Pedestrian and bicyclist safety is of growing concern, especially given the increasing numbers of urban residents choosing to walk and bike. Sharing the roads with automobiles, these road users are particularly vulnerable. An intuitive conceptual model is proposed of the determinants of injury severity in crashes between vehicles and nonmotorized road users. Using 10 years of crash data from San Francisco, CA, we estimate logistic regression models to illuminate key determinants of crash severity for both pedestrian and bicyclist collisions. The analyses are separated by party at fault to test the novel hypothesis that environmental factors affecting driver speed and reaction time may be especially important when the driver is not at fault. Pedestrian results are broadly consistent with prior research, and offer considerable support for this hypothesis. The strongest predictors of injury severity include pedestrian advanced age, driver sobriety, vehicle type, and a set of variables that help determine driver speed and reaction time. Bicyclist results were weaker overall, and the distinction by party at fault was less important.
Keywords: Bike; Collision; Injury severity; Logit model; Walk.
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