Motorcycle crash is considered as one of the critical safety issues. This study targets to examine the role of geometric design and other factors that contribute to the decision-making of motorcyclists, such as speeding, which could potentially result in a crash. This study analyzed Louisiana crash data from 2010 to 2016 to determine the patterns associated with speeding-related motorcycle crashes. The collected data contained information regarding crash characteristics and circumstances, characteristics of vehicles and drivers, crash locations, roadway types, traffic volume, segment length, and other relevant geometric information. This study employed a relatively new categorical data analysis method, which combines cluster and correspondence analysis. This study identified several high-risk scenarios in which a speeding-related motorcycle crash is more likely to occur through interactions with other related factors. The recommendations on the countermeasures can be used as a resource for policymakers to reduce speeding associated motorcycle crashes in Louisiana.


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    Titel :

    Pattern recognition in speeding related motorcycle crashes


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    04.07.2022


    Format / Umfang :

    18 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt





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