Abstract:
Due to enormous human and economic losses in road traffic crashes (RTCs), number of research efforts have been made in past to explore the causative factors in road traffic crashes. Most of the past research efforts remain focused on crash frequency and crash injury severity analysis. Present research effort is focused on the analysis of the influence of the drivers’ and vehicular characteristics, environmental conditions, crash pattern and causes of crashes on injury severity in motorways crashes. Data for present study have been extracted from the National Highways and Motorways Police (NHMP) records. Due to the ordinal nature of the response variable an ordered probit model has been estimated to study the association of crash injury severity with different explanatory variables. The model results revealed that crashes between lighter vehicles (passenger cars, pickups, panels and vans), crashes occurring during evening peak time, vehicles colliding via nose to tail pattern and crash involving new vehicles are more likely to be less severe. On the other hand dozing behind the wheel, over speeding, head-on collision and vehicle hitting pedestrian increase the probability of a crash to be more severe nature. Also, involvement of older drivers tends to increase the likelihood of the crash to be more severe. Marginal effects are presented to understand the effects of the significant variables on intermediate categories of the crash injury severity. The results of present research are expected to provide insight to planner and policy makers to enhance road safety on motorways and help in saving valuable lives.
