Car-Following Models for Human-Driven Vehicles and Autonomous Vehicles: A Systematic Review
AbstractThe focus of car-following models is to analyze the microscopic characteristics of traffic flows, with particular attention given to the interaction between adjacent vehicles. This paper presents a systematic review of existing studies on car-following models, with an emphasis on the behavior of both human-driven vehicles (HDVs) and autonomous vehicles (AVs). We classify car-following models based on their applicable background and structure. By considering driving behavior and specific model parameters, we identify the advantages and limitations of each microscopic simulation model in terms of accuracy and continuity. We also discuss model calibration methods, stability analysis, and the impact of complex traffic environments on the car-following process. Finally, we present detailed discussions of each model’s features and provide recommendations based on reviewed works and development trends for future research, including mixed traffic flow composed of AVs and HDVs.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/24732907
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Supplemental Notes:
- © 2023 American Society of Civil Engineers 2023
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Authors:
- Wang, Zelin
- Shi, Yunyang
- Tong, Weiping
- Gu, Ziyuan
- Cheng, Qixiu
- Publication Date: 2023-8
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: 04023075
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Serial:
- Journal of Transportation Engineering, Part A: Systems
- Volume: 149
- Issue Number: 8
- Publisher: American Society of Civil Engineers
- ISSN: 2473-2907
- EISSN: 2473-2893
- Serial URL: http://ascelibrary.org/journal/jtepbs
Subject/Index Terms
- TRT Terms: Automobile drivers; Autonomous vehicles; Car following; Microscopic traffic flow; Traffic models; Vehicle mix
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01885576
- Record Type: Publication
- Files: TRIS, ASCE
- Created Date: Jun 22 2023 9:49AM