Application improvement of A* algorithm in intelligent vehicle trajectory planning

被引:26
|
作者
Xiong, Xiaoyong [1 ]
Min, Haitao [1 ]
Yu, Yuanbin [1 ]
Wang, Pengyu [1 ]
机构
[1] Jilin Univ, State Key Lab Automot Simulat & Control, 5988 Renmin St, Changchun 130022, Jilin, Peoples R China
基金
国家重点研发计划;
关键词
intelligent vehicle; trajectory planning; motion control; A-star; pure pursuit;
D O I
10.3934/mbe.2021001
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Trajectory planning is one of the key technologies for autonomous driving. A* algorithm is a classical trajectory planning algorithm that has good results in the field of robot path planning. However, there are still some practical problems to be solved when the algorithm is applied to vehicles, such as the algorithm fails to consider the vehicle contours, the planned path is not smooth, and it lacks speed planning. In order to solve these problems, this paper proposes a path processing method and a path tracking method for the A* algorithm. First, the method of configuring safe redundancy space is given considering the vehicle contour, then, the path is generated based on A* algorithm and smoothed using Bessel curve, and the speed is planned based on the curvature of the path. The trajectory tracking algorithm in this paper is based on an expert system and pure tracking theory. In terms of speed tracking, an expert system for the acceleration characteristics of the vehicle is constructed and used as a priori information for speed control, and good results are obtained. In terms of path tracking, the required steering wheel angle is calculated based on pure tracking theory, and the influence factor of speed on steering is obtained from test data, based on which the steering wheel angle is corrected and the accuracy of path tracking is improved. In addition, this paper proposes a target point selection method for the pure tracking algorithm to improve the stability of vehicle directional control. Finally, a simulation analysis of the proposed method is performed. The results show that the method can improve the applicability of the A* algorithm in automated vehicle planning.
引用
收藏
页码:1 / 21
页数:21
相关论文
共 50 条
  • [1] Application of intelligent algorithm in trajectory optimization of hypersonic vehicle
    Liu, L. H.
    [J]. 10TH ASIAN-PACIFIC CONFERENCE ON AEROSPACE TECHNOLOGY AND SCIENCE & THE 4TH ASIAN JOINT SYMPOSIUM ON AEROSPACE ENGINEERING (APCATS'2019 /AJSAE'2019), 2020, 1509
  • [2] the Algorithm of Warehouse Vehicle Trajectory Intelligent Identification
    Jin, Kangcheng
    Cao, Jie
    Shen, Dongqin
    [J]. 6TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT, 2018, 139 : 64 - 70
  • [3] Research on Intelligent Vehicle Trajectory Planning Based on Multimodal Trajectory Prediction
    Huang, Jing
    Liu, Xiangzhen
    Deng, Xiaoyang
    Chen, Ran
    [J]. Qiche Gongcheng/Automotive Engineering, 2024, 46 (06): : 965 - 974
  • [4] Lane Change Trajectory Planning and Simulation for Intelligent Vehicle
    Wang, Chang
    Zheng, Chuqing
    [J]. CONSTRUCTION AND URBAN PLANNING, PTS 1-4, 2013, 671-674 : 2843 - 2846
  • [5] Intelligent trajectory planning model for electric vehicle in unknown environment
    Sheng, Pengcheng
    Ma, Jingang
    Wang, Dapeng
    Wang, Wenyang
    Elhoseny, M.
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2019, 37 (01) : 397 - 407
  • [6] Motion trajectory planning method of lane change for intelligent vehicle
    Li, Aijuan
    Li, Shunming
    Shen, Huan
    Miao, Xiaodong
    Li, Xiao
    [J]. Journal of Theoretical and Applied Information Technology, 2012, 45 (01) : 297 - 302
  • [7] Unmanned Ground Vehicle Local Trajectory Planning Algorithm
    Goll, Stanislav A.
    Leushkin, Vladimir S.
    Luksha, Sergey S.
    Borisov, Alexandr G.
    [J]. 2016 5TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO), 2016, : 317 - 321
  • [8] Trajectory Planning of Unmanned Aerial Vehicle Based On A* Algorithm
    Xu, Hao
    Xu, Xiangrong
    Li, Yan
    Zhu, Xiaosheng
    Jia, Liming
    Shi, Dongqing
    [J]. 2014 IEEE 4TH ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (CYBER), 2014, : 463 - 468
  • [9] Application of Improved RRT Algorithm in Intelligent Vehicle Path Planning Under Complicated Environment
    Zhang W.-B.
    Xiao J.-L.
    [J]. Zhongguo Gonglu Xuebao/China Journal of Highway and Transport, 2021, 34 (03): : 225 - 234
  • [10] Spatial-Temporal Risk Field for Intelligent Connected Vehicle in Dynamic Traffic and Application in Trajectory Planning
    Han, Jiayi
    Zhao, Jian
    Zhu, Bing
    Song, Dongjian
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (03) : 2963 - 2975