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Feasibility Of Using In Vehicle Video Data To Explore How To Modify Driver Behavior That Causes Nonrecurring Congestion
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Book Synopsis Feasibility of Using In-Vehicle Video Data to Explore How to Modify Driver Behavior That Causes Nonrecurring Congestion by : Hesham Rakha
Download or read book Feasibility of Using In-Vehicle Video Data to Explore How to Modify Driver Behavior That Causes Nonrecurring Congestion written by Hesham Rakha and published by Transportation Research Board. This book was released on 2011 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: TRB’s second Strategic Highway Research Program (SHRP 2) Report S2-L10-RR-1: Feasibility of Using In-Vehicle Video Data to Explore How to Modify Driver Behavior That Causes Nonrecurring Congestion presents findings on the feasibility of using existing in-vehicle data sets, collected in naturalistic driving settings, to make inferences about the relationship between observed driver behavior and nonrecurring congestion.
Book Synopsis Feasibility of Using In-Vehicle Video Data to Explore How to Modify Driver Behavior That Causes Nonrecurring Congestion by :
Download or read book Feasibility of Using In-Vehicle Video Data to Explore How to Modify Driver Behavior That Causes Nonrecurring Congestion written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Highway Research written by David J. Wise and published by DIANE Publishing. This book was released on 2010-11 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2005 Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users authorized the Dept. of Transportation (DoT) to establish a highway research program to address future challenges facing the U.S. highway system. In 2006, the Second Strategic Highway Research Program was established to conduct research in four areas -- safety, renewal, reliability, and capacity. The legislation also required a review of the program no later than three years after the first research contracts were awarded. This report provides information about the process for selecting the program's projects for funding, the projects' status, and what, if any, research was eliminated because of funding and time constraints. Charts and tables.
Author :Brandon Nevers, Kittelson & Associates, Inc. Alan F. Karr, National Institute of Statistical Sciences Xuesong Zhou, University of Utah: Jeffrey Wojtowicz, Rensselaer Polytechnic Institute Joseph Schofer, Northwestern University Asad Khatty, Planitek Transportation Research Board, Publisher :Transportation Research Board ISBN 13 :0309274524 Total Pages :936 pages Book Rating :4.3/5 (92 download)
Book Synopsis Guide to Establishing Monitoring Programs for Travel Time Reliability by : Brandon Nevers, Kittelson & Associates, Inc. Alan F. Karr, National Institute of Statistical Sciences Xuesong Zhou, University of Utah: Jeffrey Wojtowicz, Rensselaer Polytechnic Institute Joseph Schofer, Northwestern University Asad Khatty, Planitek Transportation Research Board,
Download or read book Guide to Establishing Monitoring Programs for Travel Time Reliability written by Brandon Nevers, Kittelson & Associates, Inc. Alan F. Karr, National Institute of Statistical Sciences Xuesong Zhou, University of Utah: Jeffrey Wojtowicz, Rensselaer Polytechnic Institute Joseph Schofer, Northwestern University Asad Khatty, Planitek Transportation Research Board, and published by Transportation Research Board. This book was released on with total page 936 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report from the second Strategic Highway Research Program (SHRP 2), which is administered by the Transportation Research Board of the National Academies, describes how to develop and use a Travel Time Reliability Monitoring System (TTRMS). It explains why such a system is useful, how it helps agencies do a better job of managing network performance, and what a traffic management center (TMC) team needs to do to put a TTRMS in place.
Download or read book SHRP 2 Report S2-L10-RR-1 written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :National Research Council (U.S.). Transportation Research Board. Committee for the Strategic Highway Research Program 2: Implementation Publisher : ISBN 13 : Total Pages :188 pages Book Rating :4.:/5 (1 download)
Book Synopsis Implementing the Results of the Second Strategic Highway Research Program by : National Research Council (U.S.). Transportation Research Board. Committee for the Strategic Highway Research Program 2: Implementation
Download or read book Implementing the Results of the Second Strategic Highway Research Program written by National Research Council (U.S.). Transportation Research Board. Committee for the Strategic Highway Research Program 2: Implementation and published by . This book was released on 2009 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: "(SHRP 2): Saving Lives, Reducing Congestion, Improving Quality of Life explores promising results expected from the SHRP 2 research and provides recommendations on how they could be most effectively implemented. The committee that developed the report believes that the widespread implementation of products developed by SHRP 2 is critical in order to address the nation's roadway safety, renewal, reliability, and capacity issues." -- provided by publisher.
