游戏理论运动规划与感知不确定性和前进权限制
Pouya Panahandeh1, Ahmad Reza Alghooneh1, Mohammad Pirani2
1Mechanical and Mechatronics Engineering Department, University of Waterloo, 200 University Ave W, Waterloo, ON N2L 3G1, Canada.
这项研究通过使用游戏理论来增强自动驾驶汽车 (AV) 运动规划,以确保道路右侧的坚持和管理传感器的不确定性. 该方法提高了复杂的交通场景中的AV可靠性和适应性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 游戏理论 游戏理论
背景情况:
- 自动驾驶汽车 (AV) 运动规划在遵守道路权等交通规则方面面临挑战.
- 处理传感器数据和其他道路使用者的行为所固有的不确定性对于安全的AV操作至关重要.
研究的目的:
- 为AVs开发一个强大的运动规划框架,以解决对路的权利的坚持和不确定性.
- 在动态的交通环境中利用游戏理论方法进行战略决策.
主要方法:
- 利用斯塔克尔伯格和纳什贝叶斯 (贝叶斯) 游戏理论框架来模拟道路使用者之间的互动.
- 建模道路使用者互动作为战略轨迹优化等级关系.
- 在贝叶斯平衡中纳入概率学信念和传感器测量更新,以处理不确定性.
主要成果:
- 拟议的方法使AV能够在考虑其他道路使用者的行动和优先事项的同时,从战略上优化轨迹.
- 贝叶斯平衡方面允许在感官不确定性下进行知情决策.
- 实验评估证实了该方法在提高AV运动规划可靠性和适应性方面的有效性.
结论:
- 游戏理论框架有效地解决了AV动作规划中的关键挑战,特别是权利的坚持和不确定性.
- 开发的方法提高了自动驾驶系统的稳定性和适应性.
- 这项研究有助于更安全,更有效的自动驾驶车辆导航.
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