汽车工程 ›› 2025, Vol. 47 ›› Issue (8): 1501-1512.doi: 10.19562/j.chinasae.qcgc.2025.08.007

• • 上一篇    

基于人机博弈的驾驶权接管控制策略

石英魁1,胡川1,邹建中2(),张希1   

  1. 1.上海交通大学机械与动力工程学院,上海 200240
    2.新疆生产建设兵团兴新职业技术学院科研处,铁门关 841007
  • 收稿日期:2024-12-03 修回日期:2025-02-02 出版日期:2025-08-25 发布日期:2025-08-18
  • 通讯作者: 邹建中 E-mail:jianzhong@btc.edu.cn
  • 基金资助:
    国家海外优秀青年科学基金项目(24Z990200855)

Takeover Control Strategy Based on Human-Machine Game

Yingkui Shi1,Chuan Hu1,Jianzhong Zou2(),Xi Zhang1   

  1. 1.School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240
    2.Bingtuan Xingxin Vocational and Technical College,Tiemenguan 841007
  • Received:2024-12-03 Revised:2025-02-02 Online:2025-08-25 Published:2025-08-18
  • Contact: Jianzhong Zou E-mail:jianzhong@btc.edu.cn

摘要:

当前L3级别有条件自动驾驶能够在部分特定情况下独立执行驾驶任务,从而允许人类驾驶员参与驾驶无关任务,但当系统发出接管请求,如何在驾驶员状态恢复过程中实现从自动到手动驾驶的平稳过渡是当前自动驾驶应用的关键问题。本文面向L3自动驾驶中人类驾驶员接管控制权场景,根据系统发出接管请求后驾驶员的接管行为阶段,构建了驾驶权过渡过程中的人机非零和微分博弈框架,开发了基于单评价网络的事件触发自适应动态规划控制算法,通过求解人机双方耦合控制目标下的驾驶策略以及设计基于指数-三角优化算法的柔性控制权限转移,实现了安全、稳定的自动-手动驾驶模式切换。结果表明采用该驾驶员接管策略相比于刚性控制权切换方案时,系统能实现更理想的避障表现以及更稳定的车辆运动。

关键词: 自动驾驶, 接管控制, 非零和微分博弈, 指数-三角优化算法

Abstract:

Level 3 conditional autonomous driving systems can independently execute driving tasks in certain specific situation, allowing human drivers to get involved in tasks unrelated to driving. However, when the system sends out a takeover request, achieving a smooth transition from automatic to manual vehicle control during the driver's state recovery process is a key concern in current autonomous driving application. In this paper, for the takeover process of human driver in L3 autonomous driving, a human-machine non-zero-sum differential game framework is constructed for the authority transition based on the takeover behavior of human driver upon the system's takeover request and an event-triggered adaptive dynamic programming control algorithm is developed based on critic-only structure. By solving the driving strategies under the coupled control objectives of both players and designing exponential-trigonometric optimization algorithm-based flexible authority transfer strategy, a safe and stable switch between automatic and manual driving is achieved. The results show that the proposed takeover strategy has better obstacle avoidance performance and more stable vehicle motion than rigid takeover method.

Key words: autonomous driving, takeover control, non-zero differential game, exponential-trigonometric optimization algorithm