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Author: Jerzy Kisilowski Publisher: Springer Nature ISBN: 3030913988 Category : Technology & Engineering Languages : en Pages : 309
Book Description
This books reviews and brings readers up to date with the latest research knowledge on road traffic safety. It describes and discusses mathematical descriptions of the process of a motor vehicle crash and indicates the various factors that impact on collision models. It tackles also vehicle stability and shows how the forces generated in crashes result in different extents of post-accident repair. Mathematical models that simulate vehicle stability data are compared with those of real vehicles. Practical uses of the models are explained to readers. The book will be of interest to researchers in transport and vehicle technology well as automotive industry professionals.
Author: Jerzy Kisilowski Publisher: Springer Nature ISBN: 3030913988 Category : Technology & Engineering Languages : en Pages : 309
Book Description
This books reviews and brings readers up to date with the latest research knowledge on road traffic safety. It describes and discusses mathematical descriptions of the process of a motor vehicle crash and indicates the various factors that impact on collision models. It tackles also vehicle stability and shows how the forces generated in crashes result in different extents of post-accident repair. Mathematical models that simulate vehicle stability data are compared with those of real vehicles. Practical uses of the models are explained to readers. The book will be of interest to researchers in transport and vehicle technology well as automotive industry professionals.
Author: Martin Treiber Publisher: Springer Science & Business Media ISBN: 3642324606 Category : Science Languages : en Pages : 505
Book Description
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.
Author: Antonella Ferrara Publisher: Springer ISBN: 3319759612 Category : Technology & Engineering Languages : en Pages : 324
Book Description
This monograph provides an extended overview of modelling and control approaches for freeway traffic systems, moving from the early methods to the most recent scientific results and field implementations. The concepts of green traffic systems and smart mobility are addressed in the book, since a modern freeway traffic management system should be designed to be sustainable. Future perspectives on freeway traffic control are also analysed and discussed with reference to the most recent technological advancements The most widespread modelling and control techniques for freeway traffic systems are treated with mathematical rigour, but also discussed with reference to their performance assessment and to the expected impact of their practical usage in real traffic systems. In order to make the book accessible to readers of different backgrounds, some fundamental aspects of traffic theory as well as some basic control concepts, useful for better understanding the addressed topics, are provided in the book. This monograph can be used as a textbook for courses on transport engineering, traffic management and control. It is also addressed to experts working in traffic monitoring and control areas and to researchers, technicians and practitioners of both transportation and control engineering. The authors’ systematic vision of traffic modelling and control methods developed over decades makes the book a valuable survey resource for freeway traffic managers, freeway stakeholders and transportation public authorities with professional interests in freeway traffic systems. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Author: Victor Muchuruza Publisher: ISBN: Category : Languages : en Pages :
Book Description
ABSTRACT: The deterioration of the safety of operation, coupled with the persistent increase in rearend crashes, is of great concern in finding accurate and realistic methods of modeling traffic flow and preventing traffic crashes. For some decades safety evaluation methods have relied on analysis of historical crash data. Since crashes are random and rare events and, in most cases, are independent events, it is difficult to find a sufficient number of crashes on a road section in a relatively short time period (e.g., a month or even a year). Thus, multi-year collection of crash data is used in safety analysis. Another safety evaluation method that has been practiced though in small scale is traffic conflict techniques (TCT). The advantage of using TCT in safety evaluations is the ability to test or study a safety strategy or improvement applied on the roadway facility in a relatively short period of time compared with traditional methods, which are dependent on crash data. However, use of TCT is not popular; perhaps because it needs extensive resources to collect, extract, and analyze conflict information. Moreover, like crash data analysis, use of TCT also makes concerned authorities reactive to the problem by responding to the crashes that have already occurred. Therefore, alternative proactive safety evaluation techniques that can improve the quality of traffic safety evaluation are needed at this time. One way of using proactive safety evaluation techniques and thus become more preventive than reactive towards dealing with the overall safety problem is to utilize the capability of traffic micro-simulation to assess safety on highways through examination of hazardous vehicle movements in the traffic stream. Using micro-simulation predictive methods, it may be possible to diagnose safety problems and apply appropriate remedial measures, rather than waiting until a crash occurs to remedy the problem. This means, a hazard can be early identified and possibly corrected before implementation of highway projects. In addition, the use of simulation tools to evaluate the safety of a traffic system can be advantageous because such tools provide extensive results for any study area within a relatively short time along with other traffic operational measures like level of