Investigating effective freeway service area inbound vehicles will help manage the local traffic flow and improve the layout and service capacity of the freeway service area facilities. For the freeway service area with no detecting devices, two new methods are proposed by using vehicles’ RFID (Radio Frequency Identification) data from freeway upstream and downstream roadside collecting units. The GMM-EM based method is proposed to obtain the probability distribution of the speed of passing vehicles. Using the Ant Colony Algorithm, the speed threshold for distinguishing vehicles entering or not entering the service area is gained. Then the variational inference Gaussian mixture clustering algorithm is established to determine whether the vehicle drives into the freeway service area. Using RFID data of vehicles from the Chongqing Freeway in China, the experimental results show that the average accuracy of distinguishing freeway service area inbound vehicles is more than 96%.


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    Title :

    A Novel Identification Method of Vehicle Inbound Freeway Service Area Using RFID Data


    Contributors:
    Sun, Dihua (author) / Wei, Quan (author) / Tian, Yudan (author) / Huang, Shuai (author) / Zhao, Min (author) / Wu, Xiao (author)

    Conference:

    22nd COTA International Conference of Transportation Professionals ; 2022 ; Changsha, Hunan Province, China


    Published in:

    CICTP 2022 ; 80-90


    Publication date :

    2022-09-08




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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