Path planning and discrete sliding mode tracking control for high-speed lane changing collision avoidance of vehicle

被引：0
|
作者：
Zhang J.-X. [1 ,2 ]
Wang X.-Z. [1 ]
Zhao J. [1 ]
Shi Z.-T. [3 ]
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
[3] Intelligent Vehicle Control System Research Institute, Zhejiang Asia-Pacific Mechanical and Electronic Co., Ltd., Hangzhou
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2021年 / 51卷 / 03期
关键词：
Discrete sliding mode control; Disturbance observer; High-speed lane changing collision avoidance; Path planning and tracking control; Quantic polynomial curve; Vehicle engineering;
D O I：
10.13229/j.cnki.jdxbgxb20200057
中图分类号：
学科分类号：
摘要：
In order to solve the problem of path planning and tracking control for high-speed lane changing collision avoidance of vehicle, a path planning method and a path tracking control strategy for high-speed lane changing collision avoidance of vehicle are proposed based on quintic polynomial curve and discrete sliding mode control theory, respectively. Firstly, a feasible path is planned based on quintic polynomial curve. The mapping relationship between the maximum curvature, the maximum curvature change rate of the planned path and the undetermined coefficients of the quintic polynomial curve is established indirectly by lookup table, so that the planned path meets the requirements of riding comfort and safety. Secondly, in order to track the planned path based on quintic polynomial curve quickly and steadily, a linear discrete control model with additive uncertainty is established by combining the vehicle kinematics model with the linear vehicle dynamics model of two degrees of freedom, and a path tracking control strategy is designed based on discrete sliding mode control theory with disturbance observer. Finally, a model in the loop simulation system is established based on the software of vehicle dynamics. The feasibility and effectiveness of the proposed path planning method and path tracking control strategy are verified by the model in the loop simulation system. © 2021, Jilin University Press. All right reserved.
引用
收藏
页码：1081 / 1090
页数：9
相关论文
共 16 条
  • [1] Funke J, Brown M, Erlien S M, Et al., Collision avoidance and stabilization for autonomous vehicles in emergency scenarios, IEEE Transactions on Control Systems Technology, 25, 4, pp. 1204-1216, (2017)
  • [2] Zhang Lin, Zhang Xin-jie, Guo Kong-hui, Et al., Rolling window optimization for intelligent vehicle trajectory planning in unknown environment, Journal of Jilin University(Engineering and Techinology Edition), 48, 3, pp. 654-660, (2018)
  • [3] Li Shao-song, Li Zheng, Yu Zhi-xin, Et al., Dynamic trajectory planning and tracking for autonomous vehicle with obstacle avoidance based on model predictive control, IEEE Access, 7, pp. 132074-132086, (2019)
  • [4] Minh V T, Pumwa J., Feasible path planning for autonomous vehicles
  • [5] Wang C Y, Zhao W Z, Xu Z J, Et al., Path planning and stability control of collision avoidance system based on active front steering, Science China Technological Sciences, 60, 8, pp. 1231-1243, (2017)
  • [6] Peng T, Su L L, Zhang R H, Et al., A new safe lane-change trajectory model and collision avoidance control method for automatic driving vehicles, Expert Systems with Applications, 141, (2020)
  • [7] Song Xiao-lin, Cao Hao-tian, Huang Jiang, Vehicle path planning in various driving situations based on the elastic band theory for highway collision avoidance, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 227, 12, pp. 1706-1722, (2013)
  • [8] Ji J, Khajepour A, Melek W, Et al., Path planning and tracking for vehicle collision avoidance based on model predictive control with multi-constraints, IEEE Transactions on Vehicular Technology, 66, 2, pp. 952-964, (2017)
  • [9] Guo Hong-yan, Jia Rui, Yu Zai-tao, Et al., Obstacle avoidance for autonomous ground vehicles based on moving horizon optimization, Proceeding of the 11th World Congress on Intelligent Control and Automation, (2014)
  • [10] Zhang Chao-yong, Chu Duan-feng, Liu Shi-dong, Et al., Trajectory planning and tracking for autonomous vehicle based on state lattice and model predictive control, IEEE Intelligent Transportation Systems Magazine, 11, 2, pp. 29-40, (2019)
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