In this paper, risk level correlation and classification using belief functions based on driving activities’ data about sharp transient maneuvering tasks, legal speed exceeding, and average speed ensuing with the human being who is controlling the technical system, i.e., the car, is presented. A dataset is constituted by time stamped and geographically referenced driving maneuver information, which is exceptionally reported when an acceleration exceeds the given threshold in both longitudinal and lateral direction. Risk level is labeled in terms of the change in total vehicle collision property damage cost for the analyzed time period, and long term driving activities’ magnitude and frequency is divided into two equal time periods, which are used to predict risk levels. Redistribution of conflicts generated by driving activities is used to predict the future risk level of involvement in an accident. Using fuzzy approach a microaveraged F-measure 90.98% is achieved by Dubois–Parade and PCR6 conflict redistribution methods.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Prediction of Risk Generated by Different Driving Patterns and Their Conflict Redistribution


    Beteiligte:
    Gunduz, Gultekin (Autor:in) / Yaman, Cagdas (Autor:in) / Peker, Ali Ufuk (Autor:in) / Acarman, Tankut (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2018-03-01


    Format / Umfang :

    849405 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Comparative analysis on information fusion conflict redistribution and driving risk classification

    Gunduz, Gultekin / Yaman, Cagdas / Peker, Ali Ufuk et al. | IEEE | 2017



    Automating Conflict Prediction

    Alleyne, T. A. / Elder, C. E. / Sotirovski, D. et al. | British Library Conference Proceedings | 1995



    Aircraft taxiing scheduling method based on taxiing conflict risk prediction

    LIAN GUAN / WANG YUANSHUN / XING ZHIWEI et al. | Europäisches Patentamt | 2022

    Freier Zugriff