Threshold Value Based Traffic Congestion Identification Method

نویسندگان

  • Zhanquan Sun
  • Weidong Gu
  • Jinqiao Feng
  • Xiaomin Zhu
چکیده

Traffic congestion identification is a popular research topic of Intelligent Transportation System (ITS). Many identification methods, such as threshold value based methods, California, McMaster method and so on, have been studied. But the threshold values of these methods are difficult to be determined. A novel threshold value based traffic congestion identification method is proposed in this paper. In the method, traffic flow parameters are divided into sections according to threshold values that are determineded with mutual information maximization theory. Congestion identification rules are extracted with decision tree. At last, the efficiency of the proposed method is illustrated through analyzing Jinan urban transportation data.

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تاریخ انتشار 2011