In this paper, risk level correlation and classification based on the recorded driving activities' data about sharp maneuvering tasks ensuing with the human being who is controlling the technical system, i.e., the car, in traffic is presented. The dataset is constituted by time stamped and geographically referenced driving maneuver information, which is exceptionally occurring when exceeding a given threshold acceleration in both longitudinal and lateral direction and a speed limit given as the static attribute of the road map data. Ground truth risk level is identified in terms of the change in vehicle collision property damage cost for the analyzed time period. Distribution of conflict masses generated by harsh driving activities and overspeeding is studied in order to predict the risk level about making an accident. High risk group is identified by PCR6 method with a level of accuracy of 80%.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Comparative analysis on information fusion conflict redistribution and driving risk classification


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


    Erscheinungsdatum :

    2017-10-01


    Format / Umfang :

    177929 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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

    Gunduz, Gultekin / Yaman, Cagdas / Peker, Ali Ufuk et al. | IEEE | 2018


    Refined Weighted Fusion Recognition Method for High Conflict Information

    Zhang, Xuxia / Pan, Xiangyu / Zhu, Huanna | Springer Verlag | 2022


    - Pedestrian-Vehicle Conflict Risk Analysis System

    Europäisches Patentamt | 2019

    Freier Zugriff

    - Pedestrian-Vehicle Conflict Risk Analysis System

    SONG JEONG SEOB / LEE HYEON SOO / LEE HYUN MI et al. | Europäisches Patentamt | 2018

    Freier Zugriff