulations, 2010 CFR

2010-01-01

... following information: (1) Launch vehicle. Description of: (i) Launch vehicle; (ii) Any flight termination system; and (iii) All hazards associated with the launch vehicle and any payload, including the type and... Launch Vehicle From a Non-Federal Launch Site § 415.105 Pre-application consultation. (a) An applicant...

14 CFR 415.105 - Pre-application consultation.

Code of Federal Regulations, 2011 CFR

2011-01-01

... following information: (1) Launch vehicle. Description of: (i) Launch vehicle; (ii) Any flight termination system; and (iii) All hazards associated with the launch vehicle and any payload, including the type and... Launch Vehicle From a Non-Federal Launch Site § 415.105 Pre-application consultation. (a) An applicant...

14 CFR 415.105 - Pre-application consultation.

Code of Federal Regulations, 2013 CFR

2013-01-01

... following information: (1) Launch vehicle. Description of: (i) Launch vehicle; (ii) Any flight termination system; and (iii) All hazards associated with the launch vehicle and any payload, including the type and... Launch Vehicle From a Non-Federal Launch Site § 415.105 Pre-application consultation. (a) An applicant...

14 CFR 415.105 - Pre-application consultation.

Code of Federal Regulations, 2014 CFR

2014-01-01

... following information: (1) Launch vehicle. Description of: (i) Launch vehicle; (ii) Any flight termination system; and (iii) All hazards associated with the launch vehicle and any payload, including the type and... Launch Vehicle From a Non-Federal Launch Site § 415.105 Pre-application consultation. (a) An applicant...

14 CFR 415.105 - Pre-application consultation.

Code of Federal Regulations, 2012 CFR

2012-01-01

... following information: (1) Launch vehicle. Description of: (i) Launch vehicle; (ii) Any flight termination system; and (iii) All hazards associated with the launch vehicle and any payload, including the type and... Launch Vehicle From a Non-Federal Launch Site § 415.105 Pre-application consultation. (a) An applicant...

Factors that influence tractive performance of wheels, tracks, and vehicles

USDA-ARS?s Scientific Manuscript database

Traction of agricultural vehicles and other off-road vehicles is important in allowing these vehicles to perform their desired tasks. This book chapter describes factors affecting the off-road tractive performance of tires and rubber tracks. Tractive performance is affected by soil type, soil cond...

How to select combination operators for fuzzy expert systems using CRI

NASA Technical Reports Server (NTRS)

Turksen, I. B.; Tian, Y.

1992-01-01

A method to select combination operators for fuzzy expert systems using the Compositional Rule of Inference (CRI) is proposed. First, fuzzy inference processes based on CRI are classified into three categories in terms of their inference results: the Expansion Type Inference, the Reduction Type Inference, and Other Type Inferences. Further, implication operators under Sup-T composition are classified as the Expansion Type Operator, the Reduction Type Operator, and the Other Type Operators. Finally, the combination of rules or their consequences is investigated for inference processes based on CRI.

Image acquisition system for traffic monitoring applications

NASA Astrophysics Data System (ADS)

Auty, Glen; Corke, Peter I.; Dunn, Paul; Jensen, Murray; Macintyre, Ian B.; Mills, Dennis C.; Nguyen, Hao; Simons, Ben

1995-03-01

An imaging system for monitoring traffic on multilane highways is discussed. The system, named Safe-T-Cam, is capable of operating 24 hours per day in all but extreme weather conditions and can capture still images of vehicles traveling up to 160 km/hr. Systems operating at different remote locations are networked to allow transmission of images and data to a control center. A remote site facility comprises a vehicle detection and classification module (VCDM), an image acquisition module (IAM) and a license plate recognition module (LPRM). The remote site is connected to the central site by an ISDN communications network. The remote site system is discussed in this paper. The VCDM consists of a video camera, a specialized exposure control unit to maintain consistent image characteristics, and a 'real-time' image processing system that processes 50 images per second. The VCDM can detect and classify vehicles (e.g. cars from trucks). The vehicle class is used to determine what data should be recorded. The VCDM uses a vehicle tracking technique to allow optimum triggering of the high resolution camera of the IAM. The IAM camera combines the features necessary to operate consistently in the harsh environment encountered when imaging a vehicle 'head-on' in both day and night conditions. The image clarity obtained is ideally suited for automatic location and recognition of the vehicle license plate. This paper discusses the camera geometry, sensor characteristics and the image processing methods which permit consistent vehicle segmentation from a cluttered background allowing object oriented pattern recognition to be used for vehicle classification. The image capture of high resolution images and the image characteristics required for the LPRMs automatic reading of vehicle license plates, is also discussed. The results of field tests presented demonstrate that the vision based Safe-T-Cam system, currently installed on open highways, is capable of producing automatic classification of vehicle class and recording of vehicle numberplates with a success rate around 90 percent in a period of 24 hours.

On-road vehicle emission control in Beijing: past, present, and future.

PubMed

Wu, Ye; Wang, Renjie; Zhou, Yu; Lin, Bohong; Fu, Lixin; He, Kebin; Hao, Jiming

2011-01-01

Beijing, the capital of China, has experienced rapid motorization since 1990; a trend that is likely to continue. The growth in vehicles and the corresponding emissions create challenges to improving the urban air quality. In an effort to reduce the impact of vehicle emissions on urban air quality, Beijing has adopted a number of vehicle emission control strategies and policies since the mid 1990 s. These are classified into seven categories: (1) emission control on new vehicles; (2) emission control on in-use vehicles; (3) fuel quality improvements; (4) alternative-fuel and advanced vehicles; (5) economic policies; (6) public transport; and (7) temporal traffic control measures. Many have proven to be successful, such as the Euro emission standards, unleaded gasoline and low sulfur fuel, temporal traffic control measures during the Beijing Olympic Games, etc. Some, however, have been failures, such as the gasoline-to-LPG taxi retrofit program. Thanks to the emission standards for new vehicles as well as other controls, the fleet-average emission rates of CO, HC, NO(X), and PM(10) by each major vehicle category are decreasing over time. For example, gasoline cars decreased fleet-average emission factors by 12.5% for CO, 10.0% for HC, 5.8% for NO(X), and 13.0% for PM(10) annually since 1995, and such a trend is likely to continue. Total emissions for Beijing's vehicle fleet increased from 1995 to 1998. However, they show a clear and steady decrease between 1999 and 2009. In 2009, total emissions of CO, HC, NO(X), and PM(10) were 845,000 t, 121,000 t, 84,000 t, and 3700 t, respectively; with reductions of 47%, 49%, 47%, and 42%, relative to 1998. Beijing has been considered a pioneer in controlling vehicle emissions within China, similar to the role of California to the U.S. The continued rapid growth of vehicles, however, is challenging Beijing's policy-makers.

A Discussion of Aerodynamic Control Effectors (ACEs) for Unmanned Air Vehicles (UAVs)

NASA Technical Reports Server (NTRS)

Wood, Richard M.

2002-01-01

A Reynolds number based, unmanned air vehicle classification structure has been developed which identifies four classes of unmanned air vehicle concepts. The four unmanned air vehicle (UAV) classes are; Micro UAV, Meso UAV, Macro UAV, and Mega UAV. In a similar fashion a labeling scheme for aerodynamic control effectors (ACE) was developed and eleven types of ACE concepts were identified. These eleven types of ACEs were laid out in a five (5) layer scheme. The final section of the paper correlated the various ACE concepts to the four UAV classes and ACE recommendations are offered for future design activities.

A cross-sectional examination of the physical fitness and selected health attributes of recreational all-terrain vehicle riders and off-road motorcyclists.

PubMed

Burr, Jamie F; Jamnik, Veronica; Gledhill, Norman

2010-11-01

The aims of this study were: (1) to characterize selected fitness and health attributes of two types of habitual recreational off-road vehicle riders - off-road motorcyclists and all-terrain vehicle riders; (2) to explore differences among riders in terms of vehicle type, age, and gender; and (3) to compare the fitness and health of riders to population norms and clinical health standards. Canadian off-road riders (n = 141) of both sexes aged 16 years and over were recruited through local and national off-road riding organizations. Anthropometry, fitness, and health measures of off-road motorcycle and all-terrain vehicle riders were compared with population norms, health standards, and physical activity guidelines. Off-road motorcycle riders had above average aerobic fitness (79th percentile), while all-terrain vehicle riders were lower than average (40th percentile). All riders had a healthy blood lipid profile and a low incidence of the metabolic syndrome (12.9%) compared with members of the general population. Off-road motorcycle riders had healthier body composition and fitness than all-terrain vehicle riders; however, the body composition of off-road motorcycle riders was no healthier than that of the general population and all-terrain vehicle riders were worse than the general population. Off-road motorcycle riders had healthier anthropometry and fitness than all-terrain vehicle riders and thus fewer health risk factors for future disease, demonstrating that the physiological profiles of off-road riders are dependent on vehicle type.

The effectiveness of electronic stability control in reducing real-world crashes: a literature review.

PubMed

Ferguson, Susan A

2007-12-01

Electronic stability control (ESC) is designed to help drivers maintain heading control of their vehicles in high-speed or sudden maneuvers and on slippery roads. The wider proliferation of ESC across the vehicle fleet has allowed evaluation of its effects in real-world crashes in many countries, including Japan, Germany, Sweden, France, Great Britain, and the United States. This article provides a summary of the findings. Studies that examined the real-world effectiveness of ESC were reviewed. Crash effects have been examined for different roadways, using differing analytic methods, different crash severities, and different make/model vehicles including both cars and SUVs. The review discusses the methodological differences and examines the findings according to vehicle type, crash type and severity, and road conditions. The overwhelming majority of studies find that ESC is highly effective in reducing single-vehicle crashes in cars and SUVs. Fatal single-vehicle crashes involving cars are reduced by about 30-50% and SUVs by 50-70%. Fatal rollover crashes are estimated to be about 70-90% lower with ESC regardless of vehicle type. A number of studies find improved effectiveness in reducing crashes when road conditions are slippery. There is little or no effect of ESC in all multi-vehicle crashes; however, there is a 17-38% reduction in more serious, fatal multi-vehicle crashes. Given the extraordinary benefits of ESC in preventing crashes, especially those with more serious outcomes, the implementation of ESC should be accelerated to cover the full range of passenger vehicles in both developed and developing markets.

Classification of underwater targets from autonomous underwater vehicle sampled bistatic acoustic scattered fields.

PubMed

Fischell, Erin M; Schmidt, Henrik

2015-12-01

One of the long term goals of autonomous underwater vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using AUV-based sensing, such as sidescan and synthetic aperture sonar, require an expensive payload on each outfitted vehicle and post-processing and/or image interpretation. A vehicle payload and machine learning classification methodology using bistatic angle dependence of target scattering amplitudes between a fixed acoustic source and target has been developed for onboard, fully autonomous classification with lower cost-per-vehicle. To achieve the high-quality, densely sampled three-dimensional (3D) bistatic scattering data required by this research, vehicle sampling behaviors and an acoustic payload for precision timed data acquisition with a 16 element nose array were demonstrated. 3D bistatic scattered field data were collected by an AUV around spherical and cylindrical targets insonified by a 7-9 kHz fixed source. The collected data were compared to simulated scattering models. Classification and confidence estimation were shown for the sphere versus cylinder case on the resulting real and simulated bistatic amplitude data. The final models were used for classification of simulated targets in real time in the LAMSS MOOS-IvP simulation package [M. Benjamin, H. Schmidt, P. Newman, and J. Leonard, J. Field Rob. 27, 834-875 (2010)].

40 CFR 1051.650 - What special provisions apply for converting a vehicle to use an alternate fuel?

Code of Federal Regulations, 2010 CFR

2010-07-01

... converting a vehicle to use an alternate fuel? 1051.650 Section 1051.650 Protection of Environment... vehicle to use an alternate fuel? A certificate of conformity is no longer valid for a vehicle if the... applies if such modifications are done to convert the vehicle to run on a different fuel type. Such...

49 CFR 213.345 - Vehicle qualification testing.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Vehicle qualification testing. 213.345 Section 213... Higher § 213.345 Vehicle qualification testing. (a) All rolling stock types which operate at Class 6... demonstrate that the vehicle dynamic response to track alinement and geometry variations are within acceptable...

49 CFR 580.5 - Disclosure of odometer information.

Code of Federal Regulations, 2012 CFR

2012-10-01

... the vehicle, including its make, model, year, and body type, and its vehicle identification number. (d... the mileage disclosed by the transferor when ownership of the vehicle was transferred and contain a... vehicle, each transferor shall disclose the mileage to the transferee in writing on the title or, except...

49 CFR 580.5 - Disclosure of odometer information.

Code of Federal Regulations, 2014 CFR

2014-10-01

... the vehicle, including its make, model, year, and body type, and its vehicle identification number. (d... the mileage disclosed by the transferor when ownership of the vehicle was transferred and contain a... vehicle, each transferor shall disclose the mileage to the transferee in writing on the title or, except...

