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Improved TAM Approaches for Aligning Network and Project Level Decisions Across Asset Classes
State departments of transportation (DOT) and other transportation agencies face a range of challenges in determining how best to invest in their existing pavements, bridges, and other physical assets, and in projecting what the impact of those investments will be over time. Addressing these challenges requires considering both specific planned or potential investments at a project or asset level, as well as overall expenditures and conditions for systems of assets – that is, at a network level. Evaluating assets at both the project and network levels is consistent with best practice in Transportation Asset Management (TAM), and is required by recent Federal regulations in performance and asset management. For instance, 23 Code of Federal Regulations (CFR) Part 490 requires state DOTs to set network-level performance targets for future pavement and bridge conditions for the National Highway System (NHS) based on expected funding. Also, 23 CFR Part 515 requires state DOTs to develop TAM plans for their NHS pavements and bridges including financial plans and investment strategies, implying further project-level analysis.
As transportation agencies are using their existing pavement and bridge management systems, they are finding that no one management system supports the full range of network and project-level analyses required to meet the demands of TAM practice and Federal regulations. Thus, to support TAM and meet Federal requirements agencies typically rely on multiple systems and approaches with different data requirements, analytical approaches and underlying assumptions. A common approach is to use pavement and bridge management systems to predict network-level conditions, typically projecting conditions out 10 or more years in the future, while making near-term project level decisions in a more decentralized manner using mix of expert judgment and heuristic approaches. In concept the network-level analysis can be used to guide project-level decisions, and specific project plans can often be incorporated in a network level analysis. However, in practice the network and project-level analyses are often performed largely independently from one another incorporating different data, factors and constraints.
The approach of using multiple approaches for network and project level asset analyses has numerous pitfalls. These include, but are not limited to: generating unrealistic predictions of network level conditions; developing projects that do not reflect optimal asset lifecycle plans developed at a network level; waste of staff time through inefficient business processes or duplication of effort; and omission of critical assets from one or more analyses (e.g., for lack of data or a dedicated management system). Guidance is needed to assist agencies in making better use of existing systems to integrate network and project-level analysis, as well as to define a framework for future asset management tools that will enable integrated network and project-level analyses across multiple asset classes, potentially using multi-objective approaches.
Literature Search Summary
The goal of this research is two-fold: to provide guidance on how transportation agencies can best use existing management systems and tools to integrate network and project-level analysis and provide a framework for an improve asset modeling approach that better integrates the project and network levels incorporating multiple asset types and consideration of multiple objectives. The research is intended to be of immediate value in helping transportation agencies better comply with Federal requirements to set performance targets and develop asset management plans. Also, it will help agencies to extend asset management approaches to additional systems and assets, besides the NHS pavement and bridge assets addressed through the Federal regulations. In addition, the research will help define improved approaches for asset management models for public agencies, researchers and system developers to use in developing the next generation of asset management systems.