• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2022, Vol. 58 ›› Issue (10): 200-208.doi: 10.3901/JME.2022.10.200

• 运载工程 • 上一篇    下一篇

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自动驾驶赛车路径与车速协同规划方法

李荣粲, 庄伟超, 殷国栋, 刘昊吉, 郑芝芸   

  1. 东南大学机械工程学院 南京 211189
  • 收稿日期:2021-07-09 修回日期:2021-11-25 出版日期:2022-05-20 发布日期:2022-07-07
  • 通讯作者: 殷国栋(通信作者),男,1976年出生,教授,博士研究生导师。主要研究方向为智能网联汽车、无人驾驶与智能辅助驾驶系统、车辆动力学及其控制等。E-mail:ygd@seu.edu.cn
  • 作者简介:李荣粲,男,1996年出生。主要研究方向为自动驾驶赛车轨迹规划与控制。E-mail:1195140756@qq.com
  • 基金资助:
    国家自然科学基金(51975118,52025121)和江苏省成果转化(BA2020068,BA2018023)资助项目。

Simultaneous Path and Speed Planning of Driverless Racing Car

LI Rongcan, ZHUANG Weichao, YIN Guodong, LIU Haoji, ZHENG Zhiyun   

  1. School of Mechanical Engineering, Southeast University, Nanjing 211189
  • Received:2021-07-09 Revised:2021-11-25 Online:2022-05-20 Published:2022-07-07

摘要: 自动驾驶赛车需实现路径与车速的同步规划以满足最快驾驶策略需求,但车辆行驶路径与车速的时空耦合关系使得优化问题难以构建与求解。为此,提出一种面向自动驾驶赛车的轨迹规划方法(Simultaneous path and speed planning, SP2),实现路径与车速的快速协同规划。首先,构建包括赛道边界与车辆动力学约束的自动驾驶赛车轨迹规划问题;然后,建立赛车的稳态动作空间与包含时空位置信息的状态-动作空间,通过离线遍历法确定赛车的可行运动状态转移关系;接着,基于稳态动作空间与运动状态转移网,将原时间最优轨迹优化问题转换为单位时间步长内运动距离最远的优化问题,并通过滚动多步优化实现赛车圈速最小(时间最优)轨迹的优化。最后,开展自动驾驶赛车轨迹规划的仿真与微缩试验平台试验。结果表明,所提出的SP2算法可以高效地实现自动驾驶赛车的全局路径与车速规划,并且较常规中心线轨迹具有更快的圈速。

关键词: 自动驾驶赛车, 轨迹规划, 离散工况点, 时空耦合, 时间最优

Abstract: The autonomous racing car(ARC) is supposed to plan path and speed simultaneously to meet the requirement of the fastest driving strategy. However, the spatiotemporal coupling relationship between path and speed makes the optimization problem difficult to formulate and solve. To deal with this problem, a simultaneous path and speed planning(SP2) approach for autonomous racing car is proposed in this paper to achieve rapid cooperative trajectory planning. First, a trajectory planning problem considering track boundaries and vehicle dynamics constraints is formulated. Second, the steady action space and action-state space including spatiotemporal information of the ARC is built, and the available action-state transition relationship is determined via offline traversal. After that, we transform the time optimal trajectory optimization problem into an optimization problem with the objective of achieving the longest distance per time step and apply multi-step recursive optimization scheme to render a trajectory with the fastest lap time. Last but not least, simulations and experiments in a small scaled platform is conducted. Results show that the proposed SP2 approach can efficiently provide global path and speed for the ARC, with a faster lap times compared with the traditional approach of following the center line of track.

Key words: autonomous racing car(ARC), trajectory planning, discrete operating point, spatiotemporal coupling, time optimization

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