Book Synopsis Using Digital Video Analysis to Monitor Driver Behavior at Intersections by : Derrick Parkhurst
Download or read book Using Digital Video Analysis to Monitor Driver Behavior at Intersections written by Derrick Parkhurst and published by . This book was released on 2006 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Commercially available instruments for road-side data collection take highly limited measurements, require extensive manual input, or are too expensive for widespread use. However, inexpensive computer vision techniques for digital video analysis can be applied to automate the monitoring of driver, vehicle, and pedestrian behaviors. These techniques can measure safety-related variables that cannot be easily measured using existing sensors. The use of these techniques will lead to an improved understanding of the decisions made by drivers at intersections. These automated techniques allow the collection of large amounts of safety-related data in a relatively short amount of time. There is a need to develop an easily deployable system to utilize these new techniques. This project implemented and tested a digital video analysis system for use at intersections. A prototype video recording system was developed for field deployment. A computer interface was implemented and served to simplify and automate the data analysis and the data review process. Driver behavior was measured at urban and rural non-signalized intersections. Recorded digital video was analyzed and used to test the system.
Book Synopsis Driving Volatility in Instantaneous Driving Behaviors by : Jun Liu
Download or read book Driving Volatility in Instantaneous Driving Behaviors written by Jun Liu and published by . This book was released on 2015 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasing amounts of data, generated by electronic sensors from various sources that include travelers, vehicles, infrastructure and the environment, referred to as “Big Data”, represent an opportunity for innovation in transportation systems and toward achieving safety, mobility and sustainability goals. The dissertation takes advantage of large-scale trajectory data coupled with travel behavioral information and containing 78 million second-by-second driving records from 100 thousand trips made by nearly four thousand drivers. The data covers 70 counties across the State of California and Georgia, representing various land use types, roadway network conditions and population. The trajectories cover various driving practices made by vehicles of varied body types as well as different fuel types including conventional vehicles (CVs) consuming gasoline, hybrid electric vehicles (HEVs), battery electric vehicles (BEVs), diesel vehicles and other alternative fuel vehicles (AFVs). The dissertation establishes a framework for the research agenda in instantaneous driving behavior studies using the large-scale trajectory data. The dissertation makes both theoretical and empirical contributions: 1) Developing measures for driving volatility in instantaneous driving behaviors; 2) Understanding correlates of driving volatility in hierarchies & developing applications using large-scale trajectory data. Before using second-by-second trajectories, a study, answering research questions concerning the relationships between data sampling rates and information loss, was conducted. Then, a study for quantifying driving volatility in instantaneous driving behaviors was presented. “Driving volatility”, as the core concept in the dissertation, captures extreme driving patterns under seemingly normal conditions. After that, the dissertation presents a study on exploration of the hierarchical nature of driving volatility embedded in travel survey data using multi-level modeling techniques, and highlights the role of AFVs in travel. Last, the dissertation presents a study for customizing driving cycles for individuals using large-scale trajectory data, given heterogeneous driving performance across drivers and vehicle types. The customized driving cycles help generate more accurate fuel economy information to support cost-effective vehicle choices. The implications of the findings and potential applications to fleet vehicles and driving population are also discussed in the dissertation.
