This paper aims at assessing and identifying a fatal injury risk model with an exponential structure for the accidents that occur in rainy conditions, based on highly disaggregated level of data. A probabilistic approach is used in order to assess the fatal risk as a function of probability and accidents’ consequences, based on 14 types of predictors that relate to road environment, time of accidents and lighting conditions. The influence of circadian rhythms on the drivers’ behavior is taken into consideration by setting up the accidents’ time intervals based on the “black time”. The Adjusted Bayesian Information Criterion (BIC’) is used to further test the fit of probability model in a comprehensive way and the risk distributions are described using their descriptive parameters. The highways are most dangerous during rains, since the odds for a fatal accident are 3.340 times higher than on streets. Also, the odds for those accidents that occurred between 02:00 ∼ 04:59 are 1.624 times higher than between 16:00 ∼ 20:59. This paper demonstrates that the quality of the roadways is important since there are 2.574 times higher odds for an accident to be fatal where the roadway has potholes compared with a normal pavement.


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    Titel :

    Fatal Injury Risk Model (FIRM) of the Road Accidents that Occurred in Rainy Conditions — A Probabilistic Approach


    Weitere Titelangaben:

    Int.J Automot. Technol.


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2021-10-01


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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