未知环境下智能汽车轨迹规划滚动窗口优化

Rolling window optimization for intelligent vehicle trajectory planning in unknown environment

为解决多约束条件下智能汽车在未知环境中生成全局最优轨迹的问题,引入滚动窗口优化策略,在研究车辆动力学模型特性的基础上,提出了一种能够同时满足行驶安全和全局最优的动态轨迹规划方法。为保证车辆在行驶过程中轨迹连续平稳,采用六次多项式生成曲率连续的轨迹,并将轨迹规划问题转化为求解单个多项式系数的过程。考虑车辆自身约束以及环境约束对轨迹生成速度的影响,对规划窗口中的障碍物按照度量函数进行分类,并根据最优指标决策出当前规划窗口下的局部最优轨迹和车速。利用Simulink-CarSim搭建了环境模型以及轨迹规划模型,最后通过仿真试验验证了该方法的有效性。

In order to solve the trajectory planning of intelligent vehicle with multi-constraint conditions in unknown environment,a rolling optimization scheme is presented.A feasible trajectory planning method in the local environment is proposed via vehicle dynamic study. With the characteristics of smooth trajectories of six polynomials,the process of trajectory planning is transformed into solving a single polynomial coefficient.The obstacles in the planning window are classified according to the metric function,and the optimal trajectory and vehicle speed are decided according to the optima index.Simulink and CarSim are used to develop the environmental model and the trajectory model.The effectiveness of the planning scheme is verified by simulation study.