49 CFR 580.5 - Disclosure of odometer information.

Code of Federal Regulations, 2013 CFR

2013-10-01

... the vehicle, including its make, model, year, and body type, and its vehicle identification number. (d... the mileage disclosed by the transferor when ownership of the vehicle was transferred and contain a... vehicle, each transferor shall disclose the mileage to the transferee in writing on the title or, except...

49 CFR Appendix E to Part 580 - Power of Attorney Disclosure Form

Code of Federal Regulations, 2012 CFR

2012-10-01

... imprisonment. VEHICLE DESCRIPTION Year ____ Make _______ Model _______ Body Type _______ Vehicle Identification...-in-fact, to disclose the mileage, on the title for the vehicle described above, exactly as stated in... attorney-in-fact, to sign the mileage disclosure, on the title for the vehicle described above, only if the...

49 CFR Appendix E to Part 580 - Power of Attorney Disclosure Form

Code of Federal Regulations, 2014 CFR

2014-10-01

... imprisonment. VEHICLE DESCRIPTION Year ____ Make _______ Model _______ Body Type _______ Vehicle Identification...-in-fact, to disclose the mileage, on the title for the vehicle described above, exactly as stated in... attorney-in-fact, to sign the mileage disclosure, on the title for the vehicle described above, only if the...

49 CFR 580.5 - Disclosure of odometer information.

Code of Federal Regulations, 2010 CFR

2010-10-01

... the vehicle, including its make, model, year, and body type, and its vehicle identification number. (d... the mileage disclosed by the transferor when ownership of the vehicle was transferred and contain a... vehicle, each transferor shall disclose the mileage to the transferee in writing on the title or, except...

49 CFR Appendix E to Part 580 - Power of Attorney Disclosure Form

Code of Federal Regulations, 2011 CFR

2011-10-01

... imprisonment. VEHICLE DESCRIPTION Year ____ Make _______ Model _______ Body Type _______ Vehicle Identification...-in-fact, to disclose the mileage, on the title for the vehicle described above, exactly as stated in... attorney-in-fact, to sign the mileage disclosure, on the title for the vehicle described above, only if the...

49 CFR Appendix E to Part 580 - Power of Attorney Disclosure Form

Code of Federal Regulations, 2013 CFR

2013-10-01

... imprisonment. VEHICLE DESCRIPTION Year ____ Make _______ Model _______ Body Type _______ Vehicle Identification...-in-fact, to disclose the mileage, on the title for the vehicle described above, exactly as stated in... attorney-in-fact, to sign the mileage disclosure, on the title for the vehicle described above, only if the...

49 CFR 393.11 - Lamps and reflective devices.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., reflective devices and associated equipment by the type of commercial motor vehicle. The diagrams in this... Table 1. All commercial motor vehicles manufactured on or after December 25, 1968, must, at a minimum... of the vehicle. Commercial motor vehicles manufactured before December 25, 1968, must, at a minimum...

Differential Rollover Risk in Vehicle-to-Traffic Barrier Collisions

PubMed Central

Gabauer, Douglas J.; Gabler, Hampton C.

2009-01-01

In the roadside safety community, there has been debate over the influence of vehicle and barrier type on rollover rates in traffic barrier crashes. This study investigated rollover rates between sport utility vehicles (SUVs), pickup trucks, and cars in vehicle-traffic barrier crashes and has examined the effect of barrier type on rollover risk for concrete barrier and metal barrier impacts. The analysis included 955 barrier impact cases that were selected from 11-years of in-depth crash data available through the National Automotive Sampling System (NASS) / Crashworthiness Data System (CDS). In real world tow-away level longitudinal barrier collisions, the most important predictors of vehicle rollover were found to be vehicle type and whether the vehicle was tracking prior to barrier impact. Based on binary logistic regression, SUVs were found to have 8 times the risk of rollover as cars in barrier impacts. Although pickups were found to have an increased risk of rollover compared to cars, the risk was not as pronounced as that found for SUVs. This finding has direct implications for the full scale crash testing of longitudinal barriers as the testing procedures have been predicated on the assumption that the pickup truck provides a critical or worst case impact scenario. In towaway crashes, our study does not support the notion that concrete barriers have a higher risk of vehicle rollover than metal beam barriers. PMID:20184839

State-of-the-art assessment of electric and hybrid vehicles

NASA Technical Reports Server (NTRS)

1978-01-01

Data are presented that were obtained from the electric and hybrid vehicles tested, information collected from users of electric vehicles, and data and information on electric and hybrid vehicles obtained on a worldwide basis from manufacturers and available literature. The data given include: (1) information and data base (electric and hybrid vehicle systems descriptions, sources of vehicle data and information, and sources of component data); (2) electric vehicles (theoretical background, electric vehicle track tests, user experience, literature data, and summary of electric vehicle status); (3) electric vehicle components (tires, differentials, transmissions, traction motors, controllers, batteries, battery chargers, and component summary); and (4) hybrid vehicles (types of hybrid vehicles, operating modes, hybrid vehicles components, and hybrid vehicles performance characteristics).

Clean Cities Guide to Alternative Fuel and Advanced Medium- and Heavy-Duty Vehicles (Book)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2013-08-01

Today's fleets are increasingly interested in medium-duty and heavy-duty vehicles that use alternative fuels or advanced technologies that can help reduce operating costs, meet emissions requirements, improve fleet sustainability, and support U.S. energy independence. Vehicle and engine manufacturers are responding to this interest with a wide range of options across a steadily growing number of vehicle applications. This guide provides an overview of alternative fuel power systems?including engines, microturbines, electric motors, and fuel cells?and hybrid propulsion systems. The guide also offers a list of individual medium- and heavy-duty vehicle models listed by application, along with associated manufacturer contact information, fuelmore » type(s), power source(s), and related information.« less

Clean Cities Guide to Alternative Fuel and Advanced Medium- and Heavy-Duty Vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2013-08-01

Today's fleets are increasingly interested in medium-duty and heavy-duty vehicles that use alternative fuels or advanced technologies that can help reduce operating costs, meet emissions requirements, improve fleet sustainability, and support U.S. energy independence. Vehicle and engine manufacturers are responding to this interest with a wide range of options across a steadily growing number of vehicle applications. This guide provides an overview of alternative fuel power systems--including engines, microturbines, electric motors, and fuel cells--and hybrid propulsion systems. The guide also offers a list of individual medium- and heavy-duty vehicle models listed by application, along with associated manufacturer contact information, fuelmore » type(s), power source(s), and related information.« less

High speed maglev design

DOEpatents

Rote, Donald M.; He, Jianliang; Coffey, Howard

1993-01-01

A propulsion and stabilization system for an inductive repulsion type magnetically levitated vehicle which is propelled and suspended by a system which includes dividing the superconducting magnets into two types: a strong field magnet which is located vertically below the vehicle for propulsion and guidance and a weak field superconducting magnet located at the ends of the vehicle for levitation and added guidance. Several proposed embodiments exist for the placement of the magnetic field shielding: locating the shielding on the vehicle, locating the shielding on the guideway, and locating the shielding on the guideway and adding shielding to the vertical undercarriage. In addition, the separation between the vehicle and the guideway can be controlled to reduce the exposure of the passenger cabin to magnetic fields.

High speed maglev design

DOEpatents

Rote, D.M.; Jianliang He; Coffey, H.

1993-10-19

A propulsion and stabilization system for an inductive repulsion type magnetically levitated vehicle which is propelled and suspended by a system which includes dividing the superconducting magnets into two types: a strong field magnet which is located vertically below the vehicle for propulsion and guidance and a weak field superconducting magnet located at the ends of the vehicle for levitation and added guidance. Several proposed embodiments exist for the placement of the magnetic field shielding: locating the shielding on the vehicle, locating the shielding on the guideway, and locating the shielding on the guideway and adding shielding to the vertical undercarriage. In addition, the separation between the vehicle and the guideway can be controlled to reduce the exposure of the passenger cabin to magnetic fields. 4 figures.

Improved high speed maglev design

DOEpatents

Rote, D.M.; He, Jianliang; Coffey, H.T.

1992-01-01

This report discusses a propulsion and stabilization system for an inductive repulsion type magnetically levitated vehicle which is propelled and suspended by a system which includes dividing the superconducting magnets into two types: a strong field magnet which is located vertically below the vehicle for propulsion and guidance and a weak field superconducting magnet located at the ends of the vehicle for levitation and added guidance. Several proposed embodiments exist for the placement of the magnetic field shielding: locating the shielding on the vehicle, locating the shielding on the guideway, and locating the shielding on the guideway and adding shielding to the vertical undercarriage. In addition, the separation between the be vehicle and the guideway can be controlled to reduce the exposure of the passenger cabin to magnetic fields.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joyce, R.J.; Natusch, D.F.S.; Richardson, D.W.

Blends of 15% methanol with petrol containing 1% isobutanol have been utilised by 45 vehicles operated for a period of two years. An additional 907 vehicles have been operated for approximately one year to obtain information about the distribution of M15 blends, about necessary co-solvent concentrations, and about general vehicle driveability. Initial studies have also been conducted using 15-20% emulsions of methanol with diesel in diesel-cycle engines. High methanol fuels ranging from M85 to M100 have been tested in six purpose-built vehicles and 45 retrofitted vehicles involving four different types of retrofit systems. In addition, high methanol fuels have alsomore » been tested in dieselcycle engines involving two different types of purpose-built engines, together with unmodified engines.« less

Detection of inter-patient left and right bundle branch block heartbeats in ECG using ensemble classifiers

PubMed Central

2014-01-01

Background Left bundle branch block (LBBB) and right bundle branch block (RBBB) not only mask electrocardiogram (ECG) changes that reflect diseases but also indicate important underlying pathology. The timely detection of LBBB and RBBB is critical in the treatment of cardiac diseases. Inter-patient heartbeat classification is based on independent training and testing sets to construct and evaluate a heartbeat classification system. Therefore, a heartbeat classification system with a high performance evaluation possesses a strong predictive capability for unknown data. The aim of this study was to propose a method for inter-patient classification of heartbeats to accurately detect LBBB and RBBB from the normal beat (NORM). Methods This study proposed a heartbeat classification method through a combination of three different types of classifiers: a minimum distance classifier constructed between NORM and LBBB; a weighted linear discriminant classifier between NORM and RBBB based on Bayesian decision making using posterior probabilities; and a linear support vector machine (SVM) between LBBB and RBBB. Each classifier was used with matching features to obtain better classification performance. The final types of the test heartbeats were determined using a majority voting strategy through the combination of class labels from the three classifiers. The optimal parameters for the classifiers were selected using cross-validation on the training set. The effects of different lead configurations on the classification results were assessed, and the performance of these three classifiers was compared for the detection of each pair of heartbeat types. Results The study results showed that a two-lead configuration exhibited better classification results compared with a single-lead configuration. The construction of a classifier with good performance between each pair of heartbeat types significantly improved the heartbeat classification performance. The results showed a sensitivity of 91.4% and a positive predictive value of 37.3% for LBBB and a sensitivity of 92.8% and a positive predictive value of 88.8% for RBBB. Conclusions A multi-classifier ensemble method was proposed based on inter-patient data and demonstrated a satisfactory classification performance. This approach has the potential for application in clinical practice to distinguish LBBB and RBBB from NORM of unknown patients. PMID:24903422

Detection of inter-patient left and right bundle branch block heartbeats in ECG using ensemble classifiers.

PubMed

Huang, Huifang; Liu, Jie; Zhu, Qiang; Wang, Ruiping; Hu, Guangshu

2014-06-05

Left bundle branch block (LBBB) and right bundle branch block (RBBB) not only mask electrocardiogram (ECG) changes that reflect diseases but also indicate important underlying pathology. The timely detection of LBBB and RBBB is critical in the treatment of cardiac diseases. Inter-patient heartbeat classification is based on independent training and testing sets to construct and evaluate a heartbeat classification system. Therefore, a heartbeat classification system with a high performance evaluation possesses a strong predictive capability for unknown data. The aim of this study was to propose a method for inter-patient classification of heartbeats to accurately detect LBBB and RBBB from the normal beat (NORM). This study proposed a heartbeat classification method through a combination of three different types of classifiers: a minimum distance classifier constructed between NORM and LBBB; a weighted linear discriminant classifier between NORM and RBBB based on Bayesian decision making using posterior probabilities; and a linear support vector machine (SVM) between LBBB and RBBB. Each classifier was used with matching features to obtain better classification performance. The final types of the test heartbeats were determined using a majority voting strategy through the combination of class labels from the three classifiers. The optimal parameters for the classifiers were selected using cross-validation on the training set. The effects of different lead configurations on the classification results were assessed, and the performance of these three classifiers was compared for the detection of each pair of heartbeat types. The study results showed that a two-lead configuration exhibited better classification results compared with a single-lead configuration. The construction of a classifier with good performance between each pair of heartbeat types significantly improved the heartbeat classification performance. The results showed a sensitivity of 91.4% and a positive predictive value of 37.3% for LBBB and a sensitivity of 92.8% and a positive predictive value of 88.8% for RBBB. A multi-classifier ensemble method was proposed based on inter-patient data and demonstrated a satisfactory classification performance. This approach has the potential for application in clinical practice to distinguish LBBB and RBBB from NORM of unknown patients.

