Research on trajectory tracking control algorithms for autonomous vehicles

Jigao Niu; Zhongjing Zhou; Chengcheng Cui; Jiangke Jiu

doi:10.1117/12.3038545

23 August 2024 Research on trajectory tracking control algorithms for autonomous vehicles

Jigao Niu, Zhongjing Zhou, Chengcheng Cui, Jiangke Jiu

Author Affiliations +

Proceedings Volume 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024); 132501U (2024) https://doi.org/10.1117/12.3038545
Event: Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 2024, Kuala Lumpur, Malaysia

Abstract

A coordinated control strategy integrating Linear Quadratic Regulator (LQR) and Model Predictive Control (MPC) has been designed to enhance the trajectory tracking accuracy and stability of autonomous vehicles. This strategy consists of upper and lower-level controllers, with the upper level responsible for tracking desired trajectories and vehicle speed while minimizing lateral error. The lower-level control executes actions to achieve desired steering angles and accelerations. An Extended Kalman Filter (EKF) observer is employed to update the vehicle state. Finally, hardware-in-the-loop testing experiments are conducted to validate the robustness and effectiveness of the controller, which effectively reduces lateral error and improves tracking accuracy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jigao Niu, Zhongjing Zhou, Chengcheng Cui, and Jiangke Jiu "Research on trajectory tracking control algorithms for autonomous vehicles", Proc. SPIE 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 132501U (23 August 2024); https://doi.org/10.1117/12.3038545

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