Abstract by Kaitlin Gibson
Identifying Crash Risk Factors on an Interstate Network
Highway safety improvement projects are identified by using either (i) a site-specific or (ii) a systemic approach. In the site-specific approach, locations for improvements are ranked according to the mean number of crashes at the site or the potential for improvement. Alternatively, in the systemic approach, roadway characteristics such as speed limit, shoulder width, etc. are flagged as either a “risk” (or “preventative”) feature that increases (decreases) the risk of negative outcomes. Using the Highway Safety Information System database, we seek to merge the two approaches by, first, identifying roadway factors associated with an increased occurrence of car crashes and, subsequently, identifying roadway segments with a higher crash risk. Specifically, we model the locations of crashes as a realization from a spatial point process. We then parameterize the associated intensity surface of this spatial point process as the sum of a regression on roadway characteristics and spatially correlated error terms. Through the regression we identify hazardous roadway features and through the spatially correlated error terms we identify locations of high risk.