{"title":"考虑动态交通场景下车辆稳定性的自动驾驶巴士动态变道轨迹规划与跟踪","authors":"Zhigen Nie, Yi Zhou, Yufeng Lian","doi":"10.1177/09544070241264366","DOIUrl":null,"url":null,"abstract":"Trajectory planning and tracking of lane change are critical technologies for autonomous buses. Characteristics of the buses susceptible to stability problems resulting from the high height, large passenger capacity and long lengths, coupling the dynamic traffic with the dynamic changes in the states of adjacent vehicles and road adhesion coefficient, put forward great challenges in lane change for autonomous buses (ABs). To cope with the foregoing challenges, a framework is proposed to achieve the trajectory planning and tracking of dynamic lane change for ABs. For trajectory planning approach, the trajectory planning and replanning is optimized in the safe range of longitudinal length of the lane-changing trajectory to obtain the real-time reference trajectory, combining consideration of vehicle yaw, roll stability and lane-changing efficiency. The minimum longitudinal length of lane-changing trajectory determined by the yaw stability and roll stability of ABs, combined with the maximum length formed by the adjacent vehicles with dynamic states, form the real-time safe range for lane-changing trajectory planning. For trajectory tracking approach, a tracking approach using model predictive control based on multipoint preview is proposed to achieve the real-time planned trajectory tracking considering buses stability. The effectiveness of the proposed strategy is evaluated by simulating an experimentally validated Trucksim model in different dynamic traffic scenarios to demonstrate the capability of the strategy in trajectory planning and tracking, and guaranteeing vehicle stability for dynamic lane change of ABs.","PeriodicalId":54568,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering","volume":"94 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trajectory planning and tracking of dynamic lane change for autonomous buses considering vehicle stability in dynamic traffic scenarios\",\"authors\":\"Zhigen Nie, Yi Zhou, Yufeng Lian\",\"doi\":\"10.1177/09544070241264366\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Trajectory planning and tracking of lane change are critical technologies for autonomous buses. Characteristics of the buses susceptible to stability problems resulting from the high height, large passenger capacity and long lengths, coupling the dynamic traffic with the dynamic changes in the states of adjacent vehicles and road adhesion coefficient, put forward great challenges in lane change for autonomous buses (ABs). To cope with the foregoing challenges, a framework is proposed to achieve the trajectory planning and tracking of dynamic lane change for ABs. For trajectory planning approach, the trajectory planning and replanning is optimized in the safe range of longitudinal length of the lane-changing trajectory to obtain the real-time reference trajectory, combining consideration of vehicle yaw, roll stability and lane-changing efficiency. The minimum longitudinal length of lane-changing trajectory determined by the yaw stability and roll stability of ABs, combined with the maximum length formed by the adjacent vehicles with dynamic states, form the real-time safe range for lane-changing trajectory planning. For trajectory tracking approach, a tracking approach using model predictive control based on multipoint preview is proposed to achieve the real-time planned trajectory tracking considering buses stability. 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引用次数: 0
摘要
轨迹规划和变道跟踪是自动驾驶巴士的关键技术。客车高度高、载客量大、长度长等特点容易导致稳定性问题,再加上动态交通与相邻车辆状态和道路附着系数的动态变化,给自动驾驶客车(ABs)的变道带来了巨大挑战。为应对上述挑战,本文提出了实现自动驾驶巴士动态变道轨迹规划和跟踪的框架。在轨迹规划方法中,轨迹规划和重新规划在变道轨迹纵向长度的安全范围内进行优化,以获得实时参考轨迹,同时兼顾车辆偏航、侧滚稳定性和变道效率。由 AB 车辆的偏航稳定性和侧滚稳定性确定的变道轨迹纵向长度最小值,结合相邻车辆动态状态形成的最大长度,构成变道轨迹规划的实时安全范围。在轨迹跟踪方法方面,提出了一种基于多点预览的模型预测控制跟踪方法,以实现考虑总线稳定性的实时规划轨迹跟踪。通过在不同的动态交通场景中模拟经过实验验证的 Trucksim 模型,评估了所提策略的有效性,从而证明了该策略在轨迹规划和跟踪方面的能力,并保证了 AB 动态变道时的车辆稳定性。
Trajectory planning and tracking of dynamic lane change for autonomous buses considering vehicle stability in dynamic traffic scenarios
Trajectory planning and tracking of lane change are critical technologies for autonomous buses. Characteristics of the buses susceptible to stability problems resulting from the high height, large passenger capacity and long lengths, coupling the dynamic traffic with the dynamic changes in the states of adjacent vehicles and road adhesion coefficient, put forward great challenges in lane change for autonomous buses (ABs). To cope with the foregoing challenges, a framework is proposed to achieve the trajectory planning and tracking of dynamic lane change for ABs. For trajectory planning approach, the trajectory planning and replanning is optimized in the safe range of longitudinal length of the lane-changing trajectory to obtain the real-time reference trajectory, combining consideration of vehicle yaw, roll stability and lane-changing efficiency. The minimum longitudinal length of lane-changing trajectory determined by the yaw stability and roll stability of ABs, combined with the maximum length formed by the adjacent vehicles with dynamic states, form the real-time safe range for lane-changing trajectory planning. For trajectory tracking approach, a tracking approach using model predictive control based on multipoint preview is proposed to achieve the real-time planned trajectory tracking considering buses stability. The effectiveness of the proposed strategy is evaluated by simulating an experimentally validated Trucksim model in different dynamic traffic scenarios to demonstrate the capability of the strategy in trajectory planning and tracking, and guaranteeing vehicle stability for dynamic lane change of ABs.
期刊介绍:
The Journal of Automobile Engineering is an established, high quality multi-disciplinary journal which publishes the very best peer-reviewed science and engineering in the field.