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OverviewWritten by an international team of researchers, this book focuses on traffic information processing and signal control using emerging types of traffic data. It conveys advanced methods to estimate and predict traffic flows at different levels, including macroscopic, mesoscopic and microscopic. The aim of these predictions is to optimize traffic signal control for intersections and to mitigate ever-growing traffic congestion. The book begins with an introduction to the topic, its fundamental principles and recent developments. The first part of the book then covers the estimation and prediction of the traffic flow state based on emerging detailed data sources. Coverage in this section includes traffic analytics with online web data; macroscopic traffic performance indicators based on floating car data; short-term travel time prediction by deep learning a comparison of different LSTM-DNN models; short-term traffic prediction under disruptions using deep leaning; real time demand based traffic diversion; game theoretic lane change strategy for cooperative vehicles under perfect information; and cooperative driving and a lane change-free road transportation system. The second part focuses on traffic signal control optimization, explaining how to use improved data and advanced tools for better signal control. Chapters include urban traffic control systems; algorithms and models for signal coordination; emerging technologies to enhance traffic signal coordination practices; control for short-distance intersections; and multi-day evaluation of adaptive traffic signal system based on license plate recognition detector data. A valuable resource for researchers and engineers working in the field of traffic information and control, and intelligent transport systems, Traffic Information and Control offers an overview of recent research and practical approaches to optimising traffic signal control. Full Product DetailsAuthor: Ruimin Li (Tenured Associate Professor, Tsinghua University, Department of Civil Engineering, China) , Zhengbing He (Professor, Beijing University of Technology, Beijing Key Laboratory of Traffic Engineering, China)Publisher: Institution of Engineering and Technology Imprint: Institution of Engineering and Technology Dimensions: Width: 15.60cm , Height: 2.00cm , Length: 23.40cm Weight: 0.680kg ISBN: 9781839530258ISBN 10: 1839530251 Pages: 328 Publication Date: 11 January 2021 Audience: College/higher education , Professional and scholarly , Tertiary & Higher Education , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsChapter 1: Introduction Part I: Modern traffic information technology Chapter 2: Traffic analytics with online web data Chapter 3: Macroscopic traffic performance indicators based on floating car data: formation, pattern analysis, and deduction Chapter 4: Short-term travel-time prediction by deep learning: a comparison of different LSTM-DNN models Chapter 5: Short-term traffic prediction under disruptions using deep learning Chapter 6: Real-time demand-based traffic diversion Chapter 7: Game theoretic lane change strategy for cooperative vehicles under perfect information Chapter 8: Cooperative driving and a lane change-free road transportation system Part II: Modern traffic signal control Chapter 9: Urban traffic control systems: architecture, methods and development Chapter 10: Algorithms and models for signal coordination Chapter 11: Emerging technologies to enhance traffic signal coordination practices Chapter 12: Traffic signal control for short-distance intersections with dynamic reversible lanes Chapter 13: Multiday evaluation of adaptive traffic signal system based on license plate recognition detector data Chapter 14: ConclusionReviewsAuthor InformationRuimin Li is a tenured associate professor in the Department of Civil Engineering at Tsinghua University, China. He is a vice chairman and secretary general of the transportation modelling and simulation commission of the China Simulation Federation, and an editorial advisory board member of several international journals. His research interests include intelligent transportation systems, urban transportation planning, and traffic control, safety, and simulation. Zhengbing He is a professor at the Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, China. He is an IEEE senior member, an editorial advisory board member of Transportation Research Part C, and an associate editor of IET Intelligent Transport Systems. He has published more than 80 academic papers in the fields of traffic flow theory and intelligent transportation systems. Tab Content 6Author Website:Countries AvailableAll regions |
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