Game-Theoretic Decision-Making Method and Motion Planning for Autonomous Vehicles in Overtaking

被引:1
|
作者
Cai, Lei [1 ]
Guan, Hsin [1 ]
Xu, Qi Hong [1 ]
Jia, Xin [1 ]
Zhan, Jun [1 ]
机构
[1] Jilin Univ, State Key Lab Automot Simulat & Control, Changchun 130022, Peoples R China
基金
中国国家自然科学基金;
关键词
Planning; Predictive models; Games; Decision making; Vehicle dynamics; Adaptation models; Trajectory; Autonomous vehicle; overtaking; decision making; game theory;
D O I
10.1109/TITS.2024.3378162
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Overtaking is a common driving behaviour used by human drivers while driving. Therefore, the decision on overtaking is very important in the automatic driving decision. To be able to improve the passing efficiency of intelligent vehicles, it is crucial to be able to interact with oncoming vehicles with different driving styles. An overtaking decision needs to be adapted to the situation where the vehicle being overtaken is potentially stationary or moving. Therefore, this paper proposes an overtaking decision method based on potential conflict area based on the requirements. Firstly, the planning method for each stage is given, and the generation method of the potential conflict area is proposed. Second, the interaction process between the host vehicle and the opposite oncoming vehicle is modelled by a dynamic game based on the potential conflict area. A driving style assessment method for oncoming vehicles based on potential conflict area is proposed. Thirdly, the priority of passing the potential conflict area of multiple oncoming vehicles is divided to correct the speed planning in the waiting and the speed payoff function in the game. Finally, the overtaking decision is simulated and validated by Virtual Test Drive.
引用
收藏
页码:9693 / 9709
页数:17
相关论文
共 50 条
  • [1] Hierarchical and game-theoretic decision-making for connected and automated vehicles in overtaking scenarios
    Ji, Kyoungtae
    Li, Nan
    Orsag, Matko
    Han, Kyoungseok
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2023, 150
  • [2] Deep Reinforcement Learning Based Game-Theoretic Decision-Making for Autonomous Vehicles
    Yuan, Mingfeng
    Shan, Jinjun
    Mi, Kevin
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (02) : 818 - 825
  • [3] A Three-Level Game-Theoretic Decision-Making Framework for Autonomous Vehicles
    Liu, Mushuang
    Wan, Yan
    Lewis, Frank L.
    Nageshrao, Subramanya
    Filev, Dimitar
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (11) : 20298 - 20308
  • [4] Interactive decision-making for autonomous vehicles: A layered game-theoretic framework with situational awareness
    Zhao, Junwu
    Qu, Ting
    Hu, Yunfeng
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2024,
  • [5] Hierarchical Game-Theoretic Planning for Autonomous Vehicles
    Fisac, Jaime F.
    Bronstein, Eli
    Stefansson, Elis
    Sadigh, Dorsa
    Sastry, S. Shankar
    Dragan, Anca D.
    2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2019, : 9590 - 9596
  • [6] A Multi-Vehicle Game-Theoretic Framework for Decision Making and Planning of Autonomous Vehicles in Mixed Traffic
    Yan, Yongjun
    Peng, Lin
    Shen, Tong
    Wang, Jinxiang
    Pi, Dawei
    Cao, Dongpu
    Yin, Guodong
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (11): : 4572 - 4587
  • [7] Adaptive Robust Game-Theoretic Decision Making Strategy for Autonomous Vehicles in Highway
    Sankar, Gokul S.
    Han, Kyoungseok
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (12) : 14484 - 14493
  • [8] A GAME-THEORETIC APPROACH FOR MULTICRITERIA DECISION-MAKING
    FORGO, F
    LECTURE NOTES IN ECONOMICS AND MATHEMATICAL SYSTEMS, 1984, 229 : 41 - 46
  • [9] Nash or Stackelberg? A Comparative Study for Game-Theoretic Autonomous Vehicle Decision-Making
    Bateman, Brady
    Xin, Ming
    Tseng, H. Eric
    Liu, Mushuang
    IFAC PAPERSONLINE, 2024, 58 (28): : 504 - 509
  • [10] Game-Theoretic Lane-Changing Decision Making and Payoff Learning for Autonomous Vehicles
    Lopez, Victor G.
    Lewis, Frank L.
    Liu, Mushuang
    Wan, Yan
    Nageshrao, Subramanya
    Filev, Dimitar
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (04) : 3609 - 3620