Intelligent vehicle obstacle avoidance path-tracking control based on adaptive model predictive control

Abstract. In order to solve the problems of low path-tracking accuracy, poor safety, and stability intelligent vehicles with variable speeds obstacles on road, a double-layer adaptive model predictive controller (MPC) is designed. A vehicle point mass used in an obstacle avoidance planning controller, safety collision distance established according relationship between improve driving vehicle. The design based three-degrees-of-freedom dynamics model. According horizon speed MPC algorithm, control strategy which can update prediction real time proposed accuracy path tracking. To increase stability, sideslip angle acceleration are added as soft constraint conditions. method simulated CarSim MATLAB/Simulink co-simulation platform. simulation results show that maximum lateral deviation centroid designed 0.13 m 0.4∘, respectively. Compared traditional MPC, reduced by 0.51 1.57∘, respectively, proves effectiveness method.