Graduation Year
2015
Document Type
Thesis
Degree
M.S.C.E.
Degree Name
MS in Civil Engineering (M.S.C.E.)
Department
Civil Engineering
Degree Granting Department
Civil and Environmental Engineering
Major Professor
Steven Polzin, Ph.D.
Co-Major Professor
Abdul Pinjari, Ph.D.
Committee Member
Xuehao Chu, Ph.D.
Keywords
bivariate correlation analysis, fatalities, linear regression analysis, risk-taking behavior, socio-demographic characteristics
Abstract
Traffic fatalities accounted for 1.24 million lives lost in 2013 worldwide, and almost 33 thousand of those fatalities were in the U.S. in 2013. The southeastern region of the nation stands out for continuously having higher fatality rates per mile driven than the national average. If one can establish compelling relationships between various factors and fatality rates, then policies and investments can be targeted to increase the safety on the network by focusing on policies that mitigate those factors. In this research effort risk-taking characteristics are explored. These factors have not been as comprehensively reviewed as conventional factors such as vehicle and facility conditions associated with safety. The hypothesis assumes if a person exhibits risk-taking behavior, that risk-taking behavior is not limited to only one aspect of risk, but is likely to occur in multiple facets of the person's life. Some of the risk-taking characteristics explored include credit score, safety belt use, smoking and tobacco use, drug use, mental health, educational attainment, obesity, and overall general health characteristics. All risk-taking characteristics with the exception of mental health were found to have statistically significant correlations with fatality rates alone. However, when a regression model was formed to estimate fatality rates by risk-taking characteristics, only four risk-taking characteristics - credit score, educational attainment, overall poor health, and seat belt use were found to be statistically significant at an integrated level with other demographic characteristics such as unemployment levels and population born is state of residency. By identifying at-risk population segments, education, counseling, enforcement, or other strategies may be deployed to help improve travel safety.
Scholar Commons Citation
Godfrey, Jodi Anne, "Risk-Taking Characteristics as Explanatory Variables in Variations of Fatality Rates in the Southeastern United States" (2015). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/5483
