Abstract The paper proposes an automatic traffic accident detection algorithm for the urban expressway. The algorithm is established on longitudinal time series theory based on catastrophe theory and statistics theory. The results: (1) the lengthways time series of traffic parameters data manifests a good stability than the transverse time series and it can detect accident when the losing data are more; (2) no matter what traffic flow stats are, the model can detect accident accurately. The model developed in the study can be directly used by traffic engineers and managers to detect traffic accident.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Automated Detection Algorithm for Traffic Incident in Urban Expressway Based on Lengthways Time Series


    Beteiligte:
    Li, Hong-wei (Autor:in) / Li, Su-lan (Autor:in) / Zhu, Hong-wei (Autor:in) / Zhao, Xing (Autor:in) / Zhang, Xiaoli (Autor:in)


    Erscheinungsdatum :

    16.09.2018


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Automated Detection Algorithm for Traffic Incident in Urban Expressway Based on Lengthways Time Series

    Li, Hong-wei / Li, Su-lan / Zhu, Hong-wei et al. | British Library Conference Proceedings | 2019


    Urban Expressway Incident Detection Algorithm Based on Floating Car Data

    Zhao, X. / Weng, J.-C. / Rong, J. et al. | British Library Conference Proceedings | 2010




    Modelling Incident Duration on an Urban Expressway

    Cohen, S. / Nouveliere, C. / Technical University of Crete; Department of Production and Management Engineering | British Library Conference Proceedings | 1997