Date of Award

12-2010

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Legacy Department

Civil Engineering

Committee Chair/Advisor

Ogle, Jennifer H

Committee Member

Davis , William J

Committee Member

Dixon , Karen

Committee Member

Sarasua , Wayne

Abstract

With about 125 people dying on US roads each day, the US Department of Transportation heightened the awareness of critical safety issues with the passage of SAFETEA - LU (Safe Accountable Flexible Efficient Transportation Equity Act - a Legacy for Users) legislation in 2005. The legislation required each of the states to develop a Strategic Highway Safety Plan (SHSP) and incorporate data-driven approaches to prioritize and evaluate program outcomes: Failure to do so resulted in funding sanctioning. In conjunction with the legislation, research efforts have also been progressing toward the development of new safety analysis tools such as IHSDM (Interactive Highway Safety Design Model), SafetyAnalyst and HSM (Highway Safety Manual). These software and analysis tools are comparatively more advanced in statistical theory and level of accuracy, and have a tendency to be more data intensive.
A review of the 2009 five-percent reports and excerpts from the nationwide survey revealed astonishing facts about the continuing use of traditional methods including crash frequencies and rates for site selection and prioritization. The intense data requirements and statistical complexity of advanced safety tools are considered as a hindrance to their adoption. In this context, this research aims at identifying the data requirements and data availability for SafetyAnalyst and HSM by working with both the tools. This research sets the stage for working with the Empirical Bayes approach by highlighting some of the biases and issues associated with the traditional methods of selecting projects such as greater emphasis on traffic volume and regression-to-mean phenomena. Further, the not-so-obvious issue with shorter segment lengths, which effect the results independent of the methods used, is also discussed. The more reliable and statistically acceptable Empirical Bayes methodology requires safety performance functions (SPFs), regression equations predicting the relation between crashes and exposure for a subset of roadway network. These SPFs, specific to a region and the analysis period are often unavailable. Calibration of already existing default national SPFs to the state's data could be a feasible solution, but, how well the state's data is represented is a legitimate question. With this background, SPFs were generated for various classifications of segments in Georgia and compared against the national default SPFs used in SafetyAnalyst calibrated to Georgia data.
Dwelling deeper into the development of SPFs, the influence of actual and estimated traffic data on the fit of the equations is also studied questioning the accuracy and reliability of traffic estimations.
In addition to SafetyAnalyst, HSM aims at performing quantitative safety analysis. Applying HSM methodology to two-way two-lane rural roads, the effect of using multiple CMFs (Crash Modification Factors) is studied. Lastly, data requirements, methodology, constraints, and results are compared between SafetyAnalyst and HSM.

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