Journal of South China University of Technology (Natural Science Edition) ›› 2014, Vol. 42 ›› Issue (12): 51-57,76.doi: 10.3969/j.issn.1000-565X.2014.12.008

• Traffic & Transportation Engineering • Previous Articles     Next Articles

Freeway Traffic State Identification Based onToll Data

Yang Qing-fang1,2 Ma Ming-hui2 Liang Shi-dong2 Mei Duo2   

  1. 1.State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130022,Jilin,China;2.College of Traffic,Jilin University,Changchun 130022,Jilin,China
  • Received:2014-05-04 Revised:2014-08-10 Online:2014-12-25 Published:2014-11-17
  • Contact: 杨庆芳(1966-)，女，教授，博士生导师，主要从事智能交通运输系统研究． E-mail: yangqf@jlu.edu.cn
  • About author:杨庆芳(1966-)，女，教授，博士生导师，主要从事智能交通运输系统研究．
  • Supported by:

    国家科技支撑计划项目(2014BAG03B03);山东省省管企业科技创新项目(20122150251-5)

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Abstract:

Current freeway traffic data resources have not been fully utilized,and therefore the freeway toll systemwith high management and construction costs only has such primary functions as collecting traffic information vehiclerecord and network toll,which leads to a great waste of traffic data resources.In order to solve this problem,atravel time estimation method is designed based on freeway network toll data,and the FCM(Fuzzy C-Means)cluste-ring method is adopted to identify the freeway traffic state according to the velocity changes of big and small vehi-cles.Then,the two methods are verified on the VISSIM platform.The results show that the first method can obtainhigh-quality link travel time data and the second method can accurately identify the freeway traffic state,whichhelps to update history data and can provide an accurate basis for freeway management departments to make deci-sions.

Key words: freeway, fuzzy C-means, network toll, travel time, traffic state

CLC Number: