• DocumentCode
    3730368
  • Title

    Fuzzy c-means clustering identification method of urban road traffic state

  • Author

    Guangyu Zhu; Jianjun Chen; Peng Zhang

  • Author_Institution
    MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, China 100044
  • fYear
    2015
  • Firstpage
    302
  • Lastpage
    307
  • Abstract
    Urban road state identification refers to determining the operation status of the road network system, which plays an important role in urban road traffic management. By clustering time series of traffic flow, typical fluctuation pattern recognize algorithms of traffic flow can get the urban road network operation states. As the detected traffic data contain vague and uncertain information, preprocessing is needed. An improved fuzzy c-means clustering (FCM) method is proposed in this paper. A case study based on urban road section of Beijing City demonstrates the feasibility and effectiveness of the improved FCM algorithm.
  • Keywords
    "Clustering algorithms","Roads","Algorithm design and analysis","Indexes","Classification algorithms","Linear programming"
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on
  • Type

    conf

  • DOI
    10.1109/FSKD.2015.7381958
  • Filename
    7381958