Modeling spatial spillover effect on intersection crash propensity: a case study at the county level in Ohio

Abstract

Abstract The characteristics of intersection crashes are not only affected by the subject intersection where the crash occurs but also are correlated with environmental conditions of neighboring analysis zones. There are few studies on intersection crash analysis to solve certain spatial effects on microscopic safety issues by proactively incorporating highway safety improvement measures into the long-term transportation planning process. The objective of this paper is to develop a heuristic traffic safety analysis system where spatial spillovers analysis is integrated into roadway safety assessment to incorporate micro variables and macro variables. With K-means clustering technique in a GIS environment, 8 hotspot counties are identified from 88 counties in Ohio, which have high intersection crash propensity. The rest of counties are identified as general counties. Then, an innovative integrated Generalized Linear Model is adopted to identify 11 and 20 significant variables that contribute to the intersection crash propensity in hotspot counties and general counties, respectively. To verify compatibility of intersection crash frequency models with macro-level and micro-level measurement, Reading Road in Cincinnati, Hamilton County (hotspot county) and I-71 in Mason City and Lebanon City of Warren County (general county) are used as examples for the test, and the results show a good consistence.