Investigating the Factors Affecting the Severity of Heavy Vehicle Crashes on Rural Roads Using Logit Regression*

Due to population growth and the increasing number of vehicles on rural roads, traffic accidents have become one of the most important problems in the transportation system. Heavy vehicles have a great impact on the economic progress of developing countries such as Iran. Due to the possibility of trade with the Caspian littoral countries and the existence of agricultural lands, rural roads in Guilan province experience a large volume of heavy vehicles. This study aims to investigate the factors that influence the severity of heavy vehicle crashes on rural roads using Kolmogorov-Smirnov and Friedman tests as well as a logit regression model. The results show that the presence of curves in road geometry, head-on collisions, off-peak crashes (1 AM to 6 AM), and peak crashes (7 PM-midnight), familiar drivers, and agricultural vehicles are associated with more severe injuries. Furthermore, motorcyclists are the most vulnerable road users in crashes involving heavy vehicles. On the other hand, some factors such as the presence of road median, side-swipe collision type, and clear weather reduce the severity of crashes.