Abstract

Economic factors are assumed to have substantial effects on transportation crash trends. This study makes a comprehensive examination of the relationship between the retail gasoline price, and fatal traffic crashes from 2007 to 2016 in the U.S. Random effect negative binomial (RENB) regression models are used to investigate the relationship while controlling for the other effective factors. This is achieved by developing appropriate crash prediction models. Based on the role of gender and rider's transportation mode in interpreting the prediction results, seven models are developed to investigate the relationship between the inflation adjusted gasoline price and the number of fatal crashes in male, female, motorcyclist, non-motorcyclist, bicyclist, pedestrian, and total groups. Our findings suggest that increasing gasoline prices will not significantly alter the number of total fatal crashes. On the other hand, it is estimated that a one-dollar increase in adjusted gasoline price is associated with a 24.4% increase in the number of fatal motorcycle crashes (p-value = 3.7e-14), a 1.9% decrease in the number of fatal non-motorcycle crashes (p-value = 0.02), and a 8% decrease in the number of fatal pedestrian crashes (p-value = 0.08). There is no noticeable difference between males and females in response to the gasoline price changes.

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