A real-time traffic incident detection algorithm is proposed and applied to the monitoring of a complex road junction in the city of Nancy in France. This algorithm has the potential to provide local monitoring of traffic sensors. The approach is based on macroscopic traffic flow models, and more precisely on the flow-density relationship. Once this relation is extracted from real traffic data, an admissible region is defined in the flow-density space. Then, the classification properties of neural networks are used to design the monitoring network, which detects and isolates the incidents that disturb the traffic, when the measured data are out of the admissible region. A hierarchical scheme to deal with incidents in large-scale networks is developed as well.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Neural networks for local monitoring of traffic magnetic sensors


    Weitere Titelangaben:

    Neuronale Netze für die Überwachung von magnetischen Sensoren in der Verkehrstechnik


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2005


    Format / Umfang :

    14 Seiten, 22 Bilder, 3 Tabellen, 41 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




    Monitoring of traffic networks using mobile sensors

    Zhe Cong / De Schutter, Bart / Burger, Mernout et al. | IEEE | 2014


    Signal conditioning for GMR magnetic sensors. Applied to traffic speed monitoring GMR sensors

    Pelegri Sebastia, Jose / Alberola Lluch, Jorge / Lajara Vizcaino, J. Rafael | Tema Archiv | 2007


    TRAFFIC MONITORING USING OPTICAL SENSORS

    YAN JIN / CHEN QIUSHU / RAGHAVAN AJAY et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    Traffic monitoring using optical sensors

    YU HONG / CHEN QIUSHU / KIESEL PETER et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    TRAFFIC MONITORING USING OPTICAL SENSORS

    YU HONG / CHEN QIUSHU / KIESEL PETER et al. | Europäisches Patentamt | 2023

    Freier Zugriff