The number of crashes and fatalities rate in the Commonwealth of Kentucky, U.S., have been higher than the national average for the past decades. It has been hypothesized that the distinct socioeconomic conditions of the state could be contributing to and explaining these trends. This study investigated the influence of socioeconomic characteristics on highway safety in Kentucky and attempted to identify the high-risk driver groups, based on crash data and the socioeconomic and demographic features of their residence zip codes. The quasi-induced exposure technique and binary logistic regression were employed to develop a predictive modeling approach for determining the probability of being the at-fault driver in a single-and two-unit crashes, based on socioeconomic characteristics of the driver residence zip code. The study identified that socioeconomic features such as income, poverty level, employment, age, gender, rurality, and number of traffic-related convictions of a driver’s zip code influence their likelihood to be at fault in a two-unit crash, while for single-unit crashes, in addition to these variables, educational attainment had also an impact. Younger and older drivers living in zip codes with low socioeconomic conditions have a higher probability to be the at-fault driver in both single-and two-unit crashes. The conclusions of the study can be used to determine the regions (zip codes) and driver groups with higher likelihood to be the at-fault driver in a crash and develop effective safety programs for the target groups.
Bibliographical noteFunding Information:
The authors would like to acknowledge the support of the Kentucky Injury Prevention Center and the Kentucky Transportation Cabinet.
© National Academy of Sciences: Transportation Research Board 2021.
ASJC Scopus subject areas
- Civil and Structural Engineering
- Mechanical Engineering