Anti-collision Trajectory Planning and Tracking Control based on MPC and Fuzzy PID Algorithm

Abstract

The active anti-collision technology can ensure vehicles to avoid car accidents in a short time, since vehicle collision accounts for a large proportion of most traffic accidents. It has become an important research content of active vehicle safety. In this paper a double-layer controller of trajectory planning and tracking is designed to improve driving safety for intelligent vehicles. Firstly, 2-DOF(degree-of-freedom) vehicle dynamics model is established based on the intelligent vehicle platform with front wheel steering. Secondly, the point mass vehicle model is applied to design the collision avoidance function and the trajectory re-planning function. The problem of anti-collision trajectory planning is transformed into a nonlinear quadratic planning problem with the constraints of speed, angle and angle increment. Based on MPC algorithm, the anti-collision trajectory in dynamic environment is re-planned, and the trajectory planner of active collision avoidance model for intelligent vehicle is established. Thirdly, a fuzzy adaptive PID trajectory tracking controller is employed as the trajectory tracking layer of this anti-collision model. Finally, the collision avoidance effect is simulated in Matlab/Simulink environment. The results show that the model has better collision avoidance effect and helps to track the original driving trajectory at 36km/h speed. The vehicle tests show that the dynamic trajectory planning algorithm based on MPC can ensure the vehicle to plan the anti-collision trajectory in real time when sensing obstacles, and the fuzzy PID algorithm as the trajectory tracking layer can ensure the tracking accuracy of the original trajectory after collision avoidance.