A wide array of literature strongly indicates a higher likelihood of roadway departure because of cellphone use; however, patterns of associative attributes in single-vehicle run-off-road (SVROR) crashes because of cellphone distraction remained unexplored. Using the association rule mining (ARM) method, this study aimed to identify the variable categories that concurrently occur in such crashes, visualize the structures representing those concurrent associations, and discuss the crash patterns associated with different severity types. The SVROR crashes with cellphone use by the driver at fault were highlighted to be strongly connected to non-usage of safety restraints, weekends, both lighted and unlighted dark conditions, two-lane highways without physical separation, roadway curves, and so forth. Alongside several attributes, non-usage of restraints was strongly associated with fatal and both incapacitating and non-incapacitating injury crashes. The findings of this study can benefit the determination of suitable countermeasures to prevent cellphone-related SVROR crashes.


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    Titel :

    Single-Vehicle Run-Off Road Crashes Because of Cellphone Distraction: Finding Patterns with Rule Mining


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Rahman, M. Ashifur (Autor:in) / Das, Subasish (Autor:in) / Sun, Xiaoduan (Autor:in)


    Erscheinungsdatum :

    09.09.2022




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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