基于配点法的智能车实时轨迹跟踪研究

Real-time Trajectory Tracking Research of Intelligent Vehicle Based on Collocation Method

针对智能汽车在实际行驶过程中的轨迹跟踪问题,提出了一种基于配点法的非线性模型预测控制实时优化算法。建立车辆二自由度非线性动力学模型和轨迹跟踪最优控制问题的数学模型,采用配点法将最优控制问题转化为带约束的非线性规划问题,并运用序列二次规划法实现了快速求解,通过滚动优化和反馈校正达到了对智能车实时轨迹跟踪的效果。在Prescan自动驾驶仿真环境中进行了基于ROS操作系统的硬件在环试验。结果表明:所提出的方法在保证精度的情况下,计算速度快,可以达到实时轨迹跟踪优化的要求。

A real-time optimization algorithm of nonlinear model predictive control based on collocation method was proposed to solve the trajectory tracking problem of intelligent vehicles in the actual driving process.The 2-DOF nonlinear dynamic model of the vehicle and the mathematical model of trajectory tracking optimal control problem were established.The optimal control problem was transformed into a nonlinear programming problem with restricting conditions by using the collocation method,and the sequential quadratic programming method was used to realize the fast solution.Through rolling optimization and feedback correction,the effect of real-time trajectory tracking of intelligent vehicles was achieved.In Prescan automatic driving simulation environment,the hardware-in-loop test based on ROS operating system was carried out.The results show that the proposed method is fast and can meet the requirements of real-time trajectory tracking optimization in the case of ensuring accuracy.