An Analysis of Vehicle Occupants’ Injury Severity in Crashes Occurred On Rural Freeways and Multilane Highways in Iran

Vehicle occupants comprise a considerable proportion of traffic crash victims in Iran. This paper has focused on vehicleoccupants’ injury severity and employed the Classification and Regression Tree (CART) technique in order toidentify the most important variables affecting the injury severity of these road users in crashes occurred on rural freewaysand multilane highways in Iran over a three year period (2006-2008). In the procedure adopted in this paper, theproblem of three-class prediction was decomposed into four binary prediction models. Results revealed a high overallprediction accuracy of the models. Ten explanatory variables were considered in the current study in order to find themost important variables affecting the injury severity of occupants. In this regard, some “if-then” rules pertaining tothe conditions that lead to more severe injuries are provided based on the decision tree analysis. Results confirm thealready-known importance of seatbelt usage for preventing serious injuries in one hand, and imply the insufficiencyof seatbelt usage for protecting the occupants from receiving serious injuries in some collision types, on the otherhand. This underscores the need for more safety instruments (especially airbags for all occupants of the vehicle) to beinstalled in passenger cars in Iran.