TRB Paper #11-2877 Examining the Crash Variances Estimated by the Poisson-Gamma and Conway-Maxwell-Poisson Models

1 The Poisson-gamma (negative binomial or NB) distribution is still the most common probabilistic distribution used by transportation safety analysts for modeling motor vehicle crashes. Recent studies have showed that the Conway-Maxwell-Poisson distribution (COM-Poisson) distribution is also one of the promising distributions for developing crash prediction models. The objectives of this study were to investigate and compare the estimation of crash variance predicted by COM-Poisson GLM and the traditional Negative Binomial (NB) model. The comparison analysis was carried out using the most common functional forms employed by transportation safety analysts, which link crashes to the entering flows and other explanatory variables at intersections or on segments. To accomplish the objectives of the study, several NB and COM-Poisson GLMs, including flow-only models and models with several covariates, were developed and compared using two datasets. The first dataset contained crash data collected at signalized 4-legged intersections in Toronto, Ont. The second dataset included data collected for rural 4-lane undivided highways in Texas. The results of this study show that the trend of cras