Book Synopsis Behavior Analysis and Modeling of Traffic Participants by : Xiaolin Song
Download or read book Behavior Analysis and Modeling of Traffic Participants written by Xiaolin Song and published by Synthesis Lectures on Advances. This book was released on 2021-12 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: A road traffic participant is a person who directly participates in road traffic, such as vehicle drivers, passengers, pedestrians, or cyclists, however, traffic accidents cause numerous property losses, bodily injuries, and even deaths to them. To bring down the rate of traffic fatalities, the development of the intelligent vehicle is a much-valued technology nowadays. It is of great significance to the decision making and planning of a vehicle if the pedestrians' intentions and future trajectories, as well as those of surrounding vehicles, could be predicted, all in an effort to increase driving safety. Based on the image sequence collected by onboard monocular cameras, we use the Long Short-Term Memory (LSTM) based network with an enhanced attention mechanism to realize the intention and trajectory prediction of pedestrians and surrounding vehicles. However, although the fully automatic driving era still seems far away, human drivers are still a crucial part of the road‒driver‒vehicle system under current circumstances, even dealing with low levels of automatic driving vehicles. Considering that more than 90 percent of fatal traffic accidents were caused by human errors, thus it is meaningful to recognize the secondary task while driving, as well as the driving style recognition, to develop a more personalized advanced driver assistance system (ADAS) or intelligent vehicle. We use the graph convolutional networks for spatial feature reasoning and the LSTM networks with the attention mechanism for temporal motion feature learning within the image sequence to realize the driving secondary-task recognition. Moreover, aggressive drivers are more likely to be involved in traffic accidents, and the driving risk level of drivers could be affected by many potential factors, such as demographics and personality traits. Thus, we will focus on the driving style classification for the longitudinal car-following scenario. Also, based on the Structural Equation Model (SEM) and Strategic Highway Research Program 2 (SHRP 2) naturalistic driving database, the relationships among drivers' demographic characteristics, sensation seeking, risk perception, and risky driving behaviors are fully discussed. Results and conclusions from this short book are expected to offer potential guidance and benefits for promoting the development of intelligent vehicle technology and driving safety.
Book Synopsis The Impact of In-vehicle Video Cameras on Unwanted Driver Behavior by : Jeffrey C. Devlin
Download or read book The Impact of In-vehicle Video Cameras on Unwanted Driver Behavior written by Jeffrey C. Devlin and published by . This book was released on 2010 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this project is to investigate whether driver behavior has been impacted by the presence of these cameras, specifically to address whether employee driving actions are improved by the presence of cameras and also whether apparatus operators have modified their behavior since the introduction of the cameras. After a process of evaluative and descriptive research, this examination indicates the clear ability of the drivecam to have a positive impact on unwanted behavior. The RMFD should continue to utilize this tool and the associated counseling and training activities of the Drivecams.
Book Synopsis Capturing and Analyzing Human Driving Behavior to Improve Road Travel Experience by : Ruilin Liu
Download or read book Capturing and Analyzing Human Driving Behavior to Improve Road Travel Experience written by Ruilin Liu and published by . This book was released on 2017 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: People commute on daily basis and spend a considerable amount of time on road travels. Unfortunately, due to the dense population and concentration of economic activities in metropolitan areas, urban transportation suffers a lot of challenges, e.g. traffic congestion and parking space storage, which also affect each individual's travel experience. Previous studies have looked into the transportation condition sensing solution using various static or mobile sensors and traffic related recommendation services based on the sensing results, e.g. vehicle routing and parking recommendation. However, human behaviors as the most direct reflection as well as the final modifier of the traffic condition, have not been fully explored to close the sensing-and-control loop in the urban transportation system. This dissertation aims at improving drivers' road travel experience by taking human driver's behavior in vehicle routing and parking search processes into consideration. In the first part of the dissertation, we focus on the traffic condition sensing and routing service design, altering the isolated traffic sensing and the greedy routing strategy based on sensed traffic condition. Instead, we present a participatory system, called Themis, to consider traffic sensing and route planning as a whole: (i) By analyzing time-stamped position reports and route decisions collected from the Themis mobile app, the Themis server estimates both the current traffic rhythm and the future traffic distribution. (ii) The routing requests are then combined with the sensed traffic condition to provide route recommendations that minimize the travel cost of all drivers to proactively alleviate traffic congestions. Themis has been implemented and its performance has been evaluated in both simulation experiments using real data from over 26,000 taxis and a field study. Results from both experiments demonstrate that Themis reduces traffic congestion and average travel time at various traffic densities and system penetration rates. In the second part of the dissertation, we look into the crucial part of parking recommendation, i.e., fine-grained parking availability crowdsourcing and propose a solution based on human's parking and ignoring decisions: a parking decision immediately take an available spot while an ignored spot along a driver's parking search trajectory is likely to be already taken. However, complications caused by drivers' preferences, e.g. ignoring the spots too far from the driver's destination, have to be addressed based on human parking decisions. We build a model based on a dataset of more than 55,000 real parking decisions to predict the probability that a driver would take a spot, assuming the spot is available. Then, we present a crowdsourcing system, called ParkScan, which leverages the learned parking decision model in collaboration with the hidden Markov model to estimate background parking spot availability. ParkScan has been evaluated using real-world data from both off-street scenarios (i.e., two public parking lots) and an on-street parking scenario (i.e., 35 urban blocks in Seattle). Both of the experiments show that ParkScan reduces the error of spot-level parking availability estimation compared to the state-of-art solutions. In particular, ParkScan cuts down over 15% of the estimation errors for the spots along parking search trajectory even if there is a single participant driver.
