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HAS: Hierarchical A-Star Algorithm for Big Map Navigation in Special Areas

机译:HAS:用于特殊区域的大地图导航的分层A星算法

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摘要

The problem of path-finding has to be solved in transportation, city planning, commercial computer games, navigation and many other fields. How to find the shortest path is the key point of this problem. For computer games and many other fields, since the maps are usually not very big, traditional algorithms such as Dijkstra algorithm and AStar algorithm work well. But if we want to find the shortest path of two points in a big city or even a country, the memory and CPU resources are limited and these algorithms may result in bad performance. To solve the problem of navigation in big maps, this paper introduces and analyzes the use of Hierarchical A-Star algorithm which adds the hierarchical mechanism into traditional A-Star algorithm and save the resources of CPU and memory. For a big map such as the map of a country, to find the shortest path of two points, we successively divide the map of the country into maps of states, cities, towns, and blocks. Then we implement A Star algorithm for each layer and recursively find the shortest path of these two points.
机译:寻路问题必须在交通,城市规划,商业计算机游戏,导航和许多其他领域中解决。如何找到最短路径是此问题的关键。对于计算机游戏和许多其他领域,由于地图通常不是很大,因此传统算法(例如Dijkstra算法和AStar算法)效果很好。但是,如果我们想在大城市甚至一个国家中找到两点的最短路径,则内存和CPU资源是有限的,这些算法可能会导致性能下降。为了解决大地图中的导航问题,本文介绍并分析了分层A-Star算法的使用,该分层A-Star算法在传统的A-Star算法中增加了分层机制,节省了CPU和内存的资源。对于诸如国家地图的大地图,要找到两点的最短路径,我们先将国家地图划分为州,城市,城镇和街区的地图。然后,我们对每一层实施A Star算法,然后递归找到这两点的最短路径。

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