Assessing Casualty Risk of Railroad-Grade Crossing Crashes Using Zero-Inflated Poisson Models

Abstract

A railroad grade crossing (RGC) is a spatial location where rail and highway users share the right-of-way. A significant number of traffic crashes and severe consequences at RGCs have signaled the need for appropriate models to investigate the key factors associated with the casualty risk level at an RGC in terms of the number of fatalities or injuries caused by one or more crashes in a specific time period. This study used a zero-inflated Poisson regression model to describe the relationship between the extra-zero count fatality or injury data and explanatory variables collected at 592 RGCs in Taiwan. The annual averaged daily traffic and the presence of Guidance Sign 31 were significantly associated with the probability of no fatality or injury encountered at an RGC; if an RGC was at risk of a fatality or injury, the number of daily trains, crossing angle, and Guidance Sign 31 significantly influenced the expected total number of fatalities or injuries caused by traffic crashes. The empirical results indicated that traffic exposure and traffic signage have significant effects on the risk levels of casualties at an RGC.