Identification of factors associated with pedestrian hot crash spots : spatial and statistical analysis approach

Pedestrian and bicycle safety challenges are becoming more apparent as those modes increase in popularity. Policy-relevant safety analysis methods for these modes are rare, particularly related to exposure. This paper presents a pedestrian safety hotspot analysis to identify and prioritize specific road segments and intersections with high crash locations using Geographic Information System (GIS), coupled with background demographic analysis to inform policy development. The identification process was done in a GIS environment using Getis-Ord Gi-star hotspot analysis tool. The Gi-star index was used to locate crash hot spot street segments and intersections and discern cluster structures of high or low-value concentration among local observations. The goal was to examine the existence of a spatial pattern for pedestrian crashes associated with roadway geometry, socioeconomic, population distribution and other related factors. This study focuses on Tennessee’s pedestrian crashes and identified and ranked high crash locations based on: crash frequency; weighted crash frequency by injury severities (EPDO); crash rates calculated per VMT, area, total population, mean household income, population of Whites, Blacks and Hispanics as well as the average of all rankings. The identified high crash locations and the rankings will enable state and local agencies to properly invest and prioritize funds to improve and maximize the reduction in statewide pedestrian crashes. It will also assist in identifying suitable locations for road safety audits. The hot spot identification and ranking approaches presented here represents current best practices that can be mimicked in other states