Applying the current technological possibilities has led to a wide range of traffic monitoring systems. These heterogeneous data sources individually provide a view on the current traffic state, each source having its own properties and (dis)advantages. However, these different sources can be aggregated to create a single traffic state estimation. This paper presents a data fusion algorithm that combines data on the data sample level. The proposed system fuses floating car data with stationary detector data and was implemented on live traffic. Results show the fusion algorithm allows to eliminate individual source bias and alleviates source-specific limitations.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Real-time traffic monitoring by fusing floating car data with stationary detector data


    Beteiligte:


    Erscheinungsdatum :

    01.06.2015


    Format / Umfang :

    2341154 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Fusing a Bluetooth Traffic Monitoring System With Loop Detector Data for Improved Freeway Traffic Speed Estimation

    Bachmann, Chris / Roorda, Matthew J. / Abdulhai, Baher et al. | Taylor & Francis Verlag | 2013



    Traffic time series data anomaly detection method fusing multiple mechanisms

    LI YUFENG / LIU JIAQI / HUANG JINYUAN et al. | Europäisches Patentamt | 2025

    Freier Zugriff

    Traffic Estimation And Prediction Based On Real Time Floating Car Data

    de Fabritiis, Corrado / Ragona, Roberto / Valenti, Gaetano | IEEE | 2008