基于 A* 算法与自适应分片的大规模最优路径规划
Large Scale Route Planning A* Algorithm Based on Self-Adaptive Hierarchy Method
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摘要: 路径规划引擎是在线地图系统中一个至关重要的部分, 静态路径规划算法是重中之重。现有的对 A* 算法的改进主要是通过预处理算法, 对路网数据进行静态分层预处理, 其效率过低。文章提出了一种自适应分层的思想, 同时对 A* 算法的启发式函数进行改进, 引入了方向引导函数, 使得 A* 算法在日常路网上的可用性有了较大的提高。实际的路网实验表明, 提出的算法的搜索效率、效果均优于同类算法, 与标准层次 A* 算法相比, 文章算法的搜索空间降低为原来的 42%, 搜索时间仅为原来的13%。Abstract: The route planning engine has already become an important part for an online map system. The route planning algorithm is the key for the engine. The existing improvements for A* algorithm are mainly on the preprocessing part in which the roadmap data were layered statically. In this paper, an adaptive hierarchical method was proposed with an improved heuristic function which has goal-direction process. It greatly improves the efficiency and usability of A* algorithm in the engineering road planning system. The experiment result shows that the algorithm takes up only 42% of the search space and 13% of the search time when compared with the general A* algorithm.