Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Civil Engineering

Committee Chair/Advisor

Dr. Jennifer H. Ogle

Committee Member

Dr. Wayne A. Sarasua

Committee Member

Dr. Pamela Murray-Tuite

Committee Member

Dr. Richard A. Tyrrell


In 2019, South Carolina ranked fourth in the nation in pedestrian fatalities per 100,000 population. There has been a 68% increase in total pedestrian crashes in SC from 2011 to 2018. Walking might be a choice for some individuals; however, it is mandatory for some users due to the unavailability of personal automobiles or physical disability. Thus, pedestrian crashes and resulting deaths and injuries can disproportionately affect these population segments. Nationwide pedestrian crash statistics reveal American Indian or Alaskan Native and African American populations are overburdened with pedestrian crashes. This research aims to help mitigate this overburden of pedestrian crashes from the socio-economically disadvantaged population of South Carolina.

This research initially conducts pedestrian crash analysis to determine the most prevalent pedestrian crash types (midblock pedestrian crashes irrespective of time and midblock crashes at night), analyzing walking and crossing crashes and shed light on the primary contributing factors for these types of crashes.

Following the crash analysis, this research investigates the socio-economic characteristics of the pedestrians involved in crashes by geo-coding their home locations. This analysis helps to understand that 50% of collisions occur when pedestrians are close to their home locations. This study also reveals how poverty, unavailability of personal automobiles, fewer education attainments, and living in crowded quarters are critical characteristics of the population disproportionately involved in pedestrian crashes.

Finally, a case-control study was conducted to study the characteristics of the case (crash) and control (non-crash) sites. Land use, roadway characteristics, socioeconomic and sprawl of the case-control were studied. This research wraps up with the identification of the key contributing factors associated with classification cases and control sites.



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