Download or read book Longitudinal Driving Behavior written by Saskia Josephina Leontine Ossen and published by . This book was released on 2008 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Empirical Research and Modeling of Longitudinal Driving Behavior Under Adverse Conditions written by Raymond Gerard Hoogendoorn and published by . This book was released on 2012 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development of Personalized Lateral and Longitudinal Driver Behavior Models for Optimal Human vehicle Interactive Control written by Scott C. Schnelle and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced driver assistance systems (ADAS) are a subject of increasing interest as they are being implemented on production vehicles and also continue to be developed and researched. These systems need to work cooperatively with the human driver to increase vehicle driving safety and performance. Such a cooperation requires the ADAS to work with the specific driver with some knowledge of the human driver’s driving behavior. To aid such cooperation between human drivers and ADAS, driver models are necessary to replicate and predict human driving behaviors and distinguish among different drivers. This dissertation presents several lateral and longitudinal driver models developed based on human subject driving simulator experiments that are able to identify different driver behaviors through driver model parameter identification. The lateral driver model consists of a compensatory transfer function and an anticipatory component and is integrated with the design of the individual driver’s desired path. The longitudinal driver model works with the lateral driver model by using the same desired path parameters to model the driver’s velocity control based on the relative velocity and relative distance to the preceding vehicle. A feedforward component is added to the feedback longitudinal driver model by considering the driver’s ability to regulate his/her velocity based on the curvature of his/her desired path. This interconnection between the longitudinal and lateral driver models allows for fewer driver model parameters and an increased modeling accuracy. It has been shown that the proposed driver model can replicate individual driver’s steering wheel angle and velocity for a variety of highway maneuvers. The lateral driver model is capable of predicting the infrequent collision avoidance behavior of the driver from only the driver’s daily driving habits. This is important due to the fact that these collision avoidance maneuvers require high control skills from the driver and the ADAS intervention offers the most benefits, but they happen very infrequently so previous knowledge of driver behavior during these incidents cannot be assumed to be known. The contributions of this dissertation include 1) an anticipatory and compensatory lateral driver steering model capable of modeling a wide range of in-city and highway maneuvers at a variety of speeds, 2) the combination of the lateral driver model with the addition of defining an individual driver’s desired path which allows for increased modeling accuracy, 3) a predictive lateral driver model that can predict a driver’s collision avoidance steering wheel angle signal with no prior knowledge of the driver’s collision avoidance behavior, only data from every day, standard driving, 4) the addition of a longitudinal driver model that works with the existing lateral driver model by using the same desired path and is capable of replicating an individual driver’s standard highway and collision avoidance behavior, and 5) A feedforward longitudinal driver model based on regulating the driver’s velocity along his/her desired path is added to the existing feedback longitudinal driver model that together are capable of modeling an individual driver’s velocity for lane-changing and collision-avoidance maneuvers with less than 0.45 m/s (1 mph) average error.

Download or read book Handbook of Traffic Psychology written by Bryan E. Porter and published by Academic Press. This book was released on 2011-06-22 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Traffic Psychology covers all key areas of research in this field including theory, applications, methodology and analyses, variables that affect traffic, driver problem behaviors, and countermeasures to reduce risk on roadways. Comprehensive in scope, the methodology section includes case-control studies, self-report instruments and methods, field methods and naturalistic observational techniques, instrumented vehicles and in-car recording techniques, modeling and simulation methods, in vivo methods, clinical assessment, and crash datasets and analyses. Experienced researchers will better understand what methods are most useful for what kinds of studies and students can better understand the myriad of techniques used in this discipline. Focuses specifically on traffic, as opposed to transport Covers all key areas of research in traffic psychology including theory, applications, methodology and analyses, variables that affect traffic, driver problem behaviors, and countermeasures to reduce the risk of variables and behavior Contents include how to conduct traffic research and how to analyze data Contributors come from more than 10 countries, including US, UK, Japan, Netherlands, Ireland, Switzerland, Mexico, Australia, Canada, Turkey, France, Finland, Norway, Israel, and South Africa

Download or read book Behavior Analysis and Modeling of Traffic Participants written by Xiaolin Song and published by Springer Nature. This book was released on 2022-06-01 with total page 160 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.

