Numerical Examinations of Traffic Accident Characteristics Using Analytical Statistical Methods

Abstract

This study applied analytical statistical approaches to investigate some characteristics of traffic accidents. The regression analysis of the injury severities of accidents, and the discrete choice model of different time periods of day when accidents likely occur have been developed. The Poisson regression and Logit model were used by considering the occurrence mechanism of accidents on freeways. Using the observed accident data in Washington State, the accident injury severity model was successfully estimated using a Passion regression. Three variables were found significant in the model. The findings of this study were encouraging. In the studies of Logit model the probability of occurrence of an accident in the different time periods of day including day, dawn, evening and night was expressed by the four utility functions. Both traffic flow and freeway characteristics were included in the model. Compared with most existing models, the new findings were obtained to describe some accidents characteristics.