Identifying factors explaining pedestrian crash severity : a study of Austin, Texas
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From the Federal Highway Administration to local departments of transportation, traffic safety is a persistent concern for transportation planners and engineers. Pedestrians are among the most vulnerable road users and require consideration beyond typical analysis of vehicle safety. This study has two objectives: to identify environmental, demographic, and behavioral factors explaining crash severity, and to compare methods for determining the significance of these factors. Binary and ordered logistic regression models were developed and compared to assess factor significance. Environmental and local factors, such as lighting and speed limit, had the strongest correlation with crash severity in all cases. However, inclusion of driver and pedestrian behavior and demographic characteristics improved the fit of the model and, in some cases, predictive ability. The two model types identified the same significant variables in traffic safety, but the magnitudes of the effects differed by model. This finding demonstrates that while the simpler method may yield the same overall results, combining methods can differentiate factors which contribute to the most severe crashes.