Ordered Fractional Split Approach for Aggregate Injury Severity Modeling

In crash frequency models, frequency by severity level is examined with multivariate count models. In these multivariate approaches the impact of exogenous variables is quantified through the propensity component of count models. The main interaction between variables across severity levels is sought through unobserved effects; that is, there is no interaction of observed effects across the multiple count models. Although this is not necessarily a limitation, it could be beneficial to evaluate the impact of exogenous variables in a framework that directly relates a single exogenous variable to all severity count variables simultaneously. An alternative approach to examining crash frequency by severity is proposed. Specifically, instead of modeling the number of crashes, a fractional split modeling approach is used to study the fraction of crashes by each severity level on a road segment. Given the ordered nature of injury severity, an ordered probit fractional split model is used to study crash proportion by severity levels. The model is estimated for roadway segment data for single-vehicle and multivehicle crashes in Florida for 2009 through 2011. The model estimation results highlight the effect of traffic volume, lane width, shoulder width, proportion of divided segments, and speed limit on crash proportion by severity. The model results are used to predict hot spots for various crash types. The results highlight how the ordered probit fractional split models can be used for highway safety screening.