基于MPC的无人驾驶车辆轨迹跟踪算法

Driverless Vehicle Trajectory Tracking Algorithm Based on MPC

基于三自由度车辆运动学模型,为前轮转向的无人驾驶车辆设计了一种轨迹跟踪控制算法,建立了车辆轨迹跟踪状态方程,采用模型预测控制算法,通过滚动优化和反馈校正对无人驾驶车辆实现了最优控制。为了验证运动学模型和该算法的有效性,对运动学模型进行仿真分析,并建立Carsim-Simulink联合仿真平台,分别对直线轨迹和圆形轨迹进行仿真实验。仿真结果表明,该运动学模型和算法能够有效进行无人驾驶的轨迹跟踪。

Based on the kinematics model of three-degree-of-freedom vehicle,a trajectory tracking control algorithm was designed for the driverless vehicle with front-wheel steering,and the vehicle trajectory tracking state equations were established.The model predictive control algorithm was used to achieve optimal control of the driverless vehicle through roll optimization and feedback correction.In order to verify the effectiveness of the kinematics model and the algorithm,the kinematics model was simulated and analyzed,and a Carsim-Simulink co-simulation platform was established to conduct simulation experiments on linear trajectories and circular trajectories respectively.The simulation results showed that the kinematics model and the algorithm can effectively track the trajectory of the driverless vehicle.