@article{ref1,
title="Estimation of safety performance functions for urban intersections using various functional forms of the negative binomial regression model and a generalized Poisson  regression model",
journal="Accident analysis and prevention",
year="2021",
author="De Winne, Pieter and Pirdavani, Ali and Khattak, Muhammad Wisal and De Backer, Hans and Brijs, Tom",
volume="151",
number="",
pages="e105964-e105964",
abstract="Intersections are established dangerous entities of a highway system due to the challenging and unsafe roadway environment they are characterized for drivers and  other road users. In efforts to improve safety, an enormous interest has been shown  in developing statistical models for intersection crash prediction and explanation. The selection of an adequate form of the statistical model is of great importance  for the accurate estimation of crash frequency and the correct identification of  crash contributing factors. Using a six-year crash data, road infrastructure and  geometric design data, and traffic flow data of urban intersections, we applied  three different functional forms of negative binomial models (i.e., NB-1, NB-2,  NB-P) and a generalized Poisson (GP) model to develop safety performance functions  (SPF) by crash severity for signalized and unsignalized intersections. This paper  presents the relationships found between the explanatory variables and the expected  crash frequency. It reports the comparison of different models for total, injury &  fatal, and property damage only crashes in order to obtain ones with the maximum  estimation accuracy. The comparison of models was based on the goodness of fit and  the prediction performance measures. The fitted models showed that the traffic flow  and several variables related to road infrastructure and geometric design  significantly influence the intersection crash frequency. Further, the goodness of  fit and the prediction performance measures revealed that the NB-P model  outperformed other models in most crash severity levels for signalized  intersections. For the unsignalized intersections, the GP model was the best  performing model. When only the NB models were compared, the functional form NB-P  performed better than the traditional NB-1 and, more specifically, the NB-2 models. In conclusion, our findings suggest a potential improvement in the estimation  accuracy of the SPFs for urban intersections by applying the NB-P and GP models.<p /> <p>Language: en</p>",
language="en",
issn="0001-4575",
doi="10.1016/j.aap.2020.105964",
url="http://dx.doi.org/10.1016/j.aap.2020.105964"
}