Future Automotive Systems Technology Simulator (FASTSim)

DOE Office of Scientific and Technical Information (OSTI.GOV)

An advanced vehicle powertrain systems analysis tool, the Future Automotive Systems Technology Simulator (FASTSim) provides a simple way to compare powertrains and estimate the impact of technology improvements on light-, medium- and heavy-duty vehicle efficiency, performance, cost, and battery life. Created by the National Renewable Energy Laboratory, FASTSim accommodates a range of vehicle types - including conventional vehicles, electric-drive vehicles, and fuel cell vehicles - and is available for free download in Microsoft Excel and Python formats.

Impact of study design on development and evaluation of an activity-type classifier.

PubMed

van Hees, Vincent T; Golubic, Rajna; Ekelund, Ulf; Brage, Søren

2013-04-01

Methods to classify activity types are often evaluated with an experimental protocol involving prescribed physical activities under confined (laboratory) conditions, which may not reflect real-life conditions. The present study aims to evaluate how study design may impact on classifier performance in real life. Twenty-eight healthy participants (21-53 yr) were asked to wear nine triaxial accelerometers while performing 58 activity types selected to simulate activities in real life. For each sensor location, logistic classifiers were trained in subsets of up to 8 activities to distinguish between walking and nonwalking activities and were then evaluated in all 58 activities. Different weighting factors were used to convert the resulting confusion matrices into an estimation of the confusion matrix as would apply in the real-life setting by creating four different real-life scenarios, as well as one traditional laboratory scenario. The sensitivity of a classifier estimated with a traditional laboratory protocol is within the range of estimates derived from real-life scenarios for any body location. The specificity, however, was systematically overestimated by the traditional laboratory scenario. Walking time was systematically overestimated, except for lower back sensor data (range: 7-757%). In conclusion, classifier performance under confined conditions may not accurately reflect classifier performance in real life. Future studies that aim to evaluate activity classification methods are warranted to pay special attention to the representativeness of experimental conditions for real-life conditions.

A machine learned classifier for RR Lyrae in the VVV survey

NASA Astrophysics Data System (ADS)

Elorrieta, Felipe; Eyheramendy, Susana; Jordán, Andrés; Dékány, István; Catelan, Márcio; Angeloni, Rodolfo; Alonso-García, Javier; Contreras-Ramos, Rodrigo; Gran, Felipe; Hajdu, Gergely; Espinoza, Néstor; Saito, Roberto K.; Minniti, Dante

2016-11-01

Variable stars of RR Lyrae type are a prime tool with which to obtain distances to old stellar populations in the Milky Way. One of the main aims of the Vista Variables in the Via Lactea (VVV) near-infrared survey is to use them to map the structure of the Galactic Bulge. Owing to the large number of expected sources, this requires an automated mechanism for selecting RR Lyrae, and particularly those of the more easily recognized type ab (I.e., fundamental-mode pulsators), from the 106-107 variables expected in the VVV survey area. In this work we describe a supervised machine-learned classifier constructed for assigning a score to a Ks-band VVV light curve that indicates its likelihood of being ab-type RR Lyrae. We describe the key steps in the construction of the classifier, which were the choice of features, training set, selection of aperture, and family of classifiers. We find that the AdaBoost family of classifiers give consistently the best performance for our problem, and obtain a classifier based on the AdaBoost algorithm that achieves a harmonic mean between false positives and false negatives of ≈7% for typical VVV light-curve sets. This performance is estimated using cross-validation and through the comparison to two independent datasets that were classified by human experts.

75 FR 59673 - Public Hearing Locations for the Proposed Fuel Economy Labels

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-28

... types, including electric vehicles (EV), plug-in hybrid electric vehicles (PHEV), and conventional... purchase decisions and to address the entrance of advanced technology vehicles into the U.S. market. The...

Intelligent Vehicle Initiative : needs assessment

DOT National Transportation Integrated Search

1999-11-01

The aim of the Intelligent Vehicle Initiative (IVI) is to accelerate the development and availability of advanced safety and information systems for a variety of vehicle types. Public transit, through the Federal Transit Administration (FTA), is an a...

Using multiclass classification to automate the identification of patient safety incident reports by type and severity.

PubMed

Wang, Ying; Coiera, Enrico; Runciman, William; Magrabi, Farah

2017-06-12

Approximately 10% of admissions to acute-care hospitals are associated with an adverse event. Analysis of incident reports helps to understand how and why incidents occur and can inform policy and practice for safer care. Unfortunately our capacity to monitor and respond to incident reports in a timely manner is limited by the sheer volumes of data collected. In this study, we aim to evaluate the feasibility of using multiclass classification to automate the identification of patient safety incidents in hospitals. Text based classifiers were applied to identify 10 incident types and 4 severity levels. Using the one-versus-one (OvsO) and one-versus-all (OvsA) ensemble strategies, we evaluated regularized logistic regression, linear support vector machine (SVM) and SVM with a radial-basis function (RBF) kernel. Classifiers were trained and tested with "balanced" datasets (n_ Type  = 2860, n_ SeverityLevel  = 1160) from a state-wide incident reporting system. Testing was also undertaken with imbalanced "stratified" datasets (n_ Type  = 6000, n_ SeverityLevel =5950) from the state-wide system and an independent hospital reporting system. Classifier performance was evaluated using a confusion matrix, as well as F-score, precision and recall. The most effective combination was a OvsO ensemble of binary SVM RBF classifiers with binary count feature extraction. For incident type, classifiers performed well on balanced and stratified datasets (F-score: 78.3, 73.9%), but were worse on independent datasets (68.5%). Reports about falls, medications, pressure injury, aggression and blood products were identified with high recall and precision. "Documentation" was the hardest type to identify. For severity level, F-score for severity assessment code (SAC) 1 (extreme risk) was 87.3 and 64% for SAC4 (low risk) on balanced data. With stratified data, high recall was achieved for SAC1 (82.8-84%) but precision was poor (6.8-11.2%). High risk incidents (SAC2) were confused with medium risk incidents (SAC3). Binary classifier ensembles appear to be a feasible method for identifying incidents by type and severity level. Automated identification should enable safety problems to be detected and addressed in a more timely manner. Multi-label classifiers may be necessary for reports that relate to more than one incident type.

A PEMS study of the emissions of gaseous pollutants and ultrafine particles from gasoline- and diesel-fueled vehicles

NASA Astrophysics Data System (ADS)

Huang, Cheng; Lou, Diming; Hu, Zhiyuan; Feng, Qian; Chen, Yiran; Chen, Changhong; Tan, Piqiang; Yao, Di

2013-10-01

On-road emission measurements of gasoline- and diesel-fueled vehicles were conducted by a portable emission measurement system (PEMS) in Shanghai, China. Horiba OBS 2200 and TSI EEPS 3090 were employed to detect gaseous and ultrafine particle emissions during the tests. The driving-based emission factors of gaseous pollutants and particle mass and number were obtained on various road types. The average NOx emission factors of the diesel bus, diesel car, and gasoline car were 8.86, 0.68, and 0.17 g km-1, all of which were in excess of their emission limits. The particle number emission factors were 7.06 × 1014, 6.08 × 1014, and 1.57 × 1014 km-1, generally higher than the results for similar vehicle types reported in the previous studies. The size distributions of the particles emitted from the diesel vehicles were mainly concentrated in the accumulation mode, while those emitted from the gasoline car were mainly distributed in the nucleation mode. Both gaseous and particle emission rates exhibit significant correlations with the change in vehicle speed and power demand. The lowest emission rates for each vehicle type were produced during idling. The highest emission rates for each vehicle type were generally found in high-VSP bins. The particle number emission rates of the gasoline car show the strongest growth trend with increasing VSP and speed. The particle number emission for the gasoline car increased by 3 orders of magnitude from idling to the highest VSP and driving speed conditions. High engine power caused by aggressive driving or heavy loads is the main contributor to high emissions for these vehicles in real-world situations.

Crash fatality and vehicle incompatibility in collisions between cars and light trucks or vans.

PubMed

Ossiander, Eric M; Koepsell, Thomas D; McKnight, Barbara

2014-12-01

In crashes between a car and a light truck or van (LTV), car occupants are more likely to be killed than LTV occupants. The extent this is due to the greater harm imposed by LTVs on cars or the greater protection they offer their own occupants is not known. We conducted a case-control study of collisions between two passenger vehicles in the USA during 1990-2008. Cases were all decedents in fatal crashes (N=157,684); one control was selected from each crash in a national probability sample of crashes (N=379,458). Adjusted for the type of vehicle they were riding in and other confounders, occupants of vehicles colliding with any type of LTVs (categorised as compact sport utility vehicles (SUV), full-size SUVs, minivans, full-size vans, compact pickups and full-size pickups) were at higher risk of death compared with occupants colliding with cars. Adjusted for the type of vehicle they crashed with and other confounders, occupants of LTVs in a collision with any vehicle were at lower risk of death compared with car occupants. Compared with a crash between two cars, the overall RR of death in a crash between any of the other 27 different combinations of vehicle types was 1.0 or greater, except for crashes between two full-size pickups, where the RR of death was 0.9. Although LTVs protect their own occupants better than cars do, LTVs are associated with an excess total risk of death in crashes with cars or other LTVs. 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.

Solubility and transdermal permeation properties of a dehydroepiandrosterone cyclodextrin complex from hydrophilic and lipophilic vehicles.

PubMed

Ceschel, GianCarlo; Bergamante, Valentina; Maffei, Paola; Lombardi Borgia, Simone; Calabrese, Valeria; Biserni, Stefano; Ronchi, Celestino

2005-01-01

The permeation ability of a compound is due principally to its concentration in the vehicle and to its aptitude to cross the stratum corneum of the skin. In this work ex-vivo permeation studies on newly developed formulations containing dehydroepiandrosterone (DHEA) were carried out to investigate vehicles that increase drug permeation through the skin. To enhance the solubility of DHEA, its complex form with alpha-cyclodextrin was used. In addition, the two forms (pure drug and complex form) were introduced in hydrophilic (water), lipophilic (paraffin oil), and microemulsion vehicles to evaluate the synergic effect of cyclodextrins and microemulsion vehicles on solubility and permeation. From the results, DHEA solubility is notably conditioned by the type of the vehicle used: the highest solubilities (both for pure and complex drug forms) were obtained with microemulsion, followed by paraffin oil and water. Moreover, in all the studied vehicles, the c-DHEA was more soluble than DHEA. Permeation profile fluxes showed very interesting differences. That reflect the varying drug forms (pure drug and complex form), vehicles used, and drug concentrations in the vehicles. The major flux was obtained in complex of DHEA with alpha-cyclodextrins in the microemulsion vehicle. Therefore, this type of vehicle and drug form would be very useful in the development of a topical formulation containing DHEA.

Comparison of teen driver fatality rates by vehicle type in the United States.

PubMed

Trowbridge, Matthew J; McKay, Mary Pat; Maio, Ronald F

2007-10-01

To compare national fatality rates for teen drivers by vehicle type. Fatality rates were calculated for 16- to 19-year-old drivers by vehicle type using data from the Fatal Analysis Reporting System (1999-2003) and estimates of miles driven from the National Household Transportation Survey (2001). Relative fatality risks for teen drivers of sports utility vehicles (SUVs) and pickups were calculated using passenger cars as a reference. Per vehicle mile driven, the fatality risk for both male and female teens driving SUVs was decreased relative to passenger car drivers (male teens: relative risk [RR], 0.33 [95% confidence interval [CI] = 0.29 to 0.37]; female teens: RR, 0.45 [95% CI = 0.34 to 0.59]). Fatality rates for male teens driving pickups were also lower per mile driven compared with male passenger car drivers (RR, 0.55 [95% CI = 0.51 to 0.60]). Fatality rates for female teens driving pickups and passenger cars were not statistically different but appear potentially higher for pickups (RR, 1.19 [95% CI = 0.98 to 1.44]). Both SUVs and pickups demonstrated significantly higher rates of fatal rollovers than passenger cars. Female adolescent drivers of SUVs and pickups were at particularly high risk for fatal rollovers per vehicle mile driven compared with passenger cars (SUV: RR, 1.88 [95% CI = 1.19 to 2.96]; pickup: RR, 3.42 [95% CI = 2.29 to 5.10]). Fatality rates for teen drivers vary significantly by vehicle type. From 1999 to 2003 in the United States, fatal rollovers were significantly more likely per mile driven for teen drivers of both SUVs and pickups compared with passenger cars. However, overall fatality rates (i.e., all crash types) for teen drivers of SUVs and male drivers of pickups were lower per mile driven than for teen drivers of passenger cars. The results of this ecological analysis cannot predict the individual-level fatality risk for teens driving different vehicle types. However, the significant variability in fatality rates among SUVs, pickups, and passenger cars seen at a population level suggests that vehicle choice should be further explored as a potentially modifiable risk factor in interventions to address teen driver safety.

