Design and Simulation of Intelligent Vehicle Trajectory Tracking Control Algorithm Based on LQR and PID

Abstract

In order to improve the accuracy and robustness of intelligent vehicle trajectory tracking, a longitudinal and lateral control strategy based on linear quadratic regulator (LQR) and proportional-integral-derivative (PID) algorithm was proposed. First, the two-degree-of-freedom vehicle kinematics model and trajectory tracking error model are established. Second, the trajectory tracking controller of lateral LQR control algorithm and the speed tracking controller of longitudinal double PID control algorithm are designed, and the key parameters of lateral LQR control are determined by genetic algorithm. Finally, the control algorithm is simulated by CarSim and Simulink under three working conditions: Low speed, Medium speed, and High speed. The simulation results show that the distance deviation of the lateral and longitudinal control algorithm in trajectory tracking is less than 0.05 m, and the front wheel angle and yaw angular velocity change smoothly, which ensures the accuracy and stability of trajectory tracking and improves the comfort of passengers to a certain extent.

Keywords

• intelligent vehicle
• trajectory tracking
• lateral and longitudinal control
• lqr
• pid