Type of Document Dissertation Author Ofosu, Kwabena URN etd-04212010-142504 Title An Integrated Approach to Transportation Infrastructure Management Degree Doctor of Philosophy Department Civil and Environmental Engineering, Department of Advisory Committee
Advisor Name Title John O. Sobanjo Committee Chair Lisa K. Spainhour Committee Member Yassir AbdelRazig Committee Member Marten Wegkamp University Representative Keywords
- Integrated Infrastructure Management
- Asset Management
- Sojourn Time
- Multi-objective Optimization
- Genetic Algorithm
- Infrastructure Deterioration
Date of Defense 2010-03-17 Availability unrestricted AbstractTransportation infrastructure enables the safe and timely movement of people, goods, and services. Transportation infrastructure assets include roads, bridges, culverts, tunnels, traffic control systems, and roadside appurtenances such as guardrails, lighting systems, and supports and structures for signs, signals, and luminaries. Transportation agencies use infrastructure management systems to maintain these infrastructure components. Typically each infrastructure component is managed separately and independently within an agency. Recently agencies have been exploring ways to optimize ever-decreasing overall budget allocations by coordinating work programs of the numerous infrastructure components they manage in an integrated manner. Integrated infrastructure management systems provide a comprehensive approach to systems management by analyzing the entire transportation system and evaluating the needs of the individual component systems and the interactions between them, simultaneously. It is expected that the integrated approach will potentially result in cost savings to agencies, and also minimize the impact of maintenance activities on the motoring public.
The primary objective of this study is to develop a formal framework that an agency can use to analyze tradeoffs within, and across its constituent infrastructure management systems, enabling the agency to pursue optimal strategies for its total infrastructure network in an integrated manner. In a new approach, statistical likelihood-based methods are used to develop models to predict future bridge structural reliability, and pavement condition ratings. Likelihood-based prediction models are also developed for culvert reliability index as well as culvert condition ratings. Existing project-level methodology elements for the selection of eligible improvements, and the life-cycle cost streams of the improvements are reviewed and updated. A project-level methodology for signs based on age is also developed in this study.
The allocation of maintenance, rehabilitation, and replacement dollars within and across the component infrastructure management systems over a multiyear programming period is formulated as a large-scale multi-objective integer non-linear optimization problem. The multi-objective approach enables trade-offs to be analyzed. Network parameters for the trade-off analysis include present value of life-cycle benefits, asset value, and asset service index. The network optimization problem incorporates the project-level methodologies developed in this study, and a genetic algorithm is developed to solve the multi-objective integer non-linear program.
To enhance cost-effective implementation, a project integration methodology is developed to combine together, selected projects in different asset classes, which were originally selected in different years of the multiyear program, but are in spatial proximity to one another. Project-level integration results in savings to an agency by creating economies of scale that ultimately reduce both agency and user costs, and eliminates multiple overheads and mobilization costs associated with multiple projects. Project-level integration has benefits to road users by minimizing repeated traffic disruptions and other impacts of the work activity on the public.
The sensitivity analyses performed at the project-level for sample facilities in each infrastructure class concluded that life-cycle benefits were more sensitive to improvementsí costs as well as traffic volumes using the facility, at lower discount rates. At the network optimization level, the sensitivity analyses showed that as improvementsí costs increase, the selection of more of the less capital-intensive improvements is a more effective strategy in maximizing network benefits and network performance simultaneously. A case study is presented to show the benefits of the integration of infrastructure management decisions to an agency and to road users. The case study showed that the project-level tools presented in this study as well as the network optimization methodologies can be used to efficiently find optimal solutions for networks consisting of several infrastructure systems, each of which having hundreds facilities. Computer programming tools are developed in this study, to enable an agency implement and present the data integration and analytical procedures developed in this study.
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