Based on the RTMS (Remote Traffic Microwave Sensor) data, FCD (floating car data) and plate number data collected from urban expressway, a travel speed estimation method based on BP (back-propagation) neural network is presented in this study. According to the spatial and temporal characteristics of traffic data, three kinds of data complement methods are respectively presented first, and then six data fusion models are established for each data missing and complement status. The input data includes average travel speed from FCD and traffic volume, spot speed, time occupancy rate from RTMS, and the output is the average travel speed estimation. In the model training phase, the travel speed calculated from plate number data is viewed as the real value. Finally, the models are examined by realistic traffic data with two evaluation indicators. The result shows that the fusion models can provide more effective and more accurate traffic information.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Study on Data Fusion Model with Multi-Source Heterogeneous Traffic Data


    Beteiligte:
    Qiu, Feng-cui (Autor:in) / Yao, En-jian (Autor:in) / Yang, Yang (Autor:in) / Li, Xin (Autor:in) / Zhang, Yi (Autor:in)

    Kongress:

    First International Conference on Transportation Information and Safety (ICTIS) ; 2011 ; Wuhan, China


    Erschienen in:

    ICTIS 2011 ; 1462-1468


    Erscheinungsdatum :

    16.06.2011




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Distributed multi-source heterogeneous traffic data fusion method and device

    HE SHUXIAN / CHEN LIN / REN XUEFENG et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Traffic management system based on multi-source heterogeneous data fusion technology

    ZHANG YIBO | Europäisches Patentamt | 2021

    Freier Zugriff

    Key Data Source Identification Method Based on Multi-Source Traffic Data Fusion

    Li, Shuo / Zhang, Mengmeng / Chen, Yongheng | ASCE | 2020


    Multi-source data fusion system in urban traffic big data processing

    SHI LITING / WU CHEN | Europäisches Patentamt | 2021

    Freier Zugriff

    Traffic control approach based on multi‐source data fusion

    Wang, Pu / Wang, Chengcheng / Lai, Jiyu et al. | Wiley | 2019

    Freier Zugriff