Download or read book Automotive Control written by Rolf Isermann and published by Springer. This book was released on 2016-09-08 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: The introduction of mechatronic components for the powertrain, steering and braking systems opens the way to automatic driving functions. Together with internal and environmental sensors, various driver assistance systems are going to be developed for improving driving comfort and safety. Automatic driving control functions suppose a well-designed vehicle behavior. In order to develop and implement the software-based control functions mathematical vehicle models for the stationary and dynamic behavior are required. The book first introduces basic theoretically derived models for the tire traction and force transfer, the longitudinal, lateral, roll and pitch dynamic behavior and related components, like suspensions, steering systems and brakes. These models have to be tailored to allow an identification of the many unknown parameters during driving, also in dependence of different road conditions, velocity and vehicle load. Based on these mathematical models drive dynamic control systems are developed for semi-active and active suspensions, hydraulic and electromechanical brakes including ABS, traction and steering control. Then driver assistance systems like adaptive cruise control (ACC), electronic stability control (ESC), electronic course control and anti-collision control systems are considered. The anti-collision systems are designed and tested for emergency braking, emergency steering and avoiding of overtaking accidents. The book is dedicated to automotive engineers as well as to graduate students of mechanical, electrical and mechatronic engineering and computer science.

Download or read book An Analysis of Naturalistic Driver Data in Evaluating Vehicle Longitudinal Control Systems written by Kevin Christopher Lin and published by . This book was released on 2017 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: As vehicles with advanced driver assistance systems such as adaptive cruise control (ACC) become more common on the roads, many people have begun to raise concerns about their safety and control. The National Highway Traffic Safety Administration (NHTSA) is actively pursuing research in the performance and safety of different types of these systems in an effort to guide their development and to ensure that they are safe to the public. One fundamental aspect of this pursuit is gaining an understanding of human driver behaviors under normal driving conditions. This document presents an analysis of naturalistic driver data as a means to gage the performance and guide development of vehicle longitudinal control systems such as ACC. First, an analysis of the steady-state behavior is discussed, using a frequency content based approach and method to study and extract significant amounts of data. Next, a method is proposed that uses this extracted data to stochastically replicate these behaviors over indefinitely long periods of time. A second analysis of the same set of naturalistic data is also performed to guide the development of a simplified model of an ACC system based on a second-order single degree-of-freedom (SDOF) mass-spring-damper model. The study of the relationship between the behavior of the leading vehicle and the subsequent behavior of the following vehicle is of particular interest as it is used to gage the performance of the aforementioned ACC model under a series of three different inputs.

Download or read book Traffic Safety and Human Behavior written by David Shinar and published by Emerald Group Publishing. This book was released on 2017-06-22 with total page 1262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive 2nd edition covers the key issues that relate human behavior to traffic safety. In particular it covers the increasing roles that pedestrians and cyclists have in the traffic system; the role of infotainment in driver distraction; and the increasing role of driver assistance systems in changing the driver-vehicle interaction.

Download or read book Longitudinal Driver Model and Collision Warning and Avoidance Algorithms Based on Human Driving Databases written by Kangwon Lee and published by . This book was released on 2004 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Traffic Flow Dynamics written by Martin Treiber and published by Springer Science & Business Media. This book was released on 2012-10-11 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on traffic instabilities and model calibration/validation present these topics in a novel and systematic way. Finally, the theoretical framework is shown at work in selected applications such as traffic-state and travel-time estimation, intelligent transportation systems, traffic operations management, and a detailed physics-based model for fuel consumption and emissions.

Download or read book Human Performance User Information and Simulation 2013 written by and published by . This book was released on 2013 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: "TRB Transportation Research Record: Journal of the Transportation Research Board, No. 2365 consists of 13 papers that explore driver performance and distraction; the effects of chevron alignment signs; longitudinal driving behavior with integrated crash-warning systems; in-vehicle stopping decision advisory systems; interactions with navigation systems and mobile phones while driving; road safety differences between priority-controlled intersections and right-hand priority intersections; drivers' cell phone use; speeding behavior; cell phone and texting among drivers in California; travel time reliability forecasting; business logo signing; road safety and behavioral analysis software; and drivers' stop-or-run behavior at signalized intersections."--pub. desc.

