Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Factors Influencing the Severity of Crashes Caused by Motorcyclists: Analysis of Data from Alabama
The number of motorcycle crashes in Alabama more than doubled from 1999 to 2008, while the number of fatal motorcycle crashes tripled during the same period. Most work on motorcycle crash severity has been based on analysis of all crashes involving motorcycles. The majority of motorcycle crashes in Alabama are cause by the motorcyclist. An analysis of factors affecting the injury severity outcome of motorcycle causal crashes is presented. The analysis uses a multinomial logit (MNL) regression model to examine 5 years (2006 to 2010) of crash data. The variables affecting motorcycle crashes were grouped by common characteristics into four categories: motorcyclist, crash, environment, and roadway. Average direct pseudoelasticities were obtained to interpret the factors influencing motorcyclist-caused crashes (MCCs) severity. With some 70% of motorcycles crashes in Alabama resulting in some type of injury, there is potential for positive impact on safety from policies and programs that address the behavior-related crashes identified in this study. In addition to reducing behaviors considered as aggressive, it would appear that considerable safety benefit could be derived from efforts to alter motorcyclist behavior in the vicinity of large vehicles, around roadway curves, and in rural areas.
Factors Influencing the Severity of Crashes Caused by Motorcyclists: Analysis of Data from Alabama
The number of motorcycle crashes in Alabama more than doubled from 1999 to 2008, while the number of fatal motorcycle crashes tripled during the same period. Most work on motorcycle crash severity has been based on analysis of all crashes involving motorcycles. The majority of motorcycle crashes in Alabama are cause by the motorcyclist. An analysis of factors affecting the injury severity outcome of motorcycle causal crashes is presented. The analysis uses a multinomial logit (MNL) regression model to examine 5 years (2006 to 2010) of crash data. The variables affecting motorcycle crashes were grouped by common characteristics into four categories: motorcyclist, crash, environment, and roadway. Average direct pseudoelasticities were obtained to interpret the factors influencing motorcyclist-caused crashes (MCCs) severity. With some 70% of motorcycles crashes in Alabama resulting in some type of injury, there is potential for positive impact on safety from policies and programs that address the behavior-related crashes identified in this study. In addition to reducing behaviors considered as aggressive, it would appear that considerable safety benefit could be derived from efforts to alter motorcyclist behavior in the vicinity of large vehicles, around roadway curves, and in rural areas.
Factors Influencing the Severity of Crashes Caused by Motorcyclists: Analysis of Data from Alabama
Jones, Steven (Autor:in) / Gurupackiam, Saravanan (Autor:in) / Walsh, Joe (Autor:in)
Journal of Transportation Engineering ; 139 ; 949-956
04.05.2013
82013-01-01 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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