An Accident Prediction Model For Divided Highways: A Case Study Of Trabzon Coastal Divided Highway
Free (open access)
711 - 719
F. Ture Kibar, F. Celik & B. P. Aytac
Traffic accidents in Turkey have been increasing every year. Although serious property damage and fatalities have occurred in accidents, Turkey hasn’t sufficiently overcome this problem. The main objective for this study is to investigate the factors which cause accidents and to create an accident prediction model which includes relationships between these factors. With this model, the expected number of accidents at divided highways can be predicted and suitable measures for providing road safety can be defined. For this study, 5 years’ (2002, 2003, 2004, 2006 and 2007) accident data of 113.5 km road sections of Trabzon coastal divided highway, traffic and highway characteristics of these sections were collected, then an accident prediction model was formed. The technique of generalized linear models (GLMs) was applied to the data. Because of over dispersion of Poisson regression model, a Negative Binomial regression model was found to be the most appropriate approach for analysis of this data. This model indicates that the vehicle kilometres of travel, the number of pedestrian crossing and average posted speed are significant variables on traffic accident occurrences. Keywords: traffic accidents, road safety, accident prediction model, Poisson regression, Negative Binomial regression.
Keywords: traffic accidents, road safety, accident prediction model, Poisson regression, Negative Binomial regression.