Traffic state identification is an important part in real-time traffic management and intelligent transportation systems (ITS) applications, which is conventionally based on the available single dataset from traffic sensors such as loop detector, microwave detector, video camera, Bluetooth detector, etc. An accurate profile of the traffic state on highway corridor in terms of speed and density is expected to be a critical factor for supporting traffic management measures. Data fusion techniques are nowadays applied to ITS to improve efficiency and safety of highways. As more and more ETC and DSRC data can be obtained, a method of analyzing traffic status with the datasets gained from ETC via DSRC is expected. In this paper, the DSRC was firstly large scaled installed and applied as a traffic detector along Jingcheng Highway, and the data from DSRC based detector and tolling data were used to identify the traffic state along this corridor. A data fusion method was developed in order to consider both space and time effects was proposed. The results indicated that the DSRC detector could be a promising way to collect traffic data and represent the traffic state on the network with ETC data.


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    Titel :

    A Study on Highway Corridor Traffic State Identification Based on Data Fusion of DSRC Data and ETC Data


    Beteiligte:
    Zhang, Fan (Autor:in) / Niu, Shuyun (Autor:in) / Gao, Jian (Autor:in) / Mermygka, Marianthi (Autor:in)

    Kongress:

    17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China


    Erschienen in:

    CICTP 2017 ; 2712-2724


    Erscheinungsdatum :

    2018-01-18




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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