Abstract
This study aims to rank high crash risk areas and measure the impacts of accessibility and other spatial and socio-economic factors on county-level crash severities while controlling for spatial and temporal unobserved effects. Among other insights, the results suggest that primary roadway density is positively associated with all crash severities. Contrary, intersection density is negatively associated with injury and no injury crashes. Furthermore, school density and rates of driving under the influence are both positively associated with no injury crashes. Additionally, the mean travel time to the hospital is positively associated, while urbanity is negatively associated with fatal crashes. Unobserved effects due to unstructured random effect terms are significant and contribute to the model’s overall goodness of fit. The within-area correlation among crash severities is positive and non-negligible. From a temporal perspective, both fatal and no injury crashes have decreasing trends. However, no clear pattern for injury crashes is observed across the years. From a spatial perspective, extreme high and low crash risk counties are identified throughout the study area with no clear observed patterns of clustering or dispersion.
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