Sharing the Road
Understanding and Facilitating Mixed Traffic with Human-Driven and Autonomous Vehicles
1st Edition
Will be published approx. on 20. July 2026
Book
Paperback/Softback
152 pages
978-1-032-67468-1 (ISBN)
Description
With the advancements in sensor and computation technologies, connected autonomous vehicle (CAV) services are being tested and deployed on public roads, sharing the road with human- driven vehicles (HVs). This brings challenges to traffic safety, due to uncertainty in HVs behaviors. To address these challenges, Sharing the Road offers solutions to create a safer world where HVs and AVs mix freely on our roads.
Presented from a team of researchers from different domains offering varying perspectives, this book systematically summarizes the issues and trends of mixed traffic, from the micro (such as vehicle algorithm design) to the macro (including traffic flow optimization and policy) perspectives. Customized car- following models describing the behaviors of HVs when interacting with CAVs and control algorithms optimizing the traffic flow in terms of traffic safety and efficiency are discussed. The title also summarizes approaches to model HVs' behaviors and case studies of real-life examples are provided, leaving the reader with a detailed vision of the future of a mixed- traffic world.
This title will appeal to professionals at any career stage in the fields of human factor engineering, traffic engineering, urban design, and vehicle engineering.
Presented from a team of researchers from different domains offering varying perspectives, this book systematically summarizes the issues and trends of mixed traffic, from the micro (such as vehicle algorithm design) to the macro (including traffic flow optimization and policy) perspectives. Customized car- following models describing the behaviors of HVs when interacting with CAVs and control algorithms optimizing the traffic flow in terms of traffic safety and efficiency are discussed. The title also summarizes approaches to model HVs' behaviors and case studies of real-life examples are provided, leaving the reader with a detailed vision of the future of a mixed- traffic world.
This title will appeal to professionals at any career stage in the fields of human factor engineering, traffic engineering, urban design, and vehicle engineering.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
College/higher education
Professional Reference
Illustrations
29 s/w Tabellen, 15 s/w Zeichnungen, 46 s/w Photographien bzw. Rasterbilder, 61 s/w Abbildungen
29 Tables, black and white; 15 Line drawings, black and white; 46 Halftones, black and white; 61 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Weight
453 gr
ISBN-13
978-1-032-67468-1 (9781032674681)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Dengbo He | Xiaotong Sun | Huan Yu
Sharing the Road
Understanding and Facilitating Mixed Traffic with Human-Driven and Autonomous Vehicles
E-Book
03/2025
1st Edition
CRC Press
€115.99
Available for download
Dengbo He | Xiaotong Sun | Huan Yu
Sharing the Road
Understanding and Facilitating Mixed Traffic with Human-Driven and Autonomous Vehicles
E-Book
03/2025
1st Edition
CRC Press
€115.99
Available for download
Dengbo He | Xiaotong Sun | Huan Yu
Sharing the Road
Understanding and Facilitating Mixed Traffic with Human-Driven and Autonomous Vehicles
Book
03/2025
1st Edition
CRC Press
€121.50
Shipment within 10-20 days
Persons
Dengbo He received his Bachelor's degree from Hunan University in 2012, M.S. degree from Shanghai Jiao Tong University in 2016 and Ph.D. degree from the University of Toronto in 2020. He worked as a Postdoctoral Research Fellow at the University of Toronto from 2020 to 2021 and is currently an Assistant Professor in Intelligent Transportation Thrust and Robotics and Autonomous Systems Thrust, at the Hong Kong University of Science and Technology (HKUST) (Guangzhou). He is also affiliated with the Department of Civil and Environmental Engineering, HKUST, Hong Kong SAR. His research focuses on human factors, driver behavior and the interactions between driving automation and human drivers.
Xiaotong Sun is an Assistant Professor in the Intelligent Transportation Thrust and an affiliated Assistant Professor in the Civil and Environmental Engineering Department at the Hong Kong University of Science and Technology. Before joining HKUST, she was a Postdoctoral Research Fellow at the University of Michigan, Ann Arbor. She received her Ph.D. in Civil Engineering from the University of Michigan in July 2020.
Huan Yu is an Assistant Professor in the Intelligent Transportation Thrust of the Systems Hub, and an affiliated Assistant Professor in the Department of Civil and Environmental Engineering at the Hong Kong University of Science and Technology (HKUST). Yu received her B.Eng. degree in Aerospace Engineering from Honor School (Elite program) of Northwestern Polytechnical University, and her M.Sc. and Ph.D. degrees in Aerospace Engineering from the Department of Mechanical and Aerospace Engineering, University of California, San Diego. She was a visiting scholar at University of California, Berkeley in 2018 and Massachusetts Institute of Technology in 2019. She was a Postdoctoral Researcher at University of California, San Diego before joining the HKUST (Guangzhou) in 2021.
Xiaotong Sun is an Assistant Professor in the Intelligent Transportation Thrust and an affiliated Assistant Professor in the Civil and Environmental Engineering Department at the Hong Kong University of Science and Technology. Before joining HKUST, she was a Postdoctoral Research Fellow at the University of Michigan, Ann Arbor. She received her Ph.D. in Civil Engineering from the University of Michigan in July 2020.
Huan Yu is an Assistant Professor in the Intelligent Transportation Thrust of the Systems Hub, and an affiliated Assistant Professor in the Department of Civil and Environmental Engineering at the Hong Kong University of Science and Technology (HKUST). Yu received her B.Eng. degree in Aerospace Engineering from Honor School (Elite program) of Northwestern Polytechnical University, and her M.Sc. and Ph.D. degrees in Aerospace Engineering from the Department of Mechanical and Aerospace Engineering, University of California, San Diego. She was a visiting scholar at University of California, Berkeley in 2018 and Massachusetts Institute of Technology in 2019. She was a Postdoctoral Researcher at University of California, San Diego before joining the HKUST (Guangzhou) in 2021.
Content
Contents
Acknowledgements
About the Authors
List of Contributors
Chapter 1-Introduction
Chapter 2-Empirical Research for Mixed Traffic Research
Chapter 3-Tools for Micro Mixed Traffic Research
Chapter 4 - Micro-Macro Mixed Traffic Flow Modeling
Chapter 5 - Safety of Mixed Traffic: Evidence from Empirical Studies
Chapter 6- Environmental Impact of the Mixed Traffic and Countermeasures
Chapter 7 - Case Study: Driver Performance Difference and Model Difference Evaluation on Different Car-following Scenarios under Mixed Traffic Flow
Chapter 8 - Case Study: Analysis of Mixed Traffic Flow
Chapter 9 - Case study: Mixed Traffic with Connected and Automated Vehicle Scenario in Southern California
Index
Acknowledgements
About the Authors
List of Contributors
Chapter 1-Introduction
Chapter 2-Empirical Research for Mixed Traffic Research
Chapter 3-Tools for Micro Mixed Traffic Research
Chapter 4 - Micro-Macro Mixed Traffic Flow Modeling
Chapter 5 - Safety of Mixed Traffic: Evidence from Empirical Studies
Chapter 6- Environmental Impact of the Mixed Traffic and Countermeasures
Chapter 7 - Case Study: Driver Performance Difference and Model Difference Evaluation on Different Car-following Scenarios under Mixed Traffic Flow
Chapter 8 - Case Study: Analysis of Mixed Traffic Flow
Chapter 9 - Case study: Mixed Traffic with Connected and Automated Vehicle Scenario in Southern California
Index