Graduation Year


Document Type




Degree Granting Department

Civil Engineering

Major Professor

Jian Lu, Ph.D.

Committee Member

Abdul Pinjari, Ph.D.

Committee Member

Yu Zhang, Ph.D.

Committee Member

Zhenyu Wang, Ph.D.


Ordered probit regression, Descriptive statistics, Age groups, Traffic safety, Marginal effects


In USA, despite recent efforts to improve work zone safety, the number of crashes and fatalities at work zones has increased continuously over several past years. For addressing the existing safety problems, a clear understanding of the characteristics of work zone crashes is necessary. This thesis summarized a research study focusing on work zone traffic crash analysis to investigate the characteristics of work zone crashes and to identify the factors contributing to injury severity at work zones. These factors included roadway design, environmental conditions, traffic conditions and vehicle/driver features. Especially, special population groups, which divided into older, middle Age, and young, were inspected. This study was based on history crash data from the Florida State, which were extracted from the Florida CAR (Crash Analysis Reporting) system. Descriptive statistics method was used to find the characteristics of crashes at work zones. After then, an injury severity predict model, using the ordered probit regression technology, was developed to investigate the impacts of various factors on different the injury severity at work zones. From the model, it can be concluded that some factors, including the road section with curve, alcohol/drugs involved, a high speed, angle crash and too young or old drivers are more likely to increase the probability of angle crashes. Based on the magnitudes of the variable coefficients, the factor of maximum posted speed have a great impact to injury severity, which shows restriction to driving speed is principle countermeasure for improving work zone safety.