Universal Stationary/Mobile NoFoam Unit (USNOFU) for Aircraft Rescue and Fire Fighting (ARFF) Vehicles

DTIC Science & Technology

2004-01-01

AFFF aqueous film forming foam AFRL Air Force Research Laboratory ARFF Aircraft Rescue and...distribution system checks use a fire-fighting agent called aqueous film forming foam ( AFFF ) and generate significant amounts of AFFF wastewater. Despite its...but it has been classified as persistent, bioaccumulative, and toxic (PBT). As a result, the AFFF wastewater resulting from foam distribution

Distributed tactical reasoning framework for intelligent vehicles

NASA Astrophysics Data System (ADS)

Sukthankar, Rahul; Pomerleau, Dean A.; Thorpe, Chuck E.

1998-01-01

In independent vehicle concepts for the Automated Highway System (AHS), the ability to make competent tactical-level decisions in real-time is crucial. Traditional approaches to tactical reasoning typically involve the implementation of large monolithic systems, such as decision trees or finite state machines. However, as the complexity of the environment grows, the unforeseen interactions between components can make modifications to such systems very challenging. For example, changing an overtaking behavior may require several, non-local changes to car-following, lane changing and gap acceptance rules. This paper presents a distributed solution to the problem. PolySAPIENT consists of a collection of autonomous modules, each specializing in a particular aspect of the driving task - classified by traffic entities rather than tactical behavior. Thus, the influence of the vehicle ahead on the available actions is managed by one reasoning object, while the implications of an approaching exit are managed by another. The independent recommendations form these reasoning objects are expressed in the form of votes and vetos over a 'tactical action space', and are resolved by a voting arbiter. This local independence enables PolySAPIENT reasoning objects to be developed independently, using a heterogenous implementation. PolySAPIENT vehicles are implemented in the SHIVA tactical highway simulator, whose vehicles are based on the Carnegie Mellon Navlab robots.

Guidance and control for unmanned ground vehicles

NASA Astrophysics Data System (ADS)

Bateman, Peter J.

1994-06-01

Techniques for the guidance, control, and navigation of unmanned ground vehicles are described in terms of the communication bandwidth requirements for driving and control of a vehicle remote from the human operator. Modes of operation are conveniently classified as conventional teleoperation, supervisory control, and fully autonomous control. The fundamental problem of maintaining a robust non-line-of-sight communications link between the human controller and the remote vehicle is discussed, as this provides the impetus for greater autonomy in the control system and the greatest scope for innovation. While supervisory control still requires the man to be providing the primary navigational intelligence, fully autonomous operation requires that mission navigation is provided solely by on-board machine intelligence. Methods directed at achieving this performance are described using various active and passive sensing of the terrain for route navigation and obstacle detection. Emphasis is given to TV imagery and signal processing techniques for image understanding. Reference is made to the limitations of current microprocessor technology and suitable computer architectures. Some of the more recent control techniques involve the use of neural networks, fuzzy logic, and data fusion and these are discussed in the context of road following and cross country navigation. Examples of autonomous vehicle testbeds operated at various laboratories around the world are given.

Modeling Types of Pedal Applications Using a Driving Simulator.

PubMed

Wu, Yuqing; Boyle, Linda Ng; McGehee, Daniel; Roe, Cheryl A; Ebe, Kazutoshi; Foley, James

2015-11-01

The aim of this study was to examine variations in drivers' foot behavior and identify factors associated with pedal misapplications. Few studies have focused on the foot behavior while in the vehicle and the mishaps that a driver can encounter during a potentially hazardous situation. A driving simulation study was used to understand how drivers move their right foot toward the pedals. The study included data from 43 drivers as they responded to a series of rapid traffic signal phase changes. Pedal application types were classified as (a) direct hit, (b) hesitated, (c) corrected trajectory, and (d) pedal errors (incorrect trajectories, misses, slips, or pressed both pedals). A mixed-effects multinomial logit model was used to predict the likelihood of one of these pedal applications, and linear mixed models with repeated measures were used to examine the response time and pedal duration given the various experimental conditions (stimuli color and location). Younger drivers had higher probabilities of direct hits when compared to other age groups. Participants tended to have more pedal errors when responding to a red signal or when the signal appeared to be closer. Traffic signal phases and locations were associated with pedal response time and duration. The response time and pedal duration affected the likelihood of being in one of the four pedal application types. Findings from this study suggest that age-related and situational factors may play a role in pedal errors, and the stimuli locations could affect the type of pedal application. © 2015, Human Factors and Ergonomics Society.

Towards More Nuanced Classification of NGOs and Their Services to Improve Integrated Planning across Disaster Phases

PubMed Central

Towe, Vivian L.; Acosta, Joie D.; Chandra, Anita

2017-01-01

Nongovernmental organizations (NGOs) are being integrated into U.S. strategies to expand the services that are available during health security threats like disasters. Identifying better ways to classify NGOs and their services could optimize disaster planning. We surveyed NGOs about the types of services they provided during different disaster phases. Survey responses were used to categorize NGO services as core—critical to fulfilling their organizational mission—or adaptive—services implemented during a disaster based on community need. We also classified NGOs as being core or adaptive types of organizations by calculating the percentage of each NGO’s services classified as core. Service types classified as core were mainly social services, while adaptive service types were those typically relied upon during disasters (e.g., warehousing, food services, etc.). In total, 120 NGOs were classified as core organizations, meaning they mainly provided the same services across disaster phases, while 100 NGOs were adaptive organizations, meaning their services changed. Adaptive NGOs were eight times more likely to report routinely participating in disaster planning as compared to core NGOs. One reason for this association may be that adaptive NGOs are more aware of the changing needs in their communities across disaster phases because of their involvement in disaster planning. PMID:29160810

Modic changes in lumbar spine: prevalence and distribution patterns of end plate oedema and end plate sclerosis.

PubMed

Xu, Lei; Chu, Bin; Feng, Yang; Xu, Feng; Zou, Yue-Fen

2016-01-01

The purpose of this study is to evaluate the distribution of end plate oedema in different types of Modic change especially in mixed type and to analyze the presence of end plate sclerosis in various types of Modic change. 276 patients with low back pain were scanned with 1.5-T MRI. Three radiologists assessed the MR images by T1 weighted, T2 weighted and fat-saturation T2 weighted sequences and classified them according to the Modic changes. Pure oedematous end plate signal changes were classified as Modic Type I; pure fatty end plate changes were classified as Modic Type II; and pure sclerotic end plate changes as Modic Type III. A mixed feature of both Types I and II with predominant oedematous signal change is classified as Modic I-II, and a mixture of Types I and II with predominant fatty change is classified as Modic II-I. Thus, the mixed types can further be subdivided into seven subtypes: Types I-II, Types II-I, Types I-III, Types III-I, Types II-III, Types III-II and Types I-III. During the same period, 52 of 276 patients who underwent CT and MRI were retrospectively reviewed to determine end plate sclerosis. (1) End plate oedema: of the 2760 end plates (276 patients) examined, 302 end plates showed Modic changes, of which 82 end plates showed mixed Modic changes. The mixed Modic changes contain 92.7% of oedematous changes. The mixed types especially Types I-II and Types II-I made up the majority of end plate oedematous changes. (2) End plate sclerosis: 52 of 276 patients were examined by both MRI and CT. Of the 520 end plates, 93 end plates showed Modic changes, of which 34 end plates have shown sclerotic changes in CT images. 11.8% of 34 end plates have shown Modic Type I, 20.6% of 34 end plates have shown Modic Type II, 2.9% of 34 end plates have shown Modic Type III and 64.7% of 34 end plates have shown mixed Modic type. End plate oedema makes up the majority of mixed types especially Types I-II and Types II-I. The end plate sclerosis on CT images may not just mean Modic Type III but does exist in all types of Modic changes, especially in mixed Modic types, and may reflect vertebral body mineralization rather than change in the bone marrow. End plate oedema and end plate sclerosis are present in a large proportion of mixed types.

Impacts of fleet types and charging modes for electric vehicles on emissions under different penetrations of wind power

NASA Astrophysics Data System (ADS)

Chen, Xinyu; Zhang, Hongcai; Xu, Zhiwei; Nielsen, Chris P.; McElroy, Michael B.; Lv, Jiajun

2018-05-01

Current Chinese policy promotes the development of both electricity-propelled vehicles and carbon-free sources of power. Concern has been expressed that electric vehicles on average may emit more CO2 and conventional pollutants in China. Here, we explore the environmental implications of investments in different types of electric vehicle (public buses, taxis and private light-duty vehicles) and different modes (fast or slow) for charging under a range of different wind penetration levels. To do this, we take Beijing in 2020 as a case study and employ hourly simulation of vehicle charging behaviour and power system operation. Assuming the slow-charging option, we find that investments in electric private light-duty vehicles can result in an effective reduction in the emission of CO2 at several levels of wind penetration. The fast-charging option, however, is counter-productive. Electrifying buses and taxis offers the most effective option to reduce emissions of NOx, a major precursor for air pollution.

Equating an expert system to a classifier in order to evaluate the expert system

NASA Technical Reports Server (NTRS)

Odell, Patrick L.

1989-01-01

A strategy to evaluate an expert system is formulated. The strategy proposed is based on finding an equivalent classifier to an expert system and evaluate that classifier with respect to an optimal classifier, a Bayes classifier. Here it is shown that for the rules considered an equivalent classifier exists. Also, a brief consideration of meta and meta-meta rules is included. Also, a taxonomy of expert systems is presented and an assertion made that an equivalent classifier exists for each type of expert system in the taxonomy with associated sets of underlying assumptions.

Risk factors affecting fatal bus accident severity: Their impact on different types of bus drivers.

PubMed

Feng, Shumin; Li, Zhenning; Ci, Yusheng; Zhang, Guohui

2016-01-01

While the bus is generally considered to be a relatively safe means of transportation, the property losses and casualties caused by bus accidents, especially fatal ones, are far from negligible. The reasons for a driver to incur fatalities are different in each case, and it is essential to discover the underlying risk factors of bus fatality severity for different types of drivers in order to improve bus safety. The current study investigates the underlying risk factors of fatal bus accident severity to different types of drivers in the U.S. by estimating an ordered logistic model. Data for the analysis are retrieved from the Buses Involved in Fatal Accidents (BIFA) database from the USA for the years 2006-2010. Accidents are divided into three levels by counting their equivalent fatalities, and the drivers are classified into three clusters by the K-means cluster analysis. The analysis shows that some risk factors have the same impact on different types of drivers, they are: (a) season; (b) day of week; (c) time period; (d) number of vehicles involved; (e) land use; (f) manner of collision; (g) speed limit; (h) snow or ice surface condition; (i) school bus; (j) bus type and seating capacity; (k) driver's age; (l) driver's gender; (m) risky behaviors; and (n) restraint system. Results also show that some risk factors only have impact on the "young and elder drivers with history of traffic violations", they are: (a) section type; (b) number of lanes per direction; (c) roadway profile; (d) wet road surface; and (e) cyclist-bus accident. Notably, history of traffic violations has different impact on different types of bus drivers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Crashworthiness testing of a portable maintenance work-zone barrier.

DOT National Transportation Integrated Search

2008-12-01

Barrier and shadow vehicles generally provide Caltrans maintenance workers protection from errant vehicles entering the work zones, from the upstream direction of traffic flow. This type of protection does not protect workers from vehicles entering t...

EFFECT OF VEHICLE CHARACTERISTICS ON UNPAVED ROAD DUST EMISSIONS

EPA Science Inventory

This paper presents PM₁₀ fugitive dust emission factors for a range of vehicles types and examines the influence of vehicle and wake characteristics on the strength of emissions from an unpaved road.

Dimensions of motor vehicle crash risk

DOT National Transportation Integrated Search

1999-05-01

A valid assessment of motor vehicle crash risks and the potential impact of safety interventions requires a precise understanding of the types of vehicles likely to be equipped and otherwise affected, the most relevant referent to the intervention (e...

Measuring pedestrian volumes and conflicts. Volume 2, Accident prediction model

DOT National Transportation Integrated Search

1987-12-01

This final report presents the findings, conclusions, and recommendations of the study conducted to model pedestrian/vehicle accidents. A group-type analysis approach for the prediction of pedestrian/vehicle accidents using pedestrian/vehicle conflic...

Plug-in hybrid electric vehicles in smart grid

NASA Astrophysics Data System (ADS)

Yao, Yin

In this thesis, in order to investigate the impact of charging load from plug-in hybrid electric vehicles (PHEVs), a stochastic model is developed in Matlab. In this model, two main types of PHEVs are defined: public transportation vehicles and private vehicles. Different charging time schedule, charging speed and battery capacity are considered for each type of vehicles. The simulation results reveal that there will be two load peaks (at noon and in evening) when the penetration level of PHEVs increases continuously to 30% in 2030. Therefore, optimization tool is utilized to shift load peaks. This optimization process is based on real time pricing and wind power output data. With the help of smart grid, power allocated to each vehicle could be controlled. As a result, this optimization could fulfill the goal of shifting load peaks to valley areas where real time price is low or wind output is high.

