基于多约束路径算法的大规模道路网络转弯限制最短路径逼近

K. Girish, Sandeep Sarkar, S. Rajagopalan
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引用次数: 5

摘要

多约束路径(Multi-Constrained Path, MCP)算法是一种寻路算法,与传统的路由算法不同,它不仅给出源和目的之间的路径,而且验证该路径是否满足给定的约束(右转、左转和U转)。MCP算法是NPComplete的。MCP算法的目标是在道路网络中寻找满足转弯限制的最短路径,在智能交通系统(ITS)中的路径引导等方面有着广泛的应用。在本文中,道路被认为是节点,路口被认为是边缘,因为这样可以减少需要处理的数据量。输出由可用于到达目的地的路径列表组成。用班加罗尔路网的实际数据对算法进行了测试和分析。结果表明,在执行时间上,MCP算法比传统路由算法的效率提高了84.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approximating Shortest Path in Large-Scale Road Networks with Turn Prohibitions Using Multi-constrained Path Algorithm
Multi-Constrained Path (MCP) algorithms are path finding algorithms, unlike conventional routing algorithms, they not only give a path between source and destination, also verifies whether the path satisfies the given constraints (Right turn, Left turn and U turn). MCP algorithms are NPComplete. The MCP algorithms are aimed to find the shortest path in a road network that satisfies the turn prohibitions and has many applications such as route guidance in Intelligent Transport System (ITS). In this paper, roads are considered as nodes and junctions as edges, as it reduces the amount of data to be processed. The output consists of a list of paths that can be used to reach the destination. The algorithms have be tested and analysed with the real data of Bangalore road network. The results show that the efficiency of MCP is 84.5% better than conventional routing algorithms in terms of execution time.
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