Identification and Modeling of Effective Factors on the Road Crash Severity by Binaary Logit Model

Injury severity is an important index to analyse cost of crashes. Several approaches have been used to model and predict the crash severity. In this study, using road traffic accidents in seven provinces of Iran (Isfahan, Khuzestan, southern Khorasan, Qom, Qazvin, Kerman and Mazandaran), and Binaary Logit model has been used to predict the fatal or injury crashes. The effect of important variables on the crash severity of each of the three types of accidents involving motorcycles, sedans and trucks was investigated. Also, factors such as increasing the difference in weight of vehicles, deviations to the left, increasing the age of drivers, pedestrian presence and exceeding speed limits lead to increased crash severity and fatal accidents.