Dynamic Performance of Subway Vehicle with Linear Induction Motor System

NASA Astrophysics Data System (ADS)

Wu, Pingbo; Luo, Ren; Hu, Yan; Zeng, Jing

The light rail vehicle with Linear Induction Motor (LIM) bogie, which is a new type of urban rail traffic tool, has the advantages of low costs, wide applicability, low noise, simple maintenance and better dynamic behavior. This kind of vehicle, supported and guided by the wheel and rail, is not driven by the wheel/rail adhesion force, but driven by the electromagnetic force between LIM and reaction plate. In this paper, three different types of suspensions and their characteristic are discussed with considering the interactions both between wheel and rail and between LIM and reaction plate. A nonlinear mathematical model of the vehicle with LIM bogie is set up by using the software SIMPACK, and the electromechanical model is also set up on Simulink roof. Then the running behavior of the LIM vehicle is simulated, and the influence of suspension on the vehicle dynamic performance is investigated.

Modeling and Validation of Power-split and P2 Parallel Hybrid Electric Vehicles SAE 2013-01-1470)

EPA Science Inventory

The Advanced Light-Duty Powertrain and Hybrid Analysis tool was created by EPA to evaluate the Greenhouse Gas (GHG) emissions of Light-Duty (LD) vehicles. It is a physics-based, forward-looking, full vehicle computer simulator capable of analyzing various vehicle types combined ...

Electric Vehicle Careers: On the Road to Change

ERIC Educational Resources Information Center

Hamilton, James

2012-01-01

Many occupations related to electric vehicles are similar to those that help to make and maintain all types of automobiles. But the industry is also adding some nontraditional jobs, and workers' skill sets must evolve to keep up. This article describes careers related to electric vehicles. The first section is about the electric vehicle industry…

40 CFR 86.1829-01 - Durability and emission testing requirements; waivers.

Code of Federal Regulations, 2014 CFR

2014-07-01

... under the provisions of § 86.1828-10(c) and (g). (4) Electric vehicles and fuel cell vehicles. For electric vehicles and fuel cell vehicles, manufacturers may provide a statement in the application for..., including, but not limited to, canister type, canister volume, canister working capacity, fuel tank volume...

49 CFR 383.31 - Notification of convictions for driver violations.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., in any type of motor vehicle, a State or local law relating to motor vehicle traffic control (other... motor vehicle traffic control (other than a parking violation) in a State or jurisdiction other than the... violation(s) of State or local law relating to motor vehicle traffic control, for which the person was...

40 CFR 1037.525 - Special procedures for testing hybrid vehicles with power take-off.

Code of Federal Regulations, 2014 CFR

2014-07-01

... of this section to allow testing hybrid vehicles other than electric-battery hybrids, consistent with... model, use good engineering judgment to select the vehicle type with the maximum number of PTO circuits... as needed to stabilize the battery at a full state of charge. For electric hybrid vehicles, we...

Development and Testing of an Automatic Transmission Shift Schedule Algorithm for Vehicle Simulation (SAE Paper 2015-01-1142)

EPA Science Inventory

The Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) modeling tool was created by EPA to estimate greenhouse gas (GHG) emissions of light-duty vehicles. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle type...

26 CFR 48.4072-1 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... TAXES MANUFACTURERS AND RETAILERS EXCISE TAXES Motor Vehicles, Tires, Tubes, Tread Rubber, and Taxable...”, for purposes of §§ 48.4071-1 through 48.4073-3 means tires of the type used on: (i) Motor vehicles... in connection with motor vehicles that are highway vehicles (within the meaning of § 48.4061(a)-1(d...

26 CFR 48.4072-1 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... TAXES MANUFACTURERS AND RETAILERS EXCISE TAXES Motor Vehicles, Tires, Tubes, Tread Rubber, and Taxable...”, for purposes of §§ 48.4071-1 through 48.4073-3 means tires of the type used on: (i) Motor vehicles... in connection with motor vehicles that are highway vehicles (within the meaning of § 48.4061(a)-1(d...

26 CFR 48.4072-1 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-04-01

... TAXES MANUFACTURERS AND RETAILERS EXCISE TAXES Motor Vehicles, Tires, Tubes, Tread Rubber, and Taxable...”, for purposes of §§ 48.4071-1 through 48.4073-3 means tires of the type used on: (i) Motor vehicles... in connection with motor vehicles that are highway vehicles (within the meaning of § 48.4061(a)-1(d...

Aerodynamic drag reduction by vertical splitter plates

NASA Astrophysics Data System (ADS)

Gilliéron, Patrick; Kourta, Azeddine

2010-01-01

The capacity of vertical splitter plates placed at the front or the rear of a simplified car geometry to reduce drag, with and without skew angle, is investigated for Reynolds numbers between 1.0 × 106 and 1.6 × 106. The geometry used is a simplified geometry to represent estate-type vehicles, for the rear section, and MPV-type vehicle. Drag reductions of nearly 28% were obtained for a zero skew angle with splitter plates placed at the front of models of MPV or utility vehicles. The results demonstrate the advantage of adapting the position and orientation of the splitter plates in the presence of a lateral wind. All these results confirm the advantage of this type of solution, and suggest that this expertise should be used in the automotive field to reduce consumption and improve dynamic stability of road vehicles.

Predicting membrane protein types by incorporating protein topology, domains, signal peptides, and physicochemical properties into the general form of Chou's pseudo amino acid composition.

PubMed

Chen, Yen-Kuang; Li, Kuo-Bin

2013-02-07

The type information of un-annotated membrane proteins provides an important hint for their biological functions. The experimental determination of membrane protein types, despite being more accurate and reliable, is not always feasible due to the costly laboratory procedures, thereby creating a need for the development of bioinformatics methods. This article describes a novel computational classifier for the prediction of membrane protein types using proteins' sequences. The classifier, comprising a collection of one-versus-one support vector machines, makes use of the following sequence attributes: (1) the cationic patch sizes, the orientation, and the topology of transmembrane segments; (2) the amino acid physicochemical properties; (3) the presence of signal peptides or anchors; and (4) the specific protein motifs. A new voting scheme was implemented to cope with the multi-class prediction. Both the training and the testing sequences were collected from SwissProt. Homologous proteins were removed such that there is no pair of sequences left in the datasets with a sequence identity higher than 40%. The performance of the classifier was evaluated by a Jackknife cross-validation and an independent testing experiments. Results show that the proposed classifier outperforms earlier predictors in prediction accuracy in seven of the eight membrane protein types. The overall accuracy was increased from 78.3% to 88.2%. Unlike earlier approaches which largely depend on position-specific substitution matrices and amino acid compositions, most of the sequence attributes implemented in the proposed classifier have supported literature evidences. The classifier has been deployed as a web server and can be accessed at http://bsaltools.ym.edu.tw/predmpt. Copyright © 2012 Elsevier Ltd. All rights reserved.

Monitoring Traffic Information with a Developed Acceleration Sensing Node.

PubMed

Ye, Zhoujing; Wang, Linbing; Xu, Wen; Gao, Zhifei; Yan, Guannan

2017-12-05

In this paper, an acceleration sensing node for pavement vibration was developed to monitor traffic information, including vehicle speed, vehicle types, and traffic flow, where a hardware design with low energy consumption and node encapsulation could be accomplished. The service performance of the sensing node was evaluated, by methods including waterproof test, compression test, sensing performance analysis, and comparison test. The results demonstrate that the sensing node is low in energy consumption, high in strength, IPX8 waterproof, and high in sensitivity and resolution. These characteristics can be applied to practical road environments. Two sensing nodes were spaced apart in the direction of travelling. In the experiment, three types of vehicles passed by the monitoring points at several different speeds and values of d (the distance between the sensor and the nearest tire center line). Based on cross-correlation with kernel pre-smoothing, a calculation method was applied to process the raw data. New algorithms for traffic flow, speed, and axle length were proposed. Finally, the effects of vehicle speed, vehicle weight, and d value on acceleration amplitude were statistically evaluated. It was found that the acceleration sensing node can be used for traffic flow, vehicle speed, and other types of monitoring.

Monitoring Traffic Information with a Developed Acceleration Sensing Node

PubMed Central

Ye, Zhoujing; Wang, Linbing; Xu, Wen; Gao, Zhifei; Yan, Guannan

2017-01-01

In this paper, an acceleration sensing node for pavement vibration was developed to monitor traffic information, including vehicle speed, vehicle types, and traffic flow, where a hardware design with low energy consumption and node encapsulation could be accomplished. The service performance of the sensing node was evaluated, by methods including waterproof test, compression test, sensing performance analysis, and comparison test. The results demonstrate that the sensing node is low in energy consumption, high in strength, IPX8 waterproof, and high in sensitivity and resolution. These characteristics can be applied to practical road environments. Two sensing nodes were spaced apart in the direction of travelling. In the experiment, three types of vehicles passed by the monitoring points at several different speeds and values of d (the distance between the sensor and the nearest tire center line). Based on cross-correlation with kernel pre-smoothing, a calculation method was applied to process the raw data. New algorithms for traffic flow, speed, and axle length were proposed. Finally, the effects of vehicle speed, vehicle weight, and d value on acceleration amplitude were statistically evaluated. It was found that the acceleration sensing node can be used for traffic flow, vehicle speed, and other types of monitoring. PMID:29206169

Interaction of temperature, humidity, driver preferences, and refrigerant type on air conditioning compressor usage.

PubMed

Levine, C; Younglove, T; Barth, M

2000-10-01

Recent studies have shown large increases in vehicle emissions when the air conditioner (AC) compressor is engaged. Factors that affect the compressor-on percentage can have a significant impact on vehicle emissions and can also lead to prediction errors in current emissions models if not accounted for properly. During 1996 and 1997, the University of California, Riverside, College of Engineering-Center for Environmental Research and Technology (CE-CERT) conducted a vehicle activity study for the California Air Resources Board (CARB) in the Sacramento, CA, region. The vehicles were randomly selected from all registered vehicles in the region. As part of this study, ten vehicles were instrumented to collect AC compressor on/off data on a second-by-second basis in the summer of 1997. Temperature and humidity data were obtained and averaged on an hourly basis. The ten drivers were asked to complete a short survey about AC operational preferences. This paper examines the effects of temperature, humidity, refrigerant type, and driver preferences on air conditioning compressor activity. Overall, AC was in use in 69.1% of the trips monitored. The compressor was on an average of 64% of the time during the trips. The personal preference settings had a significant effect on the AC compressor-on percentage but did not interact with temperature. The refrigerant types, however, exhibited a differential response across temperature, which may necessitate separate modeling of the R12 refrigerant-equipped vehicles from the R134A-equipped vehicles. It should be noted that some older vehicles do get retrofitted with new compressors that use R134A; however, none of the vehicles in this study had been retrofitted.

Assessing crash risk considering vehicle interactions with trucks using point detector data.

PubMed

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.

Application of SOFC for electric vehicle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamada, K.; Mizusaki, J.; Sasaki, H.

1995-12-31

Changing from gasoline powered vehicles to electric vehicles (EVs) will provide positive environmental effects. A present disadvantage of EVs with secondary battery systems is a short driving range. This can be improved by the application of a hybrid system of SOFCs and batteries. For that system, both tubular and planer types of SOFCs having 10kW power are designed which can be used for passenger cars with naphtha as fuel operated at 880--850 C . The tubular type has 106 liters in volume and 100kg in weight, and were smaller and lighter than the planer type. Subjects to be investigated onmore » SOFCs for EVs are described.« less

Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner.

PubMed

An, Jhonghyun; Choi, Baehoon; Sim, Kwee-Bo; Kim, Euntai

2016-07-20

There are several types of intersections such as merge-roads, diverge-roads, plus-shape intersections and two types of T-shape junctions in urban roads. When an autonomous vehicle encounters new intersections, it is crucial to recognize the types of intersections for safe navigation. In this paper, a novel intersection type recognition method is proposed for an autonomous vehicle using a multi-layer laser scanner. The proposed method consists of two steps: (1) static local coordinate occupancy grid map (SLOGM) building and (2) intersection classification. In the first step, the SLOGM is built relative to the local coordinate using the dynamic binary Bayes filter. In the second step, the SLOGM is used as an attribute for the classification. The proposed method is applied to a real-world environment and its validity is demonstrated through experimentation.

