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

Document Type: Research Paper


1 Assistant Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran, and Road Safety Research Centre, Iran University of Science and Technology, Tehran, Iran

2 Ph.D. Student, School of Civil Engineering, Iran University of Science and Technology and Road Safety Research Centre, Iran University of Science and Technology, Tehran, Iran


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


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