Path tracking of autonomous vehicle based on adaptive preview trajectory planning with the consideration of vehicle stability

被引:4
|
作者
Qiu, Bin [1 ,2 ]
Wei, Lingtao [1 ]
Wang, Xiangyu [1 ]
Li, Liang [1 ]
Zhou, Daolin [1 ]
Wang, Zhenfeng [3 ]
机构
[1] Tsinghua Univ, State Key Lab Automot Safety & Energy Conservat, Room AD222,Lee Shau Kee Bldg Sci & Tech, Beijing 100084, Peoples R China
[2] Minist Ind & Informat Technol, Equipment Ind Dev Ctr, Beijing, Peoples R China
[3] CATARC Tianjin Automot Engn Res Inst Co Ltd, Tianjin, Peoples R China
关键词
Path planning; preview distance; optimal control; linear quadratic regulator; polynomial fitting; DRIVER STEERING CONTROL; FUZZY CONTROL; MODEL; DESIGN;
D O I
10.1177/09544070221094112
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The path control gives the target path through planning, and uses the tracking strategy to make the vehicle converge to the target path. How to balance the tracking performance and the vehicle stability is a crucial and worthy research for the autonomous vehicle safety. In this paper, a hierarchical path control strategy consists of path planning and tracking with the consideration of vehicle lateral stability is proposed. In the adaptive preview distance block, the preview distance is adaptively regulated according to the vehicle speed, sideslip angle, and the preview trajectory curvature to balance the tracking error and stability. In the path planning block, the three-order polynomial fitting method is adopted to give the desired path according to the preview distance and the relative position relationship between vehicle and road or obstacles. The linear quadratic regulator (LQR) controller is designed to tracking the desired path fully using the previewed curvatures and the vehicle motion error. The hardware in the loop (HIL) simulation and vehicle test results illustrate that the proposed strategy can deal with path tracking, avoidance and lance change scenes in low computation burden, and maintain the stability of vehicle simultaneously.
引用
收藏
页码:1228 / 1240
页数:13
相关论文
共 50 条
  • [21] Adaptive Generalized Dynamic Inversion based Trajectory Tracking Control of Autonomous Underwater Vehicle
    Ansari, Uzair
    Bajodah, Abdulrahman H.
    Alam, Saqib
    2018 26TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION (MED), 2018, : 588 - 594
  • [22] Path tracking control of autonomous vehicle based on MPC
    Zhou, Zhiyuan
    Bao, Yi
    2024 3RD INTERNATIONAL CONFERENCE ON ENERGY AND POWER ENGINEERING, CONTROL ENGINEERING, EPECE 2024, 2024, : 211 - 216
  • [23] Autonomous ground vehicle path tracking
    Wit, J
    Crane, CD
    Armstrong, D
    JOURNAL OF ROBOTIC SYSTEMS, 2004, 21 (08): : 439 - 449
  • [24] RRT based Path Planning for Autonomous Parking of Vehicle
    Zheng, Kaiyu
    Liu, Shan
    PROCEEDINGS OF 2018 IEEE 7TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE (DDCLS), 2018, : 627 - 632
  • [25] A Behavior-Based Path Planning for Autonomous Vehicle
    Xiu, CaiJing
    Chen, Hui
    INTELLIGENT ROBOTICS AND APPLICATIONS, PT II, 2010, 6425 : 1 - 9
  • [26] Trajectory tracking and stability control of high-speed autonomous vehicle
    Wang Y.-Q.
    Gao S.
    Wang Y.-H.
    Xu Y.
    Guo D.
    Zhou Y.-C.
    Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science), 2021, 55 (10): : 1922 - 1929and1947
  • [27] Trajectory planning for autonomous modular vehicle docking and autonomous vehicle platooning operations
    Li, Qianwen
    Li, Xiaopeng
    TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2022, 166
  • [28] Path planning with PSO for autonomous vehicle
    Cai, L.
    Jia, J. P.
    ADVANCES IN ENGINEERING MATERIALS AND APPLIED MECHANICS, 2016, : 263 - 266
  • [29] Obstacle-avoidance path planning and tracking control of an autonomous vehicle
    Sun, Zhe
    Li, Shengrui
    Hong, Yiting
    Chen, Bo
    2022 IEEE 17TH INTERNATIONAL CONFERENCE ON CONTROL & AUTOMATION, ICCA, 2022, : 927 - 931
  • [30] An Adaptive Path Tracking Method for Autonomous Land Vehicle based on Neural Dynamic Programming
    Zhu, Qi
    Huang, Zhenhua
    Liu, Daxue
    Dai, Bin
    2016 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, 2016, : 1429 - 1434