Date of Award

May 2020

Document Type


Degree Name

Master of Science (MS)


Civil Engineering

Committee Member

Wayne A Sarasua

Committee Member

Jennifer H Ogle

Committee Member

William J Davis


This thesis focused on using a statistical model called the RIDIT analysis to perform a comparative study of severity crashes for different facility types in South Carolina. RIDIT uses the proportion of injury crashes and our analysis used three levels of injury categories, Fatal, Injury, and PDO as an indicator of severity level using three years of crash data from 2016 to 2018. There was two main focus of this study, first to compare the severity of two different network-screening methods (intersection to intersection and short 100’ buffers) used to identify the hotspot location for high crash incidence. We compared the severity of these two segmentation methods to determine which segments are prone to higher severity crashes within different facility types. The next objective was to compare the severity levels of different facility types in the state to determine the most severe roadway class in the state. Results showed that for rural roads, the short 100’ buffers were most likely to be severe and for urban roads, the long segments were likely to have more severe crashes. Urban two lanes undivided for urban roads and rural two lanes undivided for rural roads were determined as the most severe roadway class and the results were statistically significant. Similarly, among all rural and urban roads, rural two lanes undivided roads were found to be the most severe roadway class in the state with the results being statistically significant.



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