Characteristics of injury and fatality of run-off-road crashes on Ohio roadways

Date of Award


Degree Name

M.S. in Civil Engineering


Department of Civil and Environmental Engineering and Engineering Mechanics


Advisor: Deogratias Eustace


A run-off-road (ROR) crash or a roadway departure crash is a non-intersection crash which occurs after a vehicle crosses an edge line or a center line (i.e., leaves its designated traveled way and in the process the vehicle collides with a non-traversable obstacle or another vehicle travelling in the opposite direction or hits a pedestrian, or the vehicle overturns. The main objective of this thesis study was to determine the factors that contribute significantly to the levels of injury severity when ROR crashes occur. This study used a 5-year crash data for years 2008 - 2012 obtained from the Ohio Department of Public Safety. The decision tree model in conjunction with generalized ordered logit model was used to investigate characteristics of injury and fatality of run-off-road crashes in Ohio. The decision tree modeling was used for exploratory data analysis identified eight factors that explain a large amount of the variation in the response variable, injury severity. These important predictors for injury severity include road condition, run-off-road (ROR) crash types, posted speed limit, vehicle type, gender, alcohol-related, road contour, and drug-related. Also, complex interactions between parameters were identified. The results from the generalized ordered logit regression show that the following are significant factors in increasing the likelihood of ROR injury severity levels: alcohol and drugs use, curves and grades, female victims, overturn/rollover crashes, ROR crashes on dry roadway surfaces. Additionally, buses, truck, and emergency vehicles, and ROR crashes on roadways with posted speed limits of 40 mph or higher increase the probability of injury severity.


Accident victims Wounds and injuries Forecasting Statistical methods, Traffic fatalities Forecasting Statistical methods, Run-off-the-road accidents Ohio Forecasting Statistical methods, Traffic accidents Ohio Forecasting Statistical methods, Civil engineering

Rights Statement

Copyright 2013, author