Autonomous valet parking path planning based on hierarchical architecture

被引：0
|
作者：
Zhang J. [1 ,2 ]
Wang Z. [1 ]
Guo C. [1 ]
Zhao J. [1 ]
Zhou S. [2 ]
机构：
[1] State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun
[2] Intelligent Network R & D Institute, China FAW Group Co., Ltd., Changchun
来源：
Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) | 2021年 / 51卷 / 05期
关键词：
A[!sup]*[!/sup] algorithm; Autonomous valet parking; Improved dynamic window method; Path planning; Raster scanned algorithm;
D O I：
10.3969/j.issn.1001-0505.2021.05.021
中图分类号：
学科分类号：
摘要：
In order to solve the problem of automatic driving in the last kilometer, a novel autonomous valet parking path planning algorithm is proposed based on the hierarchical architecture. Firstly, the raster scanned algorithm is used to quickly and accurately convert the map of autonomous valet parking environment into Voronoi diagram, which can quantify the distance between any grid area and the nearest obstacle in the environment. Then, the A* algorithm is used to plan the global autonomous valet parking path, and the priority queue is used to realize the open list of A* algorithm to improve its computational efficiency. Finally, the Voronoi diagram in the autonomous valet parking environment is used to detect vehicle collision, and along the global autonomous valet parking path, a collision free path satisfying the non-holonomic and mechanical constraints of vehicle is planned by the improved dynamic window method, which expands the feasible solution space of the traditional dynamic window method and reduces its conservatism. The feasibility and effectiveness of the proposed autonomous valet parking path planning algorithm are verified in VC++6.0 environment. The results show that the proposed algorithm can safely and quickly guide the vehicle to the near target parking space, and lay the foundation for the car to perform subsequent parking operations. © 2021, Editorial Department of Journal of Southeast University. All right reserved.
引用
收藏
页码：883 / 888
页数：5
相关论文
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