Trajectory Tracking Control of Autonomous Vehicle Based on Optimized Preview Distance

Developing a fast and accurate trajectory tracking method is a core control task in the development of autonomous driving technology. This paper establishes a dynamic residual model based on the vehicle preview distance and constructs a trajectory tracking controller using a model predictive control (MPC) algorithm with the front wheel steering angle as the control input. By designing an optimized preview distance method that considers the vehicle state and the reference trajectory, the tracking accuracy is improved. The objective function and constraint conditions are designed to comprehensively consider the accuracy of vehicle tracking control and driving stability. A jiont simulation platform combing Carsim and Simulink is built to verify the effectiveness of the algorithm. Conduct simulation experiments at different speeds under double lane change conditions to explore the impact of preview distance on control results and design optimization methods for preview distance. The results of the simulation experiments demonstrate that compared to the case without optimized preview distance, the trajectory tracking controller designed in this paper can achieve high-precision control. When the vehicle is traveling at high speed,the lateral displacement error is less than 10 cm, the heading angle error is less than 1°,and the vehicle stability is significantly improved. © 2024 Science Press. All rights reserved.