Novel Intersection Type Recognition for Autonomous Vehicles Using a Multi-Layer Laser Scanner

PubMed Central

An, Jhonghyun; Choi, Baehoon; Sim, Kwee-Bo; Kim, Euntai

2016-01-01

There are several types of intersections such as merge-roads, diverge-roads, plus-shape intersections and two types of T-shape junctions in urban roads. When an autonomous vehicle encounters new intersections, it is crucial to recognize the types of intersections for safe navigation. In this paper, a novel intersection type recognition method is proposed for an autonomous vehicle using a multi-layer laser scanner. The proposed method consists of two steps: (1) static local coordinate occupancy grid map (SLOGM) building and (2) intersection classification. In the first step, the SLOGM is built relative to the local coordinate using the dynamic binary Bayes filter. In the second step, the SLOGM is used as an attribute for the classification. The proposed method is applied to a real-world environment and its validity is demonstrated through experimentation. PMID:27447640

Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

PubMed Central

Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

2009-01-01

The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

Object Classification in Semi Structured Enviroment Using Forward-Looking Sonar

PubMed Central

dos Santos, Matheus; Ribeiro, Pedro Otávio; Núñez, Pedro; Botelho, Silvia

2017-01-01

The submarine exploration using robots has been increasing in recent years. The automation of tasks such as monitoring, inspection, and underwater maintenance requires the understanding of the robot’s environment. The object recognition in the scene is becoming a critical issue for these systems. On this work, an underwater object classification pipeline applied in acoustic images acquired by Forward-Looking Sonar (FLS) are studied. The object segmentation combines thresholding, connected pixels searching and peak of intensity analyzing techniques. The object descriptor extract intensity and geometric features of the detected objects. A comparison between the Support Vector Machine, K-Nearest Neighbors, and Random Trees classifiers are presented. An open-source tool was developed to annotate and classify the objects and evaluate their classification performance. The proposed method efficiently segments and classifies the structures in the scene using a real dataset acquired by an underwater vehicle in a harbor area. Experimental results demonstrate the robustness and accuracy of the method described in this paper. PMID:28961163

Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity

PubMed Central

Li, Chang-Lin; Li, Kai-Cheng; Wu, Dan; Chen, Yan; Luo, Hao; Zhao, Jing-Rong; Wang, Sa-Shuang; Sun, Ming-Ming; Lu, Ying-Jin; Zhong, Yan-Qing; Hu, Xu-Ye; Hou, Rui; Zhou, Bei-Bei; Bao, Lan; Xiao, Hua-Sheng; Zhang, Xu

2016-01-01

Sensory neurons are distinguished by distinct signaling networks and receptive characteristics. Thus, sensory neuron types can be defined by linking transcriptome-based neuron typing with the sensory phenotypes. Here we classify somatosensory neurons of the mouse dorsal root ganglion (DRG) by high-coverage single-cell RNA-sequencing (10 950 ± 1 218 genes per neuron) and neuron size-based hierarchical clustering. Moreover, single DRG neurons responding to cutaneous stimuli are recorded using an in vivo whole-cell patch clamp technique and classified by neuron-type genetic markers. Small diameter DRG neurons are classified into one type of low-threshold mechanoreceptor and five types of mechanoheat nociceptors (MHNs). Each of the MHN types is further categorized into two subtypes. Large DRG neurons are categorized into four types, including neurexophilin 1-expressing MHNs and mechanical nociceptors (MNs) expressing BAI1-associated protein 2-like 1 (Baiap2l1). Mechanoreceptors expressing trafficking protein particle complex 3-like and Baiap2l1-marked MNs are subdivided into two subtypes each. These results provide a new system for cataloging somatosensory neurons and their transcriptome databases. PMID:26691752

Transportation and handling loads

NASA Technical Reports Server (NTRS)

Ostrem, F. E.

1971-01-01

Criteria and recommended practices are presented for the prediction and verification of transportation and handling loads for the space vehicle structure and for monitoring these loads during transportation and handling of the vehicle or major vehicle segments. Elements of the transportation and handling systems, and the forcing functions and associated loads are described. The forcing functions for common carriers and typical handling devices are assessed, and emphasis is given to the assessment of loads at the points where the space vehicle is supported during transportation and handling. Factors which must be considered when predicting the loads include the transportation and handling medium; type of handling fixture; transport vehicle speed; types of terrain; weather (changes in pressure of temperature, wind, etc.); and dynamics of the transportation modes or handling devices (acceleration, deceleration, and rotations of the transporter or handling device).

Characteristics of Reading Disability Types in Middle School Students Classified ED

ERIC Educational Resources Information Center

Mattison, Richard E.

2008-01-01

Types of reading disabilities (RD) have not yet been investigated in students classified with emotional disturbance (ED). The prevalence of RD and differentiating characteristics were examined in 118 middle school students attending a self-contained school for ED students by defining RDs with reading standard scores less than 85 on the two…

Ensemble Classifier Strategy Based on Transient Feature Fusion in Electronic Nose

NASA Astrophysics Data System (ADS)

Bagheri, Mohammad Ali; Montazer, Gholam Ali

2011-09-01

In this paper, we test the performance of several ensembles of classifiers and each base learner has been trained on different types of extracted features. Experimental results show the potential benefits introduced by the usage of simple ensemble classification systems for the integration of different types of transient features.

49 CFR 580.13 - Disclosure of odometer information by power of attorney.

Code of Federal Regulations, 2011 CFR

2011-10-01

... vehicle, including its make, model year, body type and vehicle identification number. (c) In addition to.... (b) In connection with the transfer of ownership of a motor vehicle, each transferor to whom a title...

49 CFR 580.13 - Disclosure of odometer information by power of attorney.

Code of Federal Regulations, 2012 CFR

2012-10-01

... vehicle, including its make, model year, body type and vehicle identification number. (c) In addition to.... (b) In connection with the transfer of ownership of a motor vehicle, each transferor to whom a title...

ABC's of Alternative Fuel Vehicles: A Guide to Alternative Fuel Vehicles

DOT National Transportation Integrated Search

1996-04-06

This document presents an overview of alternative fuel vehicles (AFVs), : discusses their relationship to Federal and California regulations and clean : air requirements, the major types of AFVs, and the new alternative fuels : appearing on the horiz...

Implementation and development of vehicle tracking and immobilization technologies.

DOT National Transportation Integrated Search

2010-01-01

Since the mid-1980s, limited use has been made of vehicle tracking using satellite communications to mitigate the security and safety risks created by the highway transportation of certain types of hazardous materials. However, vehicle-tracking techn...

Strategies for reducing driver distraction from in-vehicle telematics devices : a discussion document

DOT National Transportation Integrated Search

2003-04-01

"In-Vehicle Telematics" refers to devices incorporating wireless communications technologies in order to provide information services, vehicle automation and other functions. While cellular phones are currently the most common type of telematics devi...

Effects of Heavy Vehicle Characteristics on Pavement Response and Performance---Phase II

DOT National Transportation Integrated Search

1991-12-31

The objective of this research was to analyze and evaluate the interaction between heavy vehicle characteristics and pavement performance for application in pavement management. Heavy vehicle (truck and bus) characteristics include tire types (bias p...

Automated turn pike using PLC and SCADA

NASA Astrophysics Data System (ADS)

Silpa Sreedhar, P.; Aiswarya, P.; Kathirvelan, J.

2017-11-01

We propose a smart turnpike based on Programmable Logic Controller (PLC) and Supervisory Control and Data Acquisition Systems (SCADA) in this paper. In this work, the basic idea is to measure the weight of the vehicles and classify them according to its weight to the respective lanes. It is difficult for the turnpike people to monitor the whole process all the time. So, this PLC based diversion system can be implemented in turnpikes to reduce the difficulties. This method will work based on weight sensors (piezo-resistive) whose output will be fed to a PLC, which will control the vehicle diversion. Using SCADA software, the whole process can be monitored from a remote area. The algorithm developed in this successfully installed in real time system.

An original traffic additional emission model and numerical simulation on a signalized road

NASA Astrophysics Data System (ADS)

Zhu, Wen-Xing; Zhang, Jing-Yu

2017-02-01

Based on VSP (Vehicle Specific Power) model traffic real emissions were theoretically classified into two parts: basic emission and additional emission. An original additional emission model was presented to calculate the vehicle's emission due to the signal control effects. Car-following model was developed and used to describe the traffic behavior including cruising, accelerating, decelerating and idling at a signalized intersection. Simulations were conducted under two situations: single intersection and two adjacent intersections with their respective control policy. Results are in good agreement with the theoretical analysis. It is also proved that additional emission model may be used to design the signal control policy in our modern traffic system to solve the serious environmental problems.

Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles

NASA Astrophysics Data System (ADS)

Waag, Wladislaw; Fleischer, Christian; Sauer, Dirk Uwe

2014-07-01

Lithium-ion battery packs in hybrid and pure electric vehicles are always equipped with a battery management system (BMS). The BMS consists of hardware and software for battery management including, among others, algorithms determining battery states. The continuous determination of battery states during operation is called battery monitoring. In this paper, the methods for monitoring of the battery state of charge, capacity, impedance parameters, available power, state of health, and remaining useful life are reviewed with the focus on elaboration of their strengths and weaknesses for the use in on-line BMS applications. To this end, more than 350 sources including scientific and technical literature are studied and the respective approaches are classified in various groups.

Parallel Hybrid Vehicle Optimal Storage System

NASA Technical Reports Server (NTRS)

Bloomfield, Aaron P.

2009-01-01

A paper reports the results of a Hybrid Diesel Vehicle Project focused on a parallel hybrid configuration suitable for diesel-powered, medium-sized, commercial vehicles commonly used for parcel delivery and shuttle buses, as the missions of these types of vehicles require frequent stops. During these stops, electric hybridization can effectively recover the vehicle's kinetic energy during the deceleration, store it onboard, and then use that energy to assist in the subsequent acceleration.

Automotive technology status and projections. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Dowdy, M.; Burke, A.; Schneider, H.; Edmiston, W.; Klose, G. J.; Heft, R.

1978-01-01

Fuel economy, exhaust emissions, multifuel capability, advanced materials and cost/manufacturability for both conventional and advanced alternative power systems were assessed. To insure valid comparisons of vehicles with alternative power systems, the concept of an Otto-Engine-Equivalent (OEE) vehicle was utilized. Each engine type was sized to provide equivalent vehicle performance. Sensitivity to different performance criteria was evaluated. Fuel economy projections are made for each engine type considering both the legislated emission standards and possible future emissions requirements.

Study of a Terrain-Based Motion Estimation Model to Predict the Position of a Moving Target to Enhance Weapon Probability of Kill

DTIC Science & Technology

2017-09-01

target is modeled based on the kinematic constraints for the type of vehicle and the type of path on which it is traveling . The discrete- time position...is modeled based on the kinematic constraints for the type of vehicle and the type of path on which it is traveling . The discrete- time position...49 A. TRAVELING TIME COMPUTATION ............................................. 49 B. CONVERSION TO

Classifying features in CT imagery: accuracy for some single- and multiple-species classifiers

Treesearch

Daniel L. Schmoldt; Jing He; A. Lynn Abbott

1998-01-01

Our current approach to automatically label features in CT images of hardwood logs classifies each pixel of an image individually. These feature classifiers use a back-propagation artificial neural network (ANN) and feature vectors that include a small, local neighborhood of pixels and the distance of the target pixel to the center of the log. Initially, this type of...

SN2005da: A Spectroscopic and Photometric Analysis of a Peculiar Type Ic Supernova

NASA Astrophysics Data System (ADS)

Williamson, Jacob

2017-12-01

Core collapse supernovae are an important class of objects in stellar evolution research as they are the final life stage of high mass stars. Supernovae in general are classified into several spectral types; this paper explores SN 2005da, classified as a Type Ic, meaning it lacks hydrogen and helium lines. The supernova was originally classified as a broad-lined Type Ic (Type Ic-BL), with expansion velocities near maximum light greater than or approximately equal to 15000 km/s. However, some of the elements present in the spectrum, namely carbon and oxygen, have narrower lines (FWHM approximately equal to 2300 km/s) than other elements, indicating an interaction with a previously ejected envelope. The supernova is also found to have a decay time, with a change in magnitude over 15 days following maximum light of about 1.4 magnitudes, that is significantly faster than typical Type Ic or Ic-BL. This is more akin to a rarer object type known as a Type Ibn, although it lacks the characteristic narrow helium lines of this type. Therefore, SN 2005da appears to be unlike known examples of Type Ic supernovae.

75 FR 76185 - Federal Motor Vehicle Safety Standard, Rearview Mirrors; Federal Motor Vehicle Safety Standard...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-07

... Simulation D. Comparative Regulatory Requirements i. Current FMVSS No. 111 ii. Relevant European Regulations... specifically-defined type of incident in which a non-occupant of a vehicle (most commonly, a pedestrian, but it...-speed vehicle or trailer, designed to carry 10 persons or less which is constructed either on a truck...

19 CFR 18.4a - Containers or road vehicles accepted for transport under customs seal; requirements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 1 2010-04-01 2010-04-01 false Containers or road vehicles accepted for transport... General Provisions § 18.4a Containers or road vehicles accepted for transport under customs seal... design type approval by a competent authority, and (iii) if the container or road vehicle hauling the...

49 CFR Appendix D to Part 580 - Disclosure Form for Leased Vehicle

Code of Federal Regulations, 2012 CFR

2012-10-01

... certify that the odometer reading is NOT the actual mileage. Make Model Body Type Vehicle Identification... 49 Transportation 7 2012-10-01 2012-10-01 false Disclosure Form for Leased Vehicle D Appendix D to... Pt. 580, App. D Appendix D to Part 580—Disclosure Form for Leased Vehicle Odometer Disclosure...

49 CFR Appendix D to Part 580 - Disclosure Form for Leased Vehicle

Code of Federal Regulations, 2010 CFR

2010-10-01

... certify that the odometer reading is NOT the actual mileage. Make Model Body Type Vehicle Identification... 49 Transportation 7 2010-10-01 2010-10-01 false Disclosure Form for Leased Vehicle D Appendix D to... Pt. 580, App. D Appendix D to Part 580—Disclosure Form for Leased Vehicle Odometer Disclosure...

