基于改进快速行进树的自主代客泊车路径规划

为了加速自主代客泊车系统落地，基于改进快速行进树算法提出了一种自主代客泊车路径规划方法.首先，采用类广度优先搜索策略建立环境地图的“路径场”，并提出一种高计算效率的避障检测策略，基于环境地图“路径场”提出一种符合汽车非完整约束的远端参考点和近端参考点选取原则与路径节点更新原则，通过使路径节点逐渐靠近目标节点来完成自主代客泊车引导路径规划任务. 其次，基于Dubins曲线规划满足初始泊车方位角任意性要求和泊车位方位角的非唯一性要求的泊车路径，引导汽车安全驶入泊车位.最后，仿真验证所提方法的可行性.结果表明：相对于传统的快速行进算法，所提方法规划的自主代客泊车路径满足汽车非完整约束要求，可以安全引导汽车完成自主代客泊车任务.

Autonomous Valet Parking Path Planning Based on Modified Fast Marching Tree

In order to accelerate the landing of the autonomous valet parking system, a novel autonomous valet parking path planning method is proposed based on the improved fast marching tree algorithm. Firstly, a breadth-first-search-like strategy is used to establish the "path field" of the environmental map, and an obstacle avoidance detection strategy with high computational efficiency is proposed. A selection principle of the far and near reference points and an update principle of the path node based on the "path field" of environmental map are proposed to conform to the vehicle non-holonomic constraint. According to the above proposed strategies and principles, the path node is gradually close to the target node to complete the autonomous valet parking guidance path planning task. Then, on the basis of the Dubins curve, the parking path which meets the arbitrary requirement of the initial vehicle parking azimuth and the non-uniqueness requirement of the parking space azimuth angle is planned to guide the vehicle to enter the parking space safely. Finally, the feasibility of the proposed method is verified by simulation, and the results show that when compared with the traditional fast marching algorithm, the planned autonomous valet parking path based on the proposed method meets the requirement of the vehicle non-holonomic constraint and can guide the vehicle to complete the task of autonomous valet parking.