Due to legislative mandates and advances in organizational practices, transportation planning agencies have engaged in intensive data collection activities. The resulting data has been used, to some extent, by these agencies to guide their resource allocation decisions for their infrastructure assets. However, there still remains vast amounts of underutilized data that, if leveraged appropriately, could be used by planning agencies to improve the cost-effectiveness of their infrastructure maintenance and preservation activities. As a result, it is important that planning agencies gain better insights regarding the types of data frequently available within infrastructure management systems that can be used to reduce the life-cycle costs of an agency’s assets.Objectives:
The proposed research will:
- Identify and classify data items required to inform the maintenance and rehabilitation of different asset types.
- Determine the degree of relevance/criticality of select data items towards treatment decisions.
- Identify the level of detail required for asset management decisions at both the project and network level.
- Construct sensitivity analyses between data elements and infrastructure performance to explore the relationships that exist between them. This would also justify which data items are worth investing more resources into in order to mitigate uncertainties in developing long-term infrastructure preservation plans.
The research plan should:
- Conduct a literature review of relevant studies and practice within the scope of the research problem.
- Conduct a survey of current practices by planning agencies and state departments of transportation (DOTs) on current data availabilities and their use for decision-making
- Perform an in-depth case studies involving the management and application of critical data items to support infrastructure management decisions, particularly around key assets such as pavements.
- Develop a consolidated list of data elements and the level of detail required to support treatment decisions.
- Propose a method to identify the data that are critical to predict the infrastructure performance. The method should include but not limited to the plan of data collection, data mining, data analysis, model development and validation process.
- Flintsch, G. W., & Bryant, J. W. (2006). Asset management data collection for supporting decision processes. US Department of Transport, Federal Highway Administration, Washington, DC.
Duration: 18 months
Project Budget: $300,000
Topics: Asset Management Plans
Subjects: Inventory and Condition Assessment, Maintenance and Preservation