Dangerous driving events data are widely used as surrogates to traffic crashes. Large-scale dangerous driving events data collected from smartphones are explored in this study. Clustering analysis is performed on dangerous driving events counted in spatial cells. Spatial and temporal patterns of the cluster distributions are then explored. Both the existence of spatial autocorrelation and the similarity of cluster distributions for different time periods are uncovered.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Exploring Spatial and Temporal Patterns of Large-scale Smartphone-based Dangerous Driving Event Data*


    Beteiligte:
    Yang, Di (Autor:in) / Xie, Kun (Autor:in) / Ozbay, Kaan (Autor:in) / Yang, Hong (Autor:in)


    Erscheinungsdatum :

    2019-10-01


    Format / Umfang :

    496606 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Dangerous driving behavior detection using smartphone sensors

    Fu Li, / Hai Zhang, / Huan Che, et al. | IEEE | 2016


    DANGEROUS DRIVING EVENT REPORTING

    STENNETH LEON / MODICA LEO | Europäisches Patentamt | 2020

    Freier Zugriff

    Dangerous driving event reporting

    STENNETH LEON / MODICA LEO | Europäisches Patentamt | 2020

    Freier Zugriff

    Dangerous Driving Event Reporting

    STENNETH LEON / MODICA LEO | Europäisches Patentamt | 2015

    Freier Zugriff