A Comparative Study of Alternative Model Structures and Criteria for Ranking Locations for Safety Improvements

Abstract

In transportation safety literature, many statistical models and criteria have been proposed for quantifying risk at transportation facilities such as roadway intersections and highway–rail grade crossings, and identifying candidate locations, or blackspots, for engineering improvements. There are, however, few systematic studies on the comparative performance and practical implications of these models and criteria. The primary goal of this study is to investigate the relative impacts that the use of various alternative models and ranking criteria can have on identifying blackspots. Three alternative models are considered in this investigation, including the popular negative binomial model (NB), the heterogeneous negative binomial model (HNB), and the zero inflated negative binomial model (ZINB). The expected accident frequency based on both marginal distribution and posterior distribution is considered as a ranking criterion. A sample of highway–railway grade crossings located in the Canadian railway network is used in this investigation as an application environment.