Smart Funding Strategies for Maintaining Interdependent Transportation Infrastructure Assets

US Transportation Collection2019PDFTech ReportWang, ZhaohuaLi, MingshuLiu, LierHoudhary, AnirudhZhang, GeCenter for Transportation, Equity, Decisions & Dollars (CTEDD). University of TexasUniversity of Texas at ArlingtonUnited States. Department of Transportation. Research and Innovative Technology AdministrationUnited States. Department of Transportation. University Transportation Centers (UTC) ProgramCenter for Transportation, Equity, Decisions and Dollars (CTEDD)United StatesAsset managementBridgesCase studiesDeteriorationFinancingHighway maintenanceInfrastructureMultiple criteria decision makingOptimizationPavement maintenanceTraffic simulationTransportationGenetic algorithmsCross-assetTraffic ReassignmentCTEDD 018-07Final report; 8/15/2018 \u2013 12/14/2019This research project aims to cost-effectively maintain entire road network that consists of different transportation infrastructure assets, such as pavements, bridges, signs, etc. A well-maintained road network is critically important to support the nation\u2019s mobility, economy, and security. To address this need, this research project explored several aspects of smart funding strategies for optimally maintaining road network that consists of different, but interdependent, transportation infrastructure assets. First, a larger case study was conducted to demonstrate the benefit of maintenance programming by considering the interdependency between pavements and bridges. For this purpose, a general framework, consisting of pavements and bridges, was formulated as an interdependency-based optimization model by incorporating traffic capacity models, deterioration models, and treatment improvement models. In the meantime, for comparison purpose, a WSM-based optimization model was also developed by adopting the commonly used engineering-judgment-based MCDM method. The results demonstrated that WSM-based maintenance programming and the resulted performance relies on decision makers\u2019 preference. In contrast, the interdependency-based counterpart can achieve the best maintenance programming that maximizes the transportation efficiency of the road network without the need of decision makers\u2019 preference. More importantly, the maintenance programming based on engineering judgment cannot consider the spatial relationship and interdependency among different types of assets, which results in the difficulty of coordination in highway agencies\u2019 practice. Second, a new bridge deterioration modeling is developed to improve the objectivity and effectiveness of bridge maintenance action plan. Deterioration probability matrices of deck, substructure and superstructure, as three major components of a bridge, are used to determine their deterioration states instead of using substructure\u2019s matrix for a bridge as a whole. A new index is created to represent overall health of a bridge; it considers three components of a bridge, their area and unit maintenance costs, which can more subjectively define bridge condition. Third, traffic reassignment was explored to be integrated with pavement maintenance programming. The open source traffic simulation software, SUMO, was adopted for this purpose. A case study taking a small fraction of road networks in Atlanta was used as input for computation. Integrating SUMO into this optimization problem formulation consumes excessive computation time than expected, yet the study shows promising results of such integration. Both objectivity and cost-effectiveness are improved in this attempt. Finally, conclusions and recommendations were offered.110