考虑驾驶员和道路特性的车辆自适应巡航模型预测控制

摘要

文章提出一种将模糊逻辑控制与模型预测控制相结合的控制方法用于车辆的自适应巡航控制(ACC).在该方法中,模糊控制器根据驾驶员和道路特性对模型预测控制器得到的优化结果进行修正,得到期望的纵向加速度作为主车的控制输入.ACC算法在Matlab/Simulink中搭建,仿真结果显示,提出的ACC算法能够在不同的驾驶风格和路面条件下很好地实现跟车功能,算法具有很强的鲁棒性.%In this paper, a control method combining fuzzy logic control and model predictive control for adaptive cruise control (ACC) of vehicles is proposed. In this method, the optimization result obtained by the model prediction controller according to the characteristics of the driver and the road is corrected by the fuzzy controller, and the desired longitudinal acceleration is obtained as the control input of the host vehicle. The ACC algorithm in this paper is built in Matlab/Simulink. The simulation results show that the proposed method implements follow-up functions well, and the algorithm has strong robustness under different driving styles and road conditions.