A MPC-BASED Mix function controller on path planning and path tracking of autonomous vehicles

Autonomous tracking control is one of the most important part among the vehicle autonomous navigation, it is related to the safety and comfort of vehicles and traffic efficiency. In this paper, the model predictive control method is designed to solve the problem of path planning and tracking controller in the process of overtaking. Based on the analysis of lane changing model, the kinematics of the vehicle is established to research the kinematics regularly of the vehicle from the perspective of geometry. In addition, the minimum safe distance model of overtaking lane change is constructed. By comparing several typical lane change models, the mixed function model is selected as the path planning model of overtaking lane change. The experimental results demonstrate that the improved model predictive control method has the advantages of small steady-state error, fast response and strong robustness, which can effectively improve the accuracy of path tracking.