Design of Vehicle Trajectory Optimization Based on Multiple-Shooting method and Modified Particle Swarm Optimization

This paper applies multiple-shooting method and modified particle swarm optimization to trajectory optimization of vehicles. The multiple-shooting method is used to discretize the control and state quantities of the vehicle model and transform the trajectory optimization problem into a nonlinear programming problem. Particle swarm optimization (PSO) is used to solve the parametric nonlinear programming problem and improves the traditional penalty functions. The fitness functions are calculated by using the constraint measure combining distance measure and adaptive penalty functions. A diving trajectory of vehicles is optimized whose simulation results verify the effectiveness and versatility of the proposed algorithm, comparing with direct-shooting method.