关键词: 协同自适应巡航控制, 执行器时延, 模型预测算法, 联合仿真

Abstract: In the hierarchical longitudinal control structure of the Cooperative Adaptive Cruise Control（CACC） system, the upper level controller uses the state space model predictive control algorithm to determine the desired longitudinal acceleration of the target vehicle by the expected distance and the real-time information of the vehicles and the environment. The lower level controller determines the throttle or brake commands required to track the desired acceleration. The actuator delay of a vehicle has a significant impact on the stability of the system. In view of the compensation characteristic of the dynamic matrix control algorithm on the pure lag object, an improved model predictive control algorithm is proposed by this paper and combined with the PID control algorithm（the lower level controller） to form the hierarchical longitudinal control structure, which is used to compensate the effect of vehicle actuator delay. The designed algorithm is simulated by SIMULINK/CARSIM co-simulation platform. The simulation results show that the designed algorithm can reduce the speed tracking error and the spacing error of the CACC system in following process and improve the stability of the system.

Key words: Cooperative Adaptive Cruise Control（CACC）, actuator delay, Model Predictive Control（MPC） algorithm, co-simulation