基于改进A^*算法的一种智能车路径规划方法

Intelligent Vehicle Trajectory Planning Based on Improved Genetic Algorithm

轨迹规划是智能车安全行驶的关键技术。基于A^*算法在复杂地图轨迹规划耗时长、拐点多等问题,提出了一种基于图论及几何方法的改进A^*算法的避障与导航方法。该方法在传统A^*算法的基础上结合图论进行路径规划,同时剔除路径中冗余节点,并采用Labview进行具体的仿真实验来验证轨迹规划算法的性能。结果表明:该改进算法在复杂环境中仍能有效找到距离短且平滑路径,提高了智能车的运行效率降低了能耗,可用于实际的智能车安全行驶管理中。

Trajectory planning is the key safe driving technology of intelligent vehicle.To solve the problems of long time consuming and many inflection points in the A^*algorithm during complex map trajectory planning,an improved A^*algorithm proposed in graph theory and geometric method.The improved algorithm was combined with the traditional one,the redundant nodes were eliminated,and the performance of the trajectory-planning algorithm was verified in simulation experiments.The results show that the shortest distance and smoothest path can be found effectively in a complex environment using the improved algorithm,which enhances the running efficiency of the intelligent vehicle and reduced the energy cost,thus it can be used in the actual safe driving management of intelligent vehicles.