Personalized Motion Planning and Tracking Control for Autonomous Vehicles Obstacle Avoidance

A personalized motion planning and tracking control framework is proposed to prevent collisions between autonomous vehicles and obstacles ahead. The presented framework consists of a motion planning generator and a cooperative tracking controller. For motion planning, a multi-constrained numerical optimization method is used to generate the obstacle avoidance motion planning for autonomous vehicles according to the individual needs of the passengers. For tracking control, a cooperative longitudinal and lateral motion controller is designed to track the planning results. The longitudinal controller is composed of a model predictive controller, and the lateral controller is composed of a nonlinear steering controller. The planning results show that the adopted motion planning algorithm can achieve personalized motion planning according to the needs of the passengers. Simulink and CarSim co-simulation results show the excellent tracking performance of the proposed cooperative controller. The performance analysis results show that the proposed framework can improve the corresponding driving performance according to the individual needs of the passengers.