Download or read book Driver Behavior and Performance in an Age of Increasingly Instrumented Vehicles written by Oren Musicant and published by Frontiers Media SA. This book was released on 2021-09-29 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Self regulation of the Driving Behaviour of Older Drivers written by James Peter Thompson and published by . This book was released on 2007 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Intelligent Vehicles written by Azim Eskandarian and published by Springer. This book was released on 2012-02-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Intelligent Vehicles provides a complete coverage of the fundamentals, new technologies, and sub-areas essential to the development of intelligent vehicles; it also includes advances made to date, challenges, and future trends. Significant strides in the field have been made to date; however, so far there has been no single book or volume which captures these advances in a comprehensive format, addressing all essential components and subspecialties of intelligent vehicles, as this book does. Since the intended users are engineering practitioners, as well as researchers and graduate students, the book chapters do not only cover fundamentals, methods, and algorithms but also include how software/hardware are implemented, and demonstrate the advances along with their present challenges. Research at both component and systems levels are required to advance the functionality of intelligent vehicles. This volume covers both of these aspects in addition to the fundamentals listed above.

Download or read book Traffic Data Collection and its Standardization written by Jaume Barceló and published by Springer Science & Business Media. This book was released on 2010-07-20 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: A nice night of October 2007, in Beijing, during the XV World Conference on ITS a number of colleagues met informally for a dinner party that spontaneously became a vivid discussion on the importance of traffic data for all types of p- poses. Researchers can hardly do any progress in modeling, developing, and te- ing theories without suitable data, and what practitioners can do in real life is limited not only by technology but also by the availability of the required data. Quite frequently, the data and not the technologies are what determine how far we can go. Any discussion about traffic data leads in a natural way to a discussion on the variety of traffic data sources, formats, levels of aggregation, accuracies, and so on. Consequently, we moved to talk on the initiative that Kuwahara had undertaken in his traffic laboratory at the University of Tokyo, known as the International Traffic Data Base, and thus smoothly but inexorably we came to agree that it would be convenient to organize a workshop to continue our discussion at a more formal level, share our points of view with other colleagues, listen what they had to say and, if possible, d- seminate the findings in our professional and academic communities.

Download or read book Advances in Intelligent Vehicles written by Yaobin Chen and published by Academic Press. This book was released on 2014-03-20 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Intelligent Vehicles presents recent advances in intelligent vehicle technologies that enhance the safety, reliability, and performance of vehicles and vehicular networks and systems. This book provides readers with up-to-date research results and cutting-edge technologies in the area of intelligent vehicles and transportation systems. Topics covered include virtual and staged testing scenarios, collision avoidance, human factors, and modeling techniques. The Series in Intelligent Systems publishes titles that cover state-of-the-art knowledge and the latest advances in research and development in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. Provides researchers and engineers with up-to-date research results and state-of-the art technologies in the area of intelligent vehicles and transportation systems Covers hot topics, including driver assistance systems; cooperative vehicle-highway systems; collision avoidance; pedestrian protection; image, radar and lidar signal processing; and V2V and V2I communications

Download or read book Behavior Modeling and Motion Planning for Autonomous Driving Using Artificial Intelligence written by Meixin Zhu and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With an emphasis on longitudinal driving, this dissertation aims to develop data-driven models that improve existing driving behavior models and facilitate various kinds of autonomous driving planning. The first part of this work focuses on behavior modeling, which falls within the background of microscopic traffic simulation, traffic flow theory, and motion prediction. Two different driving behavior models are proposed. To model the long-term dependency of future actions on historical driving situations, a long-sequence car-following trajectory prediction model is developed using the attention-based Transformer model. The model follows a general format of encoder-decoder architecture. The encoder takes historical speed and spacing data as inputs and forms a mixed representation of historical driving context using multi-head self-attention. The decoder takes the future lead vehicle speed profile as input and outputs the predicted future following speed profile in a generative way (instead of an auto-regressive way, avoiding compounding errors). The second part of this work extends the single forward-pass of behavior prediction in the first part to the sequential motion planning of autonomous driving. Based on different demands, two motion planning algorithms are proposed for autonomous longitudinal driving. To learn a driving policy that can do closed-loop sequential planning and imitate human drivers' behavior, a framework for human-like autonomous car-following planning based on deep reinforcement learning (RL) is proposed. Car-following dynamics are encoded into a simulation environment, and a reward function that signals how much the agent deviates from the empirical data is used to encourage behavioral imitation. It was found that using RL for imitation learning purposes can well address the distribution shift issue. This is the first study that uses RL to address the distribution shift issue for imitation-orientated longitudinal motion planning. To propose a safe, efficient, and comfortable velocity planning method for autonomous driving, a multi-objective velocity planning method based on RL is proposed. To directly optimize driving performance, a reward function is developed by referencing human driving data and combining driving features related to safety, efficiency, and comfort. It was found that the proposed model demonstrates the capability of safe, efficient, and comfortable velocity control and outperforms human drivers.