基于自适应预测步长的车辆主动转向跟踪控制

Autonomous Vehicle Active Steering Tracking Control Based on Adaptive Prediction Step

为提高智能车辆主动转向跟踪控制的跟踪精度、稳定性和实时性等问题,提出一种基于自适应预测步长的模型预测路径跟踪控制器,引入自适应预测步长功能函数,根据车速和参考路径的曲率动态调整预测步长。MATLAB和CarSim联合仿真结果表明:该控制器可降低横向跟踪偏差,在高速低附着和高速高附着工况下均保持车辆稳定性,相比于单一根据道路曲率动态调整预测预测步长的控制器,降低了60%的计算时间,提高了实时性。

In order to improve the tracking accuracy,stability and real-time performance of autonomous vehicle active steering tracking control,a model prediction path tracking controller based on adaptive prediction step is proposed,and an adaptive prediction step function is introduced.Based on the curvature of the path,dynamically adjust the prediction step size.MATLAB and Car Sim joint simulation results show that the controller can reduce lateral tracking deviation and maintain vehicle stability under both high-speed low-adhesion conditions and high-speed high-adhesion conditions.Compared with the controller that only dynamically adjusts the predicted prediction step based on road curvature,it reduces the calculation time by 60%and greatly improves the real-time performance.