AbstractUsing a comprehensive database of police-reported accidents in Hawaii, we describe the nature of pedestrian accidents over the period 2002–2005. Approximately 36% of the accidents occur in residential areas, while another 34% occur in business areas. Only 41.7% of the pedestrian accidents occur at intersections. More pedestrian crashes occur at non-intersection locations—including midblock locations, driveways, parking lots, and other off roadway locations. Approximately 38.2% of the crashes occur at crosswalk locations, while proportionately more (61.8%) of the pedestrian accidents occur at non-crosswalk locations. Using this database the human, temporal, roadway, and environmental factors associated with being “at-fault” for both pedestrians and drivers are also examined. Using techniques of logistic regression, several different explanatory models are constructed, to identify the factors associated with crashes producing fatalities and serious injuries. Finally, two pedestrian models (drunk males and young boys) and one driver model (male commuters) are developed to provide further understanding of pedestrian accident causation. Drunk male pedestrians who were jaywalking were in excess of 10× more likely than other groups to be at-fault in pedestrian accidents. Young boys in residential areas were also more likely to be at-fault. Male commuters in business areas in the morning were also found to have higher odds of being classified at-fault when involved in pedestrian accidents. The results of this study indicate that there should be a combination of enforcement and educational programs implemented for both the pedestrian and drivers to show those at-fault the consequences of their actions, and to reduce the overall number of accidents.


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    Title :

    Modeling fault among accident—Involved pedestrians and motorists in Hawaii


    Contributors:

    Published in:

    Publication date :

    2008-08-14


    Size :

    7 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






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