交通运输系统工程与信息

交通运输系统工程与信息 ›› 2005, Vol. 5 ›› Issue (1): 62-67 .

• 系统工程理论与方法 • 上一篇    下一篇

基于模糊聚类的快速路交通流状况分类

陈德望
  

  1. 北京交通大学 电子信息工程学院, 北京100044
  • 收稿日期:2004-01-22 修回日期:1900-01-01 出版日期:2005-02-01 发布日期:2005-02-01

Classification of Traffic Flow Situation of
Urban Freeways Based on Fuzzy Clustering

CHEN De-wang
  

  1. School of Electrical and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
  • Received:2004-01-22 Revised:1900-01-01 Online:2005-02-01 Published:2005-02-01

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摘要： 人们对交通流状况的判断常常是比较模糊的,本文根据实测快速路交通流数
据,利用模糊聚类的方法对交通流状况的分类进行了研究,分别把交通流分成了2类、3类和6类.论文对实验结果进行了分析,并给出了适用于北京快速路交通流状况分类的一些关键参数.分析结果表明:用模糊聚类进行交通流状况分类是一种可行的方法;速度对交通流分类的影响最大,其次是占有率,流量的作用最低;除了在速度很高、速度很低或者占有率很大的情况下可直接判断交通流状况,其他情况下需要根据交通流三个变量来综合判断.

关键词: 快速路, 交通流, 模糊聚类, 服务水平 >

Abstract: As the judgment on the situation of traffic flow often is vague, a fuzzy clustering method is used to classify the field traffic flow data of urban freeway in this paper and traffic flow are
classified into 2, 3or 6 categories respectively. Some important parameters about the traffic flow classification are given based on the analysis of the experimental result. The analysis results show that using fuzzy clustering to classify the traffic flow is feasible; of the three traffic flow parameters, speed have the greatest influence on the traffic flow classification, occupancy the second, flowthe least; unless in the situation with very high speed, very low speed or very high occupancy, the right
judgment of traffic flow situation can given directly, we should judge comprehensively according to the all three traffic flowv ariables.

Key words: urban freeway, traffic flow, fuzzy clustering, level of service