Exploring the determinants of pedestrian-vehicle crash severity in New York City.

Pedestrian-vehicle crashes remain a major concern in New York City due to high percentage of fatalities. This study develops random parameter logit models for explaining pedestrian injury severity levels of New York City accounting for unobserved heterogeneity in the population and across the boroughs. A log-likelihood ratio test for joint model suitability suggests that separate models for each of the boroughs should be estimated. Among many variables, road characteristics (e.g., number of lanes, grade, light condition, road surface, etc.), traffic attributes (e.g., presence of signal control, type of vehicle, etc.), and land use (e.g., parking facilities, commercial and industrial land use, etc.) are found to be statistically significant in the estimated model. The study also suggests that the set of counter measures should be different for different boroughs in the New York City and the priority ranks of countermeasures should be different as well.