Autonomous Vehicle Lateral Control Based on Fractional-order PID

Lateral control is the key technology of autonomous driving. The traditional model-based lateral control algorithm relies on the mathematical model of the controlled vehicle, and the inaccuracy of the model results in poor algorithm performance. In order to further improve the tracking accuracy of the target path, a fractional-order PID control algorithm based on data-driven control is proposed for control, and the particle swarm optimization (PSO) algorithm is used to optimize its parameters. In order to prove the performance of the algorithm, based on the MATLAB/CarSim joint simulation platform, it was compared with the PID control and linear quadratic regulator (LQR) under the same working conditions. The experimental results show that the vehicle based on the FOPID control can effectively overcome the increase in tracking error caused by the change of path curvature, while the vehicle can maintain good comfort, stability and safety.