Abstract Purpose A new model based approach for the traffic congestion detection in time series of airborne optical digital camera images is proposed. Methods It is based on the estimation of the average vehicle speed on road segments. The method puts various techniques together: the vehicle detection on road segments by change detection between two images with a short time lag, the usage of a priori information such as road data base, vehicle sizes and road parameters and a simple linear traffic model based on the spacing between vehicles. Results The estimated speed profiles from experimental data acquired by an airborne optical sensor - 3K camera system - coincide well with the reference measurements. Conclusions Experimental results show the great potential of the proposed method for the detection of traffic congestion on highways in along-track scenes.


    Access

    Download


    Export, share and cite



    Title :

    Model based traffic congestion detection in optical remote sensing imagery


    Contributors:

    Published in:

    Publication date :

    2010-04-02


    Size :

    8 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Detection of Traffic Congestion in SAR Imagery

    Palubinskas, Gintautas / Runge, Hartmut | VDE-Verlag | 2008


    Detection of traffic congestion in airborne SAR imagery

    Palubinskas, Gintautas / Runge, Hartmut | Tema Archive | 2007


    TRAFFIC CONGESTION DETECTION DEVICE, TRAFFIC CONGESTION DETECTION SYSTEM, AND TRAFFIC CONGESTION DETECTION METHOD

    ESHITA NAOHIKO / MORIGUCHI TAKUO / TOKUUME SHINYA et al. | European Patent Office | 2022

    Free access

    Improving the Traffic Management System Based on Remote Sensing Data Imagery

    Suharyadi R. / Hidayati Iswari Nur / Upadana Made Dwiyana Surya et al. | DOAJ | 2023

    Free access

    Road congestion degree detection method based on remote sensing communication

    XUE QING | European Patent Office | 2015

    Free access