利用Dijkstra算法和谷歌地图确定旅行时间和最快路线

Suardinata Suardinata, Rusdisal Rusmi, Muhammad Amrin Lubis
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引用次数: 2

摘要

Dijkstra算法通常用于确定将一个点作为开始节点连接到另一个点作为结束节点的最短路径。在本研究中,以UNP学生宿舍作为起始节点,以学生经常访问的图书馆作为结束节点。由于学生一般都住在校园附近,步行出行,所以需要另一条路线来确定最快的出行时间。因此,本研究的目的是利用Dijkstra算法,对比谷歌地图显示的路线,确定从节点的起点到终点的行驶时间最快的路线。数据来自谷歌地图,它显示了许多路线的可用性,学生可以用最快的旅行时间。结果表明,使用Dijkstra算法和Google Map的最快路线分别为14条和3条,间隔15分钟和21分钟。根据这些数据得出结论,使用Dijkstra算法获得的最快路线的旅行时间比在谷歌地图上找到的数据快6分钟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determining Travel Time and Fastest Route Using Dijkstra Algorithm and Google Map
Dijkstra's algorithm is commonly used to determine the shortest route connecting a point as a starting node to another which acts as the end node. In this study, the UNP student dormitory acted as the starting node, while the library which is frequently visited by students was sampled from the campus as the end node. Due to the fact that students generally live around campus and move on foot, an alternative route is needed to determine the fastest travel time. Therefore, this study aims to determine the route with the fastest travel time from the start to the end of nodes using the Dijkstra algorithm, in comparison with the route displayed by Google Map. Data were obtained from Google Map, which showed the availability of many routes with the possibility of students taking the fastest travel time. The result showed that the fastest route using the Dijkstra algorithm and Google Map were 14 and 3 alternatives at 15 and 21 minutes intervals. Based on these data, it is concluded that the travel time through the fastest route obtained using the Dijkstra algorithm was 6 minutes faster than data found in the Google Map.
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