Route selection based on real time traffic condition using Ant Colony System and fuzzy inference system

Erick Alfons Lisangan, Sean Coonery Sumarta
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引用次数: 5

Abstract

Route selection from the point of origin to destination today is not only considering the shortest distance but also traffic conditions, such as average speed and vehicle intensity. In this research, we propose method of the ant's location selection using Fuzzy Inference System in the Ant Colony System. The location selection not only consider the distance but also the probability of next location. The probability of next location is the output of fuzzy inference system with the input is the traffic conditions between current location and next location. The dataset is data of traffic condition in the area of Aarhus, Denmark. The results show that the route selection is not only based on the distance location but also the traffic condition between locations. The proposed method is expected to be the basis to develop the real-time location searching's application with input coming from sensors by considering the average execution less than one second in finding route.
利用蚁群系统和模糊推理系统进行基于实时交通状况的路径选择
如今,从起点到目的地的路线选择不仅要考虑最短距离,还要考虑交通状况,如平均速度和车辆强度。在本研究中,我们提出了在蚁群系统中利用模糊推理系统进行蚁群选址的方法。位置选择不仅考虑了距离,而且考虑了下一个位置的概率。下一个位置的概率是模糊推理系统的输出,输入是当前位置与下一个位置之间的交通状况。该数据集是丹麦奥胡斯地区的交通状况数据。结果表明,路径选择不仅要考虑距离位置,而且要考虑位置之间的交通状况。考虑到寻路的平均执行时间小于1秒,该方法有望成为开发传感器输入实时定位搜索应用的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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