无人驾驶车辆轨迹跟踪控制研究

Research on Trajectory Tracking Control of Driverless Vehicles

为了提升智能车辆在轨迹跟踪控制中的性能,文章基于车辆运动学模型建立了一种带有前馈补偿和反馈最优控制策略的线性二次型调节器(LQR)轨迹跟踪控制算法。并通过搭建Carsim/Simulink联合仿真模型,验证该算法在不同工况下的轨迹跟踪效果。结果表明,该算法在不同车速和不同路面附着条件下都能保证无人驾驶车辆准确地跟踪参考轨迹,且具有较强的鲁棒性。

In order to improve the performance of driverless vehicles in trajectory tracking control, a linear quadratic regulator(LQR) trajectory tracking control algorithm with feedforward compensation and feedback optimal control strategy is established based on vehicle kinematics model. By constructing the Carsim/Simulink joint simulation model, the trajectory tracking effect of the algorithm under different conditions is verified. The results show that the proposed algorithm can ensure that the driverless vehicle accurately tracks the reference trajectory under different vehicle speeds and different road surface attachment conditions, and has strong robustness.