The transportation infrastructure system in the United States is aging and insufficient to serve the current needs of a growing population. Major highways have already exceeded their life expectancy. Therefore, state transportation agencies need to restore existing transportation networks across the nation. Penetrating to the second layer of the issue, there are many highways to rehabilitate, but funds are limited. This demands efficient allocation and prioritization of projects. The lack of analytical methods for fund allocation and project prioritization has always been a challenge for transportation agencies. To address this issue, this research is intended to develop a quantitative approach to prioritizing capital projects. The major objectives of this research are (a) to highlight the limitation of existing fund allocation and prioritization methods and (b) to create an effective quantitative model for prioritizing projects for transportation agencies. The pertinent literature review of monthly Texas Department of Transportation reports was accomplished to select three real-time highway projects from Texas. The information retrieved from the reports includes average annual daily traffic, total project cost, length (in miles), and crash rate information for the selected project. First, information was analyzed to calculate accident savings using cost-benefit analysis and ranked according to their cost to benefit ratio. The same data was processed to reduce envy and allocate funds fairly on the basis of three criteria (i.e., cost, safety, and traffic congestion) using the fair division method algorithm coded on a Matlab framework. Last, results from the previous two methods were analyzed and integrated using the analytical hierarchy process to generate a common result. The results of the research reveal that the combination of the cost-benefit analysis, the fair division method, and the analytical hierarchy process can be a promising tool, as it is not only effective to prioritize projects on their merits but also helps to minimize envy among participants during fund allocation.