Book Synopsis Examining the Relationship Between Driver Distraction, Crash, and Near-crash Risk Using Naturalistic Driving Data by : Anshu Bamney
Download or read book Examining the Relationship Between Driver Distraction, Crash, and Near-crash Risk Using Naturalistic Driving Data written by Anshu Bamney and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distracted driving is among the leading causes of motor vehicle crashes worldwide, though the magnitude of this problem is difficult to quantify given the limitations of police-reported crash data. A more promising approach is to evaluate the impacts of distraction in real-world driving events. To that end, this study leverages data from the second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study (NDS) to gain important insights into the risks posed by driver distraction. The objectives of this study are to assess the risk of crash and near-crash events under different contextual environments based upon whether the driver was engaged in any secondary (i.e., non-driving related) tasks. The research also compares speed profiles of distracted drivers in low-speed and high-speed environments, providing important insights into how driver behavior changes based upon the type and intensity of distraction. The first analysis uses the standard SHRP 2 data to compare the differences between near-crash risks on limited access freeways and two-lane highways. Mixed-effects logistic regression models were estimated to discern how the risks of near-crash events varied by distraction type while controlling for the effects of driver, roadway, and traffic characteristics. In general, the risks were more pronounced for those distractions that were a combination of cognitive, visual, and manual distractions (for e.g., cell phone texting). While the same factors tended to increase near-crash risk on both types of facilities, the impacts of several factors tended to be more pronounced on two-lane highways where interaction with other vehicles occurred more frequently. The second analysis uses a subset of the NDS data that were focused on naturalistic engagement in secondary tasks (NEST). The NEST data were used to assess how the type and duration of distraction impacted the likelihood of crash and near-crash events. Separate comparisons were made between crashes and near-crashes with "normal" baseline driving events. The results show the duration of distraction to be a strong predictor of both crash and near-crash risk and were found to have similar relationships with crashes and near-crashes. The risks were highest for those secondary tasks that introduce a combination of visual and manual distractions that provides evidence that distractions requiring higher levels of engagement have more pronounced impacts on safety. The third and final analysis uses NEST data to analyze how driver speed selection varies based upon the types of secondary tasks that a driver is engaged in. Comparisons are made as to differences between high-speed and low-speed environments. Two-way random effects linear regression models were estimated for both speed regimes while controlling for driver, roadway, and traffic characteristics. In general, engagement in all tasks was found to decrease speeds in high-speed environments, while the effects were mixed in low-speed settings. These changes in speeds are much pronounced for secondary tasks that include a combination of visual, manual, and cognitive distractions, such as cell phone use. Among all secondary tasks, handheld cellphone talking was associated with highest speed changes in both environments followed by reaching/manipulating an object and holding an object. Ultimately, the results of this study provides further motivation for more aggressive legislation and enforcement against distracted driving. This can be achieved by enforcing strict laws and fines, graduated licensing process, public campaigns, modified infrastructure (rumble strips and tactile lane marking), and other such measures.
