Dijkstra算法
算法
计算机科学
A*搜索算法
最短路径问题
计算
比例(比率)
Suurballe算法
网格
最短路径快速算法
可视化
K最短路径路由
明星(博弈论)
寻路
算法设计
Floyd–Warshall算法
数据挖掘
图形
理论计算机科学
数学
物理
数学分析
几何学
量子力学
作者
Dexin Yu,Luchen Wang,Xincheng Wu,Zhuorui Wang,Jianyu Mao,Xiyang Zhou
摘要
In the real world, traffic scenes are complex and contain intricate road networks, which makes the shortest path computation on large-scale road networks a challenging task. Existing research has concentrated on small-scale urban road networks or grid maps. In practical scenarios, however, we are often faced with seeking the shortest paths on large-scale road networks. For this reason, it is imperative to develop efficient shortest path searching algorithms, as it offers significant savings in time and resources. To tackle this issue, this paper proposes two improved A* algorithms, namely the Weighted A* algorithm and the Bidirectional Weighted A* algorithm. To verify the effectiveness of our proposed algorithms, we validated the performance of our proposed algorithms against the conventional Dijkstra and A* algorithms on urban road networks of different sizes. Our results significantly demonstrate the effectiveness of our solution, as both algorithms significantly outperform Dijkstra's and A* algorithms, with little loss of accuracy.
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