Abstract: As an important part of advanced assisted (ADAS) driving, lane keeping control is significant to reduce driving fatigue and improve driving safety. Based on lane line potential field design and model predictive control, this paper proposes a model predictive lane keeping control method that integrates lane line potential field to optimize driving stability and safety during lane keeping. The co-simulation of the proposed algorithm is carried out under Carsim&Simulink. The simulation results show that, compared with PID control, the lane keeping algorithm based on model predictive control has obvious advantages in both tracking accuracy and vehicle stability, and the lateral tracking accuracy and vehicle stability are significantly improved. Furthermore, compared with the lane keeping MPC without the fusion of the lane line potential field, the proposed method has better vehicle stability and traffic efficiency (27.8 km/h vs 26.6 km/h), and its maximum yaw rate and maximum lateral acceleration decrease by almost 10%. The simulation results show the effectiveness and superiority of the proposed algorithm, which has good engineering guiding significance.