Book Synopsis Exploratory Advanced Research Program by :
Download or read book Exploratory Advanced Research Program written by and published by . This book was released on 2015 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: The flagship dataset to emerge from the Transportation Research Board's second Strategic Highway Research Program (SHRP 2) study is the naturalistic driving study (NDS). The study is a focus on driver behavior and addresses the notion that it is possible to obtain more and better information on what people do when they drive--not just in the moments before they get into a collision but on a day-to-day basis. Researchers for the NDS have gathered over 1.2-million hours of data, collected from the vehicles of approximately 3,000 volunteers going about their regular activities. Each of those vehicles was equipped with four cameras, a Global Positioning System (GPS), and many other sensors. Over 2 petabytes (2,000 terabytes) of data has been generated over a 2-year period, a majority of which comes from video captured by the onboard cameras. The massive size of the video data creates a serious data bottleneck for researchers and makes traditional methods for identifying features in the data, such as objects, behaviors, roadside design details, and surrounding vehicles, completely inadequate. Several video analytics research projects, funded by the EAR Program, aim to make data processing and analysis more practical by focusing on increasing the automation of video data decoding. The goal of these EAR Program projects is to assist researchers through the use of an algorithm designed to narrow down the amount of data researchers need to manually review. There are six ongoing video analytics projects funded by the EAR Program, all tasked with developing technology to make it feasible for a researcher to quickly and flexibly get what they need from an extremely large dataset. The following pages contain summary descriptions of the EAR Program-sponsored research projects investigating video analytics.
Book Synopsis Methods to Explore Driving Behavior Heterogeneity Using SHRP2 Naturalistic Driving Study Trajectory-level Driving Data by : Britton Elaine Hammit
Download or read book Methods to Explore Driving Behavior Heterogeneity Using SHRP2 Naturalistic Driving Study Trajectory-level Driving Data written by Britton Elaine Hammit and published by . This book was released on 2018 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding driving behavior and its impact on traffic flow is crucial for maintaining and operating the transportation network. Traffic analysis requires accurate representations of driving behavior—how different drivers drive and how the same driver adjusts to different driving scenarios—for the realistic development of predictive models. Heterogeneity in driving behavior impacts the capacity of the transportation network; therefore, it is crucial to account for this heterogeneity when planning, assessing alternatives, and managing real-time roadway operations. The recent availability of trajectory-level driving data offers researchers and practitioners an unprecedented opportunity to improve the depiction of driving behavior in microsimulation models. A review of literature clearly demonstrates a foundation for research in heterogeneous driving behaviors, yet countless unanswered questions and uninvestigated hypotheses remain. This dissertation is designed to connect the dots between the complex layers of theory, high resolution driving data, and behavioral analytics necessary for successful behavioral research. Starting with the formation of a hypothesis, this dissertation walks through the required steps for collecting data, processing those data, and analyzing driving behavior. At each pivotal point, contributions are made to bridge the gaps between the crucial elements of research, aspiring to add value to current and future studies. These contributions include (i) trajectory-level data sufficiency guidance, (ii) radar-vision data processing algorithms for instrumented vehicle data, (iii) recommendations for transparent and systematic procedures to calibrate car-following models, (iv) a trajectory simulation validation methodology for interpretation and validation of calibration results, and (v) an empirical car-following model developed from an Artificial Neural Network. Ultimately, an analytic framework is developed from these contributions and applied to trajectory-level data available through the second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study to investigate the influence of weather conditions on driving behavior. This case study exemplifies the impact that complex human behaviors have in traffic flow theory and the importance of using trajectory-level data to accurately calibrate driving behavior used in microsimulation models.
Book Synopsis Autonomous Vehicle Technology by : James M. Anderson
Download or read book Autonomous Vehicle Technology written by James M. Anderson and published by Rand Corporation. This book was released on 2014-01-10 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.
Book Synopsis Road Traffic Congestion: A Concise Guide by : John C. Falcocchio
Download or read book Road Traffic Congestion: A Concise Guide written by John C. Falcocchio and published by Springer. This book was released on 2015-03-13 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on road traffic congestion in cities and suburbs describes congestion problems and shows how they can be relieved. The first part (Chapters 1 - 3) shows how congestion reflects transportation technologies and settlement patterns. The second part (Chapters 4 - 13) describes the causes, characteristics, and consequences of congestion. The third part (Chapters 14 - 23) presents various relief strategies - including supply adaptation and demand mitigation - for nonrecurring and recurring congestion. The last part (Chapter 24) gives general guidelines for congestion relief and provides a general outlook for the future. The book will be useful for a wide audience - including students, practitioners and researchers in a variety of professional endeavors: traffic engineers, transportation planners, public transport specialists, city planners, public administrators, and private enterprises that depend on transportation for their activities.
Book Synopsis Experimental Immunology by : Joseph N. Blattman
Download or read book Experimental Immunology written by Joseph N. Blattman and published by Cognella Academic Publishing. This book was released on 2016-12-31 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
