一种针对铰接转向车辆的状态预测方法

A State Prediction Method for Articulated Steering Vehicle

车辆状态预测对于风险评估以及规划控制意义重大。提出了一种用于铰接转向车辆的状态预测方法。首先构建了模型预测控制器,并根据控制信息设计了虚拟测量向量。接着设计了一种卡尔曼滤波预测器,融合了虚拟测量向量以及模型预测结果并输出最终预测结果。仿真结果表明,提出的状态预测算法可以准确预测0.5秒内铰接转向车辆的铰接转角、速度以及位置。

Vehicle state prediction is essential for risk assessment and control.A state prediction method is proposed for articulated steering vehicles.First,the model prediction controller is constructed,and the pseudo-measurement vector is designed according to the control information.Then a Kalman filter predictor,which combines the virtual measurement vector and the model prediction results,is designed to output the final prediction results.The simulation results show that the proposed state prediction algorithm can accurately predict the articulated steering vehicle states within 0.5 seconds,including steering angle,speed,and position.