More than 30% of cellphone-distracted fatal crashes occurred to drivers younger than 25-years-old in 2018, even though they constitute less than 12% of total licensed drivers in the U.S. Using joint correspondence analysis (JCA), this study analyzed six years (2014–2019) of cellphone-related fatal crashes involving young drivers based on the data from the Fatality Analysis Reporting System (FARS). This unsupervised learning algorithm can graphically display the co-occurrence of variable categories in a lower-dimensional space by effectively summarizing the knowledge of a complex crash dataset. The Boruta algorithm was applied to select the relevant features from the preliminary crash dataset. The empirical results of JCA manifest a few interesting fatal crash patterns. For example, young male drivers in light trucks were involved in deadly collisions while performing specific cellphone activities (other than talking and listening), cellphone-related fatal crashes occurred to young females with prior crash records, and so on. Apart from alcohol and drug involvement, this study identified young drivers’ additional risk-taking maneuvers while engaged in cellphone usage, including: disregarding traffic signs and signals, speeding, and unrestrained driving. The associations could guide the safety officials and policymakers in developing appropriate engineering, education, and enforcement strategies when dealing with cellphone-distracted young drivers.


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    Titel :

    Young drivers and cellphone distraction: Pattern recognition from fatal crashes


    Beteiligte:
    Hossain, Md Mahmud (Autor:in) / Zhou, Huaguo (Autor:in) / Das, Subasish (Autor:in) / Sun, Xiaoduan (Autor:in) / Hossain, Ahmed (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    04.03.2023


    Format / Umfang :

    26 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt