Lane Changing Comfort Trajectory Planning of Intelligent Vehicle Based on Particle Swarm Optimization Improved Bezier Curve

This paper focuses on lane-changing trajectory planning and trajectory tracking control in autonomous vehicle technology. Aiming at the lane-changing behavior of autonomous vehicles, this paper proposes a new lane-changing trajectory planning method based on particle swarm optimization (PSO) improved third-order Bezier curve path planning and polynomial curve speed planning. The position of Bezier curve control points is optimized by the particle swarm optimization algorithm, and the lane-changing trajectory is optimized to improve the comfort of lane changing process. Under the constraints of no-collision and vehicle dynamics, the proposed method can ensure that the optimal lane-changing trajectory can be found in different lane-changing scenarios. To verify the feasibility of the above planning algorithm, this paper designs the lateral and longitudinal controllers for trajectory tracking control based on the vehicle dynamic tracking error model. The simulation is carried out in the Carsim-Simulink co-simulation platform. The simulation results show that the trajectory planning method proposed in this paper can ensure the safety and efficiency of lane changing of the vehicle in the process of lane changing, and has better performance in ride comfort.