service, delays, travel times, and capacities. Therefore, the objective of this dissertation was to analyze numerically the likelihood of the traffic crashes that might occur on the highway using cellular based micro-simulations. The modeling considered occurrence of rear-end crashes on high-speed highways with two lanes of traffic in each direction. Narrowing the safety evaluation to rear-end crashes, this study sought to analyze these crashes by providing simulation evidence of association between time-based traffic safety indicators and driver attributes with the likelihood of conflict or collision. To meet the study objectives, a stochastic cellular automata traffic model have been extended to use field-derived vehicle and driver characteristics. The vehicles' acceleration submodel in the simulation is categorized into different regimes depending on the prevailing traffic conditions. The vehicles' evolutions in the proposed micro-simulation model are based on kinematic equations to enhance the realism of their advancements. Behavioral variance in the model is introduced by taking in consideration both driver aggression and responsiveness to the traffic conditions. The model is calibrated using field data. Comparison of simulated spacings and speeds obtained from the simulation output with vehicle trajectories data obtained from the field return a Mean Absolute Percentage Error (MAPE) of less than 10% and a Theil's coefficient of inequality (U) of about 0.002. These statistics inferred that the proposed model worked well in replicating traffic on the field. In addition, correlation results showed that simulation results not only agree to the theoretical results but also to the detector data collected from the field. The driver behavior was found to contribute more in the likelihood of crashes which was determined by amount of great deceleration that driver apply to maintain safety during movement. The likelihood of vehicles to crash in the model was formulated from the Gamma distribution functions. Closer examination of the probability of a vehicle to crash in the model indicated that the likelihood of crashing is high when the traffic is flowing close to the maximum flow.
Author: Andrew Tarko Publisher: Elsevier ISBN: 0128105054 Category : Transportation Languages : en Pages : 254
Book Description
Measuring Road Safety Using Surrogate Events provides researchers and practitioners with the tools they need to quickly and effectively measure traffic safety. As traditional crash-based safety analyses are being undermined by today’s growing use of intelligent vehicular and road safety technologies, crash surrogates--or near misses--can be more effectively used to measure the future risk of crashes. This book advances the idea of using these near-crash techniques to deliver quicker and more adequate measurements of safety. It explores the relationships between traffic conflicts and crashes using an extrapolation of observed events rather than post-crash data, which is significantly slower to obtain. Readers will find sound estimation methods based on rigorous scientific principles, offering compelling new tools to better equip researchers to understand road safety and its factors. Consolidates the latest updates/ideas from disparate places into a single resource Establishes a consistent use of key terms, definitions and concepts to help codify this emerging field Contains numerous application-oriented case studies throughout Includes learning aids, such as chapter objectives, a glossary, and links to data used in examples
Author: Fouzi Harrou Publisher: Elsevier ISBN: 0128234334 Category : Transportation Languages : en Pages : 270
Book Description
Road Traffic Modeling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. The book examines commonly used traffic analysis methodologies as well the emerging methods that use deep learning methods. Other sections discuss how to understand statistical models and machine learning algorithms and how to apply them to traffic modeling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, this book is ideal for researchers and practitioners who want to improve the performance of intelligent transportation systems. Provides integrated, up-to-date and complete coverage of the key components for intelligent transportation systems: traffic modeling, forecasting, estimation and monitoring Uses methods based on video and time series data for traffic modeling and forecasting Includes case studies, key processes guidance and comparisons of different methodologies
Author: Ennio Cascetta Publisher: Springer Science & Business Media ISBN: 0387758577 Category : Business & Economics Languages : en Pages : 753
Book Description
"This book provides a rigorous and comprehensive coverage of transportation models and planning methods and is a must-have to anyone in the transportation community, including students, teachers, and practitioners." Moshe Ben-Akiva, Massachusetts Institute of Technology.
Author: Zou, Xi Publisher: ISBN: Category : Languages : en Pages : 36
Book Description
Abstract: Driving behaviors at intersection are complex because drivers have to perceive more traffic events than normal road driving and thus are exposed to more errors with safety consequences. Drivers make real-time responsesin a stochastic manner. This paper presents our study using Hidden Markov Models (HMM) to model driving behaviors at intersections. Observed vehicle movement data are used to build up the model. A single HMM is used to cluster the vehicle movements when they are close to intersection. The re-estimated clustered HMMs provide better prediction of the vehicle movements compared to traditional car-following models. Only through vehicles on major roads are considered in this paper. Journal of the Transportation Research Board: Transportation.
Author: Jerzy Kisilowski
Author: Jerzy Kisilowski
Author: Martin Treiber
Author: C. T. Spracklen
Author: Antonella Ferrara
Author: Victor Muchuruza
Author: Andrew Tarko
Author: 
Author: Fouzi Harrou
Author: Ennio Cascetta
Author: Zou, Xi