49 CFR Appendix D to Part 580 - Disclosure Form for Leased Vehicle

Code of Federal Regulations, 2014 CFR

2014-10-01

... certify that the odometer reading is NOT the actual mileage. Make Model Body Type Vehicle Identification... 49 Transportation 7 2014-10-01 2014-10-01 false Disclosure Form for Leased Vehicle D Appendix D to... Pt. 580, App. D Appendix D to Part 580—Disclosure Form for Leased Vehicle Odometer Disclosure...

49 CFR Appendix D to Part 580 - Disclosure Form for Leased Vehicle

Code of Federal Regulations, 2013 CFR

2013-10-01

... certify that the odometer reading is NOT the actual mileage. Make Model Body Type Vehicle Identification... 49 Transportation 7 2013-10-01 2013-10-01 false Disclosure Form for Leased Vehicle D Appendix D to... Pt. 580, App. D Appendix D to Part 580—Disclosure Form for Leased Vehicle Odometer Disclosure...

49 CFR Appendix D to Part 580 - Disclosure Form for Leased Vehicle

Code of Federal Regulations, 2011 CFR

2011-10-01

... certify that the odometer reading is NOT the actual mileage. Make Model Body Type Vehicle Identification... 49 Transportation 7 2011-10-01 2011-10-01 false Disclosure Form for Leased Vehicle D Appendix D to... Pt. 580, App. D Appendix D to Part 580—Disclosure Form for Leased Vehicle Odometer Disclosure...

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data

PubMed Central

Navarro, Pedro J.; Fernández, Carlos; Borraz, Raúl; Alonso, Diego

2016-01-01

This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%). PMID:28025565

Field quantification of physical exposures of police officers in vehicle operation.

PubMed

McKinnon, Colin D; Callaghan, Jack P; Dickerson, Clark R

2011-01-01

Mobile police officers perform many of their daily duties in their vehicles. Combined workspace inflexibility and prolonged driving create potential musculoskeletal injury risks. Limited research exists that quantitatively describes postural and load exposures associated with mobile police work. The purpose of this study was to characterize officer activity during a typical workday and identify opportunities for ergonomic intervention. Digital video of traffic officers (N = 10) was used to classify postures according to work activity. Cumulative time in 10 activities was calculated, and a time-history of driver activity documented. Most (55.5 ± 13.4%) time was out of the vehicle, and 22.3 ± 10.5% was spent in single-arm driving. On paper documentation and mobile data terminal use were identified as in-car activities that may benefit from targeted interventions. The primary contribution of this study is characterization of daily mobile police activity and the identification of possible intervention strategies to mitigate physical exposure levels.

On the Use of 3dB Qualification Margin for Structural Parts on Expendable Launch Vehicles

NASA Technical Reports Server (NTRS)

Yunis, Isam

2007-01-01

The standard random vibration qualification test used for Expendable Launch Vehicle components is Maximum Predicted Environment (MPE) + 6dB for a duration of 4 times the service life of the part. This can be a severe qualification test for these fatigue-sensitive structures. This paper uses flight data from several launch vehicles to establish that reducing the qualification approach to MPE+3dB for the duration of the peak environment (1x life) is valid for fatigue-sensitive structural components. Items that can be classified as fatigue-sensitive are probes, ducts, tubing, bellows, hoses, and any non-functional structure. Non-functional structure may be flight critical or carry fluid, but it cannot include any moving parts or electronics. This reduced qualification approach does not include primary or secondary structure which would be exclusively designed by peak loads, either transient or quasi-static, that are so large and of so few cycles as to make fatigue a moot point.

Traffic signs recognition for driving assistance

NASA Astrophysics Data System (ADS)

Sai Sangram Reddy, Yatham; Karthik, Devareddy; Rana, Nikunj; Jasmine Pemeena Priyadarsini, M.; Rajini, G. K.; Naseera, Shaik

2017-11-01

In the current circumstances with the innovative headway, we must be able to provide assistance to the driving in recognising the traffic signs on the roads. At present time, many reviews are being directed moving in the direction of the usage of a keen Traffic Systems. One field of this exploration is driving support systems, and many reviews are being directed to create frameworks which distinguish and perceive street signs in front of the vehicle, and afterward utilize the data to advise the driver or to even control the vehicle by implementing this system on self-driving vehicles. In this paper we propose a method to detect the traffic sign board in a frame using HAAR cascading and then identifying the sign on it. The output may be either given out in voice or can be displayed as per the driver’s convenience. Each of the Traffic Sign is recognised using a database of images of symbols used to train the KNN classifier using open CV libraries.

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data.

PubMed

Navarro, Pedro J; Fernández, Carlos; Borraz, Raúl; Alonso, Diego

2016-12-23

This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%).

Graduated driver license compliant teens involved in fatal motor vehicle crashes.

PubMed

Pressley, Joyce C; Addison, Diane; Dawson, Patrick; Nelson, Sharifa S

2015-09-01

Significant reductions in motor vehicle injury mortality have been reported for teen drivers after passage of graduated driver licensing (GDL), seat belt, and no tolerance alcohol and drug laws. Despite this, teen drivers remain a vulnerable population with elevated fatal crash involvement. This study examines driver, vehicle, and crash characteristics of GDL-compliant, belted, and unimpaired teen drivers with the goal of identifying areas where further improvements might be realized. The Fatality Analysis Reporting System (FARS) for 2007 to 2009 was used to examine and classify driver violations/errors in compliant teen drivers (n = 1,571) of passenger vehicles involved in a fatal collision. Teens driving unbelted, non-GDL compliant, or impaired by alcohol or drugs were excluded. Statistical analysis used χ, Fisher's exact and multivariable logistic regression. Odds ratios are reported with 95% confidence intervals. Significance was defined as p < 0.05. Nearly one third (n = 1,571) of teen drivers involved in a fatal motor vehicle crash were GDL compliant, unimpaired, and belted. The majority held an intermediate GDL license (90.6%). Crash-related factors were identified for 63.1% of fatal crashes. Age- and sex-adjusted odds identified overcorrecting, speeding, lane errors, school morning crashes, distractions, and driving on slippery surfaces as having increased odds of fatality for the teen driver as well as newer vehicle models and heavier vehicle weight as protective. Among compliant drivers, weekday crashes before and after school and committing a driving violation at the time of crash were associated with increased risk of driver death and higher incidence of incapacitating injury in surviving drivers. Therapeutic study, level V.

Vehicle operating costs, fuel consumption, and pavement type condition factors

DOT National Transportation Integrated Search

1982-06-01

This report presents updated vehicle operating cost tables which may be used by a highway agency for estimation of vehicle operating costs as a function of operational and roadway variables. These results, partially based on fuel consumption tests on...

Properties of train load frequencies and their applications

NASA Astrophysics Data System (ADS)

Milne, D. R. M.; Le Pen, L. M.; Thompson, D. J.; Powrie, W.

2017-06-01

A train in motion applies moving steady loads to the railway track as well as dynamic excitation; this causes track deflections, vibration and noise. At low frequency, the spectrum of measured track vibration has been found to have a distinct pattern; with spectral peaks occurring at multiples of the vehicle passing frequency. This pattern can be analysed to quantify aspects of train and track performance as well as to design sensors and systems for trackside condition monitoring. To this end, analytical methods are developed to determine frequency spectra based on known vehicle geometry and track properties. It is shown that the quasi-static wheel loads from a moving train, which are the most significant cause of the track deflections at low frequency, can be understood by considering a loading function representing the train geometry in combination with the response of the track to a single unit load. The Fourier transform of the loading function describes how the passage of repeating vehicles within a train leads to spectral peaks at various multiples of the vehicle passing frequency. When a train consists of a single type of repeating vehicle, these peaks depend on the geometry of that vehicle type as the separation of axles on a bogie and spacing of those bogies on a vehicle cause certain frequencies to be suppressed. Introduction of different vehicle types within a train or coupling of trainsets with a different inter-car length changes the spectrum, although local peaks still occur at multiples of the passing frequency of the primary vehicle. Using data from track-mounted geophones, it is shown that the properties of the train load spectrum, together with a model for track behaviour, allows calculation of the track system support modulus without knowledge of the axle loads, and enables rapid determination of the train speed. For continuous remote condition monitoring, track-mounted transducers are ideally powered using energy harvesting devices. These need to be tuned to optimise energy abstraction; the appropriate energy harvesting frequencies for given vehicle types and line speeds can also be predicted using the models developed.

Preliminary assessment of pavement damage due to heavier loads on Louisiana highways : technical summary.

DOT National Transportation Integrated Search

1999-05-01

The principal objective of this study is to provide a preliminary assessment of the effect of increasing the gross vehicle weight (GVW) on Louisiana type 2 and type 6 vehicles as allowed by special permits, on pavement costs to rehabilitate the damag...

Do Demographics and Functional Abilities Influence Vehicle Type Driven by Older Canadians?

PubMed

Vrkljan, Brenda; Crizzle, Alexander; Villeneuve, Simon; Porter, Michelle; Koppel, Sjaan; Mazer, Barbara L; Naglie, Gary; Bédard, Michel; Tuokko, Holly A; Gélinas, Isabelle; Marshall, Shawn C; Rapoport, Mark J

2016-06-01

In this study, we examined the Candrive baseline data (n = 928; aged 70 to 94; 62% were men) to determine whether driver characteristics (i.e., age, gender, height, weight, BMI) and certain functional abilities (i.e., Rapid Paced Walk, Timed Up and Go) influenced the types of vehicles driven. There were significant differences with respect to type of vehicle and mean driver age (F = 3.58, p = 0.003), height, (F = 13.32, p < 0.001), weight (F = 14.31, p < 0.001), and BMI (F = 4.40, p = 0.001). A greater proportion of drivers with osteoporosis (χ2 = 21.23, p = 0.020) and osteo/rheumatoid arthritis (χ2 = 21.23, p = 0.020) drove small and medium-sized cars compared to larger ones. Further research is needed to examine older driver-vehicle interactions, and the relationship to demographics and functional abilities, given the vulnerability of this age group to automotive-related injuries.

Effects of vehicle power on passenger vehicle speeds.

PubMed

McCartt, Anne T; Hu, Wen

2017-07-04

During the past 2 decades, there have been large increases in mean horsepower and the mean horsepower-to-vehicle weight ratio for all types of new passenger vehicles in the United States. This study examined the relationship between travel speeds and vehicle power, defined as horsepower per 100 pounds of vehicle weight. Speed cameras measured travel speeds and photographed license plates and drivers of passenger vehicles traveling on roadways in Northern Virginia during daytime off-peak hours in spring 2013. The driver licensing agencies in the District of Columbia, Maryland, and Virginia provided vehicle information numbers (VINs) by matching license plate numbers with vehicle registration records and provided the age, gender, and ZIP code of the registered owner(s). VINs were decoded to obtain the curb weight and horsepower of vehicles. The study focused on 26,659 observed vehicles for which information on horsepower was available and the observed age and gender of drivers matched vehicle registration records. Log-linear regression estimated the effects of vehicle power on mean travel speeds, and logistic regression estimated the effects of vehicle power on the likelihood of a vehicle traveling over the speed limit and more than 10 mph over the limit. After controlling for driver characteristics, speed limit, vehicle type, and traffic volume, a 1-unit increase in vehicle power was associated with a 0.7% increase in mean speed, a 2.7% increase in the likelihood of a vehicle exceeding the speed limit by any amount, and an 11.6% increase in the likelihood of a vehicle exceeding the limit by 10 mph. All of these increases were highly significant. Speeding persists as a major factor in crashes in the United States. There are indications that travel speeds have increased in recent years. The current findings suggest the trend toward substantially more powerful vehicles may be contributing to higher speeds. Given the strong association between travel speed and crash risk and crash severity, this is cause for concern.

Hypersonic Wind Tunnel Test of a Flare-type Membrane Aeroshell for Atmospheric Entry Capsules

NASA Astrophysics Data System (ADS)

Yamada, Kazuhiko; Koyama, Masashi; Kimura, Yusuke; Suzuki, Kojiro; Abe, Takashi; Koichi Hayashi, A.

A flexible aeroshell for atmospheric entry vehicles has attracted attention as an innovative space transportation system. In this study, hypersonic wind tunnel tests were carried out to investigate the behavior, aerodynamic characteristics and aerodynamic heating environment in hypersonic flow for a previously developed capsule-type vehicle with a flare-type membrane aeroshell made of ZYLON textile sustained by a rigid torus frame. Two different models with different flare angles (45º and 60º) were tested to experimentally clarify the effect of flare angle. Results indicate that flare angle of aeroshell has significant and complicate effect on flow field and aerodynamic heating in hypersonic flow at Mach 9.45 and the flare angle is very important parameter for vehicle design with the flare-type membrane aeroshell.

