Despite the zero tolerance and minimum legal drinking age laws since 1999, crashes caused by underage drinking drivers have occurred every year in the United States, which is a huge cause for concern for roadway safety. This study utilized multiple correspondence analysis (MCA) on 9 years (2010 to 2018) of at-fault, underage (aged 15 to 20 years), alcohol-intoxicated driver crashes in Louisiana to investigate hidden crash attribute patterns. This exploratory multivariate analysis technique identifies systematic associations among categories of qualitative variables rather than recognizing the effect of a single factor on the response variable. The results exhibited the capability of MCA in discovering the meaningful clouds of crash contributory factors from a complex multidimensional dataset. Fatal crashes happened to underage alcohol-intoxicated drivers who were not using seatbelts on high-speed curve segments under dark without streetlights, whereas single-vehicle crashes resulted in moderate injuries among drinking novice teenagers operating light trucks. The findings also revealed the driving behavior patterns of rookie drivers after alcohol intake that resulted in collisions. For example, male teenagers were engaged in impaired driving during weekends under adverse weather conditions, and underage drinking drivers tended to use cellphones during late-night driving. Targeting critical attributes identified from associations could be helpful in reducing the number of related crashes and fatalities. Furthermore, knowledge gained about the attribute groups identified in this study could be included in educational training programs targeting risky driving maneuvers. Integration of multiple interventions could be more strategic in minimizing underage drinking collisions.


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    Title :

    Investigating Underage Alcohol-Intoxicated Driver Crash Patterns in Louisiana


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2021-07-07




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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