Using K-means algorithm for the road junction time period analysis

Hung-Chi Chu, Chi-Kun Wang
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引用次数: 4

Abstract

Traffic congestion is one of the important issues in developed and developing countries. Due to the rapid development of information communication technology, the use of data mining technology in the intelligent traffic monitoring system has become the current trend of research and development. Use the information collected by the vehicle detector (VD) to analyze the causes of traffic congestion and find a suitable road junction time period classification. The k-means algorithm was used in cluster analysis to group the traffic flow and divide traffic time. According to the more precise analysis, the traffic congestion problem can be solved by the appropriate traffic signal lights cycle arrangements. The experimental result showed that the proposed mechanism can provide a suitable traffic flow classification and can indicate the difference of traffic pattern between weekday and weekend.
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采用K-means算法对道路交叉口时段进行分析
交通拥堵是发达国家和发展中国家面临的重要问题之一。由于信息通信技术的飞速发展,在智能交通监控系统中应用数据挖掘技术已成为当前的研究发展趋势。利用车辆检测器(VD)收集到的信息,分析交通拥堵的原因,找到合适的路口时段分类。聚类分析中采用k-means算法对交通流进行分组和时间划分。根据更精确的分析,可以通过适当的交通信号灯周期安排来解决交通拥堵问题。实验结果表明,所提出的机制能够提供合适的交通流分类,并能反映工作日和周末交通模式的差异。
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