Unmanned driving trajectory planning method based on obstacle prediction and MPC (Model predictive control) algorithm

The invention discloses an unmanned driving trajectory planning method based on obstacle prediction and an MPC (Model predictive control) algorithm. The method includes the following steps of: surrounding vehicle motion trajectory prediction; collision prediction analysis and minimum safety distance calculation; reference trajectory and constraint condition generation; and model predictive control(MPC)-based trajectory optimization to obtain final trajectory output. With the method of the invention adopted, obstacle motion prediction and model predictive control (MPC) principle-based trajectory optimization is utilized to perform the motion decision and trajectory planning of a driverless vehicle. 本发明公开了一种基于障碍物预测与MPC算法的无人驾驶轨迹规划方法：周围车辆运动轨迹预测；碰撞预测分析与最小安全距离的计算；考轨迹与约束条件的生成；利用模型预测控制(MPC)进行轨迹优化，得到最终轨迹输出。本发明能够利用障碍物运动预测与模型预测控制(MPC)原理的轨迹最优化进行无人驾驶车辆的运动决策与轨迹规划。