Environmental Compliance Assessment System (ECAS). Connecticut Supplement

DTIC Science & Technology

1994-09-01

Applicator - any individual who uses or supervises the use of any restricted-use pesticides or any pesticide on property not owned or rented by the...for entry onto the property by pedes- trians or motor vehicles. " Restricted-Use Pesticide - any pesticide --: pesticide use classified as restricted...personnel making an outdoor application of a pesticide within application requires 100 yd of any property line post a sign at the time of application

Prospects for Classifying Complex Imagery Using a Self-Organizing Neural Network

DTIC Science & Technology

1989-01-11

complex imagery. In his original re- port, Fukushima demonstrated that this system could discriminate between simple alphabetical characters...on a VAX-8600 minicomputer. Wire frame models of three different vehicles were used to test the properties which Fukushima had demonstrated. The...Table No. Page 3-1 Parameters for Training on Three Input Images 14 3-2 Trained Results 17 vn 1. INTRODUCTION The Neocognitron of Fukushima [2

Highlights of the Department of the Navy FY 2013 Budget

DTIC Science & Technology

2012-02-01

ability to perform undersea warfare to include high altitude launched torpedo capability, surface warfare and ISR missions make it a critical force...60B and SH-60F helicopters, whose primary mission areas are undersea warfare and surface warfare. This platform will have numerous capability...sensors to detect, localize, classify and identify undersea threats at a safe distance from friendly ships. The Remote Multi-Mission Vehicle provides

Proceedings of the Second Manned Space Flight Meeting

NASA Technical Reports Server (NTRS)

1964-01-01

The papers presented in this report represent the classified portion of the Second Manned Space Flight Meeting which was held in Dallas, TX, on April 22-24, 1963. The meeting was co-sponsored by the American Institute of Aeronautics and Astronautics and the National Aeronautics and Space Administration. The following subjects are discussed in the report: Manned Space Flight Programs, Launch Vehicles, Spacecraft Design, and Guidance and Control.

Active Optical Sensors for Tree Stem Detection and Classification in Nurseries

PubMed Central

Garrido, Miguel; Perez-Ruiz, Manuel; Valero, Constantino; Gliever, Chris J.; Hanson, Bradley D.; Slaughter, David C.

2014-01-01

Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops. PMID:24949638

Correlation of black smoke and nitrogen oxides emissions through field testing of in-use diesel vehicles.

PubMed

Lin, Cherng-Yuan; Chen, Lih-Wei; Wang, Li-Ting

2006-05-01

Diesel vehicles are one of the major forms of transportation, especially in metropolitan regions. However, air pollution released from diesel vehicles causes serious damage to both human health and the environment, and as a result is of great public concern. Nitrogen oxides and black smoke are two significant emissions from diesel engines. Understanding the correlation between these two emissions is an important step toward developing the technology for an appropriate strategy to control or eliminate them. This study field-tested 185 diesel vehicles at an engine dynamometer station for their black smoke reflectivity and nitrogen oxides concentration to explore the correlation between these two pollutants. The test results revealed that most of the tested diesel vehicles emitted black smoke with low reflectivity and produced low nitrogen oxides concentration. The age of the tested vehicles has a significant influence on the NOx emission. The older the tested vehicles, the higher the NOx concentrations emitted, however, there was no obvious correlation between the age of the tested diesel vehicles and the black smoke reflectivity. In addition, if the make and engine displacement volume of the tested diesel vehicles are not taken into consideration, then the correlation between the black smoke reflectivity and nitrogen oxides emission weakens. However, when the tested vehicles were classified into various groups based on their makes and engine displacement volumes, then the make of a tested vehicle became a dominant factor for both the quantity and the trend of the black smoke reflectivity, as well as the NOx emission. Higher emission indices of black smoke reflectivity and nitrogen oxides were observed if the diesel vehicles were operated at low engine speed and full engine load conditions. Moreover, the larger the displacement volume of the engine of the tested vehicle, the lower the emission indices of both black smoke reflectivity and nitrogen oxides emitted. The emission indices of black smokes reflectivity and nitrogen oxides emission of the tested diesel vehicles were also influenced by the make of the vehicle. It was observed that the emission indices of black smoke reflectivity decreased nearly linearly with the increase of the emission indices of NOx for the tested vehicles belonging to the same group of make and engine displacement volume.

Bayesian network classifiers for categorizing cortical GABAergic interneurons.

PubMed

Mihaljević, Bojan; Benavides-Piccione, Ruth; Bielza, Concha; DeFelipe, Javier; Larrañaga, Pedro

2015-04-01

An accepted classification of GABAergic interneurons of the cerebral cortex is a major goal in neuroscience. A recently proposed taxonomy based on patterns of axonal arborization promises to be a pragmatic method for achieving this goal. It involves characterizing interneurons according to five axonal arborization features, called F1-F5, and classifying them into a set of predefined types, most of which are established in the literature. Unfortunately, there is little consensus among expert neuroscientists regarding the morphological definitions of some of the proposed types. While supervised classifiers were able to categorize the interneurons in accordance with experts' assignments, their accuracy was limited because they were trained with disputed labels. Thus, here we automatically classify interneuron subsets with different label reliability thresholds (i.e., such that every cell's label is backed by at least a certain (threshold) number of experts). We quantify the cells with parameters of axonal and dendritic morphologies and, in order to predict the type, also with axonal features F1-F4 provided by the experts. Using Bayesian network classifiers, we accurately characterize and classify the interneurons and identify useful predictor variables. In particular, we discriminate among reliable examples of common basket, horse-tail, large basket, and Martinotti cells with up to 89.52% accuracy, and single out the number of branches at 180 μm from the soma, the convex hull 2D area, and the axonal features F1-F4 as especially useful predictors for distinguishing among these types. These results open up new possibilities for an objective and pragmatic classification of interneurons.

Safety of the Japanese K-car in a real-world low-severity frontal collision.

PubMed

Hitosugi, Masahito; Matsui, Yasuhiro

2015-01-01

Kei-cars (K-cars), which are a tiny 660 cc mini-car class 3.4 m long or less, 1.48 m wide or less, and 2.00 m high or less, have become popular in Japan. To evaluate the safety of K-car drivers in frontal collisions, we retrospectively compared the severity of injuries suffered by drivers between K-cars and standard vehicles involved in frontal collisions in which at least one injury occurred. From in-depth data provided by the Institute for Traffic Accident Research and Data Analysis from 1993 to 2010, records for 1379 drivers aged 36.8 ± 15.6 years were collected for analysis. Of the 1379 drivers, 1115 subjects were in standard vehicles and 264 were in K-cars. The mean delta V of the struck vehicle was 28.6 ± 15.6 km/h. After classifying the subjects according to seat belt use and air bag deployment, the background of the drivers and delta V, the injury severity scores (ISSs) and Abbreviated Injury Scale (AIS) scores were compared for all body regions. Under similar conditions, no significant differences in severity of injuries of the drivers were found between K-cars and standard vehicles. Although we are generally concerned that drivers of small vehicles suffer more severe injuries, our results suggest that, for real-world accidents, K-cars provide similar safety for drivers involved in frontal collisions as standard vehicles in low delta V impact conditions.

Acoustically active liposome-nanobubble complexes for enhanced ultrasonic imaging and ultrasound-triggered drug delivery.

PubMed

Nguyen, An T; Wrenn, Steven P

2014-01-01

Ultrasound is well known as a safe, reliable imaging modality. A historical limitation of ultrasound, however, was its inability to resolve structures at length scales less than nominally 20 µm, which meant that classical ultrasound could not be used in applications such as echocardiography and angiogenesis where one requires the ability to image small blood vessels. The advent of ultrasound contrast agents, or microbubbles, removed this limitation and ushered in a new wave of enhanced ultrasound applications. In recent years, the microbubbles have been designed to achieve yet another application, namely ultrasound-triggered drug delivery. Ultrasound contrast agents are thus tantamount to 'theranostic' vehicles, meaning they can do both therapy (drug delivery) and imaging (diagnostics). The use of ultrasound contrast agents as drug delivery vehicles, however, is perhaps less than ideal when compared to traditional drug delivery vehicles (e.g., polymeric microcapsules and liposomes) which have greater drug carrying capacities. The drawback of the traditional drug delivery vehicles is that they are not naturally acoustically active and cannot be used for imaging. The notion of a theranostic vehicle is sufficiently intriguing that many attempts have been made in recent years to achieve a vehicle that combines the echogenicity of microbubbles with the drug carrying capacity of liposomes. The attempts can be classified into three categories, namely entrapping, tethering, and nesting. Of these, nesting is the newest-and perhaps the most promising. © 2014 Wiley Periodicals, Inc.

Highway measurements of vehicle-induced turbulence (VIT) and enhanced mixing in the surface layer

NASA Astrophysics Data System (ADS)

Miller, S. J.; Gordon, M.; Staebler, R. M.; Li-Chee-Ming, J.; Taylor, P.

2016-12-01

Motor vehicles generate vehicle-induced turbulence (VIT) while in motion, which affects the mixing and transport of emitted trace gases, heat and momentum. During July, 2016 a 40Hz sonic anemometer (ATI) and a co-located 20Hz open path CO2/H2O gas analyzer (LICOR) were assembled and driven on highways in the Greater Toronto Area. An ultra-high sensitivity aerosol spectrometer was employed to measure the total number concentration of particles between 60 and 1000nm at the position of the gas analyzer and sonic anemometer. A video camera with GPS capabilities was also utilized to assess the surrounding features while chasing a specific vehicle type. The following distance of each chased vehicle is calculated as a function of pixel location, with the back edge of each followed vehicle being identified as the initial contrast between the vehicle's shadow and the roadway. Combining the sonic anemometer data with the GPS data allows turbulence statistics to be developed and correlations with vehicle type and following distance to be examined. Vehicle-induced turbulence is assessed using turbulent kinetic energy (TKE), a measure of turbulent mixing, which maximizes near the followed vehicle and decreases with increasing following distance. Vehicle exhaust plumes are identified using the measured CO2 concentration. The CO2 concentration data in conjunction with TKE and turbulent fluxes are used to explore the potential impacts of vehicle-induced turbulence on atmospheric mixing within the surface layer.

Operational use of Landsat data for timber inventory

NASA Technical Reports Server (NTRS)

Price, Curtis V.; Bowlin, Harry L.

1987-01-01

Landsat TM data, digital elevation model (DEM) data, and field observations were used to generate a timber type/structure and land-cover strata map of the Sequoia National Forest in California, U.S. and to create a classification data set. The spectral classes were identified as 32 information classes of land cover or timber type and structure. DEM data were used for the determination of major timber specie types by topographic regions of natural occurrence. The results suggest that, for inventories over large areas, traditional per-pixel classifiers are not appropriate for TM-resolution data sets over spatially complex regions such as forest lands; either resolution must be degraded, or more context-dependent classifiers, such as the ECHO classifier described by Landgrebe (1979), must be used.

49 CFR 565.26 - Reporting requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN.... Once confirmed by SAE, the identifier need not be resubmitted to NHTSA. (b) Manufacturers of vehicles... make and type of vehicle it manufactures at least 60 days before affixing the first VIN using the...

49 CFR 565.26 - Reporting requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN.... Once confirmed by SAE, the identifier need not be resubmitted to NHTSA. (b) Manufacturers of vehicles... make and type of vehicle it manufactures at least 60 days before affixing the first VIN using the...

49 CFR 565.16 - Reporting requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... NHTSA. (b) Manufacturers of vehicles subject to this part shall submit, either directly or through an agent, the unique identifier for each make and type of vehicle it manufactures at least 60 days before...

49 CFR 565.26 - Reporting requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN.... Once confirmed by SAE, the identifier need not be resubmitted to NHTSA. (b) Manufacturers of vehicles... make and type of vehicle it manufactures at least 60 days before affixing the first VIN using the...

49 CFR 565.16 - Reporting requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... NHTSA. (b) Manufacturers of vehicles subject to this part shall submit, either directly or through an agent, the unique identifier for each make and type of vehicle it manufactures at least 60 days before...

49 CFR 565.16 - Reporting requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... NHTSA. (b) Manufacturers of vehicles subject to this part shall submit, either directly or through an agent, the unique identifier for each make and type of vehicle it manufactures at least 60 days before...

49 CFR 565.26 - Reporting requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN.... Once confirmed by SAE, the identifier need not be resubmitted to NHTSA. (b) Manufacturers of vehicles... make and type of vehicle it manufactures at least 60 days before affixing the first VIN using the...

49 CFR 565.26 - Reporting requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS Alternative VIN.... Once confirmed by SAE, the identifier need not be resubmitted to NHTSA. (b) Manufacturers of vehicles... make and type of vehicle it manufactures at least 60 days before affixing the first VIN using the...

49 CFR 565.16 - Reporting requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... NHTSA. (b) Manufacturers of vehicles subject to this part shall submit, either directly or through an agent, the unique identifier for each make and type of vehicle it manufactures at least 60 days before...

49 CFR 565.16 - Reporting requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION VEHICLE IDENTIFICATION NUMBER (VIN) REQUIREMENTS VIN Requirements... NHTSA. (b) Manufacturers of vehicles subject to this part shall submit, either directly or through an agent, the unique identifier for each make and type of vehicle it manufactures at least 60 days before...