Research on Vehicle Multi-Objective Adaptive Cruise Control System Based on Particle Swarm Optimization Algorithm

To improve the comfort and take the vehicle safety into account at the same time of car following process of the adaptive cruise control (ACC) system, A multi-objective ACC hierarchical control system is designed. The upper layer is the desired acceleration planning layer, Firstly, a variable time headway (VTH) strategy is introduced, and a model predictive control (MPC) algorithm considering multi-objective optimization is designed, secondly, by adopting relaxation vector management method, the problem is solved which the MPC algorithm can't find the optimum solution caused by hard constraints, then the control problem is transformed into a quadratic programming problem with multiple constraints, and the particle swarm optimization (PSO) algorithm is introduced to solve the problem. The lower layer is the control execution layer, the switching strategy of throttle control and brake control is designed, and the lower level controller is realized by PID (proportional integral derivative) control and Lookup-Table (2-D) module. The simulation results show that the multi-objective ACC algorithm based on particle swarm optimization can improve the safety, comfort and fuel economy of the vehicle.