Transportation agencies in the United States nowadays rely on tax dollars for maintaining surface transportation infrastructure, which mainly... Show moreTransportation agencies in the United States nowadays rely on tax dollars for maintaining surface transportation infrastructure, which mainly comes from fuel tax. However, travel behaviors are changing every day. People and businesses demand better and safer roads. Yet, consumers travel in more fuel-efficient vehicles and buy less gas, which means less revenue for fixing aging roads and highways. Meanwhile, new construction and repair costs increase for our overburdened transportation systems. Transportation agencies, therefore, must use their limited funding more wisely to optimize the service performance and minimize risks (Li, 2018). The budget allocation problem in transportation is not an easy task. The consequences of an ineffective decision in allocating resources are multi-facet both in the short- and long-term, including degrading in the condition of transportation facilities, losing public trust, and increasing backlogs in maintenance and repair. Therefore, transportation agencies are seeking more robust and comprehensive data-driven strategies that take into account of agency’s strategic goals and regulatory requirements, user expectations, nature of the asset, availability of resources, and lifecycle cost analysis in determining the optimal allocation of resources and making the best use of available funds (Li and Sinha, 2004; Sinha and Labi, 2007).
The proposed research aims to utilize the concept of multicriteria decision making coupled with a holistic asset management framework to support performance-based allocations of transportation budgets and help transportation agencies achieve the future vision of the nation’s strategic planning requirements to enable sustainable management of the system. A computational study for the real-world dataset obtained by a state Department of Transportation (DOT) is conducted using the proposed budget allocation method. The results from the computational study reveal that the proposed method can derive optimal decision solutions for transportation budget allocation problems and can be utilized by transportation agencies on different scales – urban and rural, in other sectors – public and private, to effectively manage the transportation infrastructure sustainably, by effectively spending transportation budget to maximize service performance and minimize operating costs. Show less
