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.
Research on trajectory tracking control algorithms for autonomous vehicles
Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024) ; 2024 ; Kuala Lumpur, Malaysia
Proc. SPIE ; 13250
23.08.2024
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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