A comparative study of state-of-the-art driving strategies for autonomous vehicles

被引:64
|
作者
Zhao, Can [1 ]
Li, Li [1 ]
Pei, Xin [1 ]
Li, Zhiheng [1 ,2 ]
Wang, Fei-Yue [3 ]
Wu, Xiangbin [4 ]
机构
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Tsinghua Shenzhen Int Grad Sch, Shenzhen 518055, Peoples R China
[3] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China
[4] Intel China Inst, Beijing 100080, Peoples R China
来源
ACCIDENT ANALYSIS AND PREVENTION | 2021年 / 150卷 / 150期
基金
中国国家自然科学基金;
关键词
Autonomous vehicles; Driving strategy; Risk appetite; Interaction manner; TRAFFIC FLOW THEORIES; AUTOMATED VEHICLES; COLLISION-AVOIDANCE; DECISION-MAKING; BEHAVIOR; RISK; ENVIRONMENT; TRANSITION; CONTROLLER; MITIGATION;
D O I
10.1016/j.aap.2020.105937
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
The autonomous vehicle is regarded as a promising technology with the potential to reshape mobility and solve many traffic issues, such as accessibility, efficiency, convenience, and especially safety. Many previous studies on driving strategies mainly focused on the low-level detailed driving behaviors or specific traffic scenarios but lacked the high-level driving strategy studies. Though researchers showed increasing interest in driving strategies, there still has no comprehensive answer on how to proactively implement safe driving. After analyzing several representative driving strategies, we propose three characteristic dimensions that are important to measure driving strategies: preferred objective, risk appetite, and collaborative manner. According to these three characteristic dimensions, we categorize existing driving strategies of autonomous vehicles into four kinds: defensive driving strategies, competitive driving strategies, negotiated driving strategies, and cooperative driving strategies. This paper provides a timely comparative review of these four strategies and highlights the possible directions for improving the high-level driving strategy design.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlooks
    Wei, Lianzhen
    Li, Zirui
    Gong, Jianwei
    Gong, Cheng
    Li, Jiachen
    2021 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2021, : 44 - 51
  • [2] Modelling and simulation of (connected) autonomous vehicles longitudinal driving behavior: A state-of-the-art
    Sadid, Hashmatullah
    Antoniou, Constantinos
    IET INTELLIGENT TRANSPORT SYSTEMS, 2023, 17 (06) : 1051 - 1071
  • [3] Study on State-of-the-art Cloud Services Integration Capabilities with Autonomous Ground Vehicles
    Damacharla, Praveen
    Mehta, Dhwani
    Javaid, Ahmad Y.
    Devabhaktuni, Vijay K.
    2018 IEEE 88TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2018,
  • [4] Review article: State-of-the-art trajectory tracking of autonomous vehicles
    Li, Lei
    Li, Jun
    Zhang, Shiyi
    MECHANICAL SCIENCES, 2021, 12 (01) : 419 - 432
  • [5] Cybersecurity and Forensics in Connected Autonomous Vehicles: A Review of the State-of-the-Art
    Sharma, Prinkle
    Gillanders, James
    IEEE ACCESS, 2022, 10 : 108979 - 108996
  • [6] Generalizing state-of-the-art object detectors for autonomous vehicles in unseen environments
    Khosravian, Amir
    Amirkhani, Abdollah
    Kashiani, Hossein
    Masih-Tehrani, Masoud
    EXPERT SYSTEMS WITH APPLICATIONS, 2021, 183
  • [7] Autonomous Guided Vehicles for Smart Industries - The State-of-the-Art and Research Challenges
    Cupek, Rafal
    Drewniak, Marek
    Fojcik, Marcin
    Kyrkjebo, Erik
    Lin, Jerry Chun-Wei
    Mrozek, Dariusz
    Ovsthus, Knut
    Ziebinski, Adam
    COMPUTATIONAL SCIENCE - ICCS 2020, PT V, 2020, 12141 : 330 - 343
  • [8] State-of-the-Art Review on Recent Advancements on Lateral Control of Autonomous Vehicles
    Biswas, Archishman
    Reon, M. A. Obayed
    Das, Prangon
    Tasneem, Zinat
    Muyeen, S. M.
    Das, Sajal K.
    Badal, Faisal R.
    Sarker, Subrata Kumar
    Hassan, Md Mehedi
    Abhi, Sarafat Hussain
    Islam, Md Robiul
    Ali, Md Firoj
    Ahamed, Md Hafiz
    Islam, Md Manirul
    IEEE ACCESS, 2022, 10 : 114759 - 114786
  • [9] State-of-the-Art Review on Traffic Control Strategies for Emergency Vehicles
    Yu, Weiqi
    Bai, Weichen
    Qi, Liang
    Luan, Wenjing
    IEEE ACCESS, 2022, 10 : 109729 - 109742
  • [10] Unmanned aerial vehicles using machine learning for autonomous flight; state-of-the-art
    Choi, Su Yeon
    Cha, Dowan
    ADVANCED ROBOTICS, 2019, 33 (06) : 265 - 277