Car-Following Models for Human-Driven Vehicles and Autonomous Vehicles: A Systematic Review

被引:25
作者
Wang, Zelin [1 ]
Shi, Yunyang [1 ]
Tong, Weiping [1 ]
Gu, Ziyuan [1 ]
Cheng, Qixiu [2 ,3 ]
机构
[1] Southeast Univ, Sch Transportat, Nanjing 210096, Peoples R China
[2] Hong Kong Polytech Univ, Dept Logist & Maritime Studies, Kowloon, Hong Kong, Peoples R China
[3] Hong Kong Polytech Univ, Shenzhen Res Inst, Shenzhen, Peoples R China
基金
中国国家自然科学基金;
关键词
Car-following model; Human-driven vehicles (HDVs); Autonomous vehicles (AVs); Calibration; Stability analysis; Complex environment; ADAPTIVE CRUISE CONTROL; MIXED TRAFFIC FLOW; CONNECTED AUTOMATED VEHICLES; CELLULAR-AUTOMATA; EXPERIMENTAL VALIDATION; COLLISION-AVOIDANCE; STABILITY ANALYSIS; DRIVING BEHAVIOR; CONTROL STRATEGY; TRAJECTORY DATA;
D O I
10.1061/JTEPBS.TEENG-7836
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The 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.
引用
收藏
页数:21
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