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

Zelin Wang, Yunyang Shi, Weiping Tong, Ziyuan Gu, Qixiu Cheng*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

26 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number04023075
JournalJournal of Transportation Engineering Part A: Systems
Volume149
Issue number8
DOIs
Publication statusPublished - 1 Aug 2023

Bibliographical note

Publisher Copyright:
© 2023 American Society of Civil Engineers.

Keywords

  • Autonomous vehicles (AVs)
  • Calibration
  • Car-following model
  • Complex environment
  • Human-driven vehicles (HDVs)
  • Stability analysis

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