复杂路况下无人车辆全速域路径跟踪复合控制研究

Study on composite path tracking control of unmanned vehicle in full-speed domain under complex road conditions

针对无人驾驶车辆控制器在宽速度变化范围及复杂路况下跟踪适应性问题,提出一种路径跟踪复合控制方法。建立基于车辆误差状态空间方程的模型预测控制器,并通过它求解前轮转角和纵向加速度,控制车辆直线行驶时精确跟踪目标路径;在分析车辆行驶过程中不同车速和路面附着系数对路径跟踪性能影响基础上,利用模糊控制原理构建转角补偿控制,并以道路曲率信息作为补偿控制选择机制;二者共同构成无人驾驶车辆全速域路径跟踪复合控制器。在考虑安全行车的避障路径规划下进行跟踪实验,结果表明:在全路面系数下以0~180 km/h速度变化,提出的控制方法都具有良好的控制效果,以180 km/h在冰雪路面上行驶时,其最大横向误差仅为0.36 m。

Aiming at the tracking adaptability of unmanned vehicle controllers in the wide range of speed variation and complex road conditions,a path tracking composite control method is proposed.A model predictive controller based on the vehicle error state space equation is established,and solves the front wheel angle and longitudinal acceleration to control the vehicle to accurately track the target path in its straight line.Based on the analysis of the impact of different vehicle speeds and road attachment coefficients on the path tracking performance,the fuzzy control principle is used to construct the corner compensation control,and the road curvature information is used as the compensation control selection mechanism.The two controllers together constitute the full-speed domain path tracking composite control for unmanned vehicles.Tracking experiments are done under the obstacle avoidance path planning considering safe driving,the results show that the proposed control method has good control effect in the change range of 0~180 km/h under the whole road attachment coefficients,and the maximum lateral error is only 0.36 m when driving at 180 km/h on icy and snowy roads.