基于改进混合A*的智能汽车时空联合规划方法

doi:10.19562/j.chinasae.qcgc.2023.07.003

Abstract

Abstract:

Motion planning is the critical module of trajectory generation in autopilot system. The existing motion planning mostly adopts path-velocity decomposition method， which is easy to fall into trajectory suboptimal in complex dynamic scenarios. In this paper， a spatio-temporal joint motion planning method based on the combination of search and numerical optimization is proposed to solve the drivable trajectory directly. Firstly， the improved hybrid A* is used to search for the initial rough trajectory in the spatio-temporal range. Secondly， a drivable spatio-temporal corridor is constructed based on the initial trajectory， and considering vehicle dynamics and trajectory continuity constraints， the numerical optimization method is used to further smooth the initial trajectory. Finally， two typical complex dynamic scenarios of lane change overtaking and side-vehicle cut-in are selected for simulation test. The results show that the proposed planning method is more flexible and more reasonable than the traditional spatio-temporal decoupling planning method， and has better real-time computing performance.

Key words: spatio-temporal joint planning, improved hybrid A*, spatio-temporal corridor, numerical optimization

Jie Hu, Zhihao Zhang, Ruinan Chen, Ruipeng Chen, Haoyan Liu, Qi Zhu, Hui Chen. Spatio-temporal Joint Planning Method of Intelligent Vehicles Based on Improved Hybrid A[J].Automotive Engineering, 2023, 45(7): 1123-1133.

Figures/Tables 25

算法1 时空混合A*算法流程

输入：车辆配置参数，道路环境信息，障碍物信息

输出：初始粗轨迹

1. Initialize the open set and closed set with the $N s t a r t$ ；

2. while the open set is not empty

3. Estimate the nodes’ cost in the open set according to equation （4） and （5） and take the node with the lowest cost as current node；

4. Add the current node to the closed set；

5. if the current node is the destination node $N e n d$

break；

6. else

7. Remove the current node from the open set；

8. Generate the neighboring nodes with the time step （dt） according

to equation（3）；

9. for each neighboring node

10. if it is in the closed set or doesn’t pass the reasonability check

11. continue；

12. else

13. if it is not in the open set， add it to the open set；

14. end

15. end

16. end

17. end

18. Trajectory = Back track nodes in the closed set from the $N e n d$ to $N s t a r t$ by the lowest cost；

19. return coarse trajectory；

参数	数值
车长 $L V / m$	4.79
车宽 $W / m$	1.92
轴距 $L / m$	2.91
前轮转角范围 $δ / (°)$	［-22， 22］
速度范围 $v / (m · s - 1)$	［0， 20］
加速度范围 $a / (m · s - 2)$	［-3， 2］
离散加速度集 $A$	｛-3，-1，-0.2， 0， 0.1， 0.3，0.6，1，1.5，2｝
前轮转角离散数量 $N$	11

References 18

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场景	平均耗时/ms
场景	本文方法	Lattice^［18］	时空RRT*^［6］
换道超车	117	57	683
旁车切入	76	35	410

Spatio-temporal Joint Planning Method of Intelligent Vehicles Based on Improved Hybrid A

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