Developing Meta Data for State DOTs from Complex Optimization Problems to Support Asset Management

Limited resources, aging infrastructure, and an increased focus on performance and life cycle costs rather than simply condition have led to widespread adoption of asset management principles by state DOTs. The practice of asset management is heavily influenced by a broad base of experience with asset specific tools for pavement and bridge management, commercial software, and the federal requirement to develop Transportation Asset Management Plans for NHS bridges and pavements. While states use deterioration and costs models, identify goals and objectives, and aim to identify optimal preservation and improvement decisions, the state of the practice does reflect widespread application of the complex decision-making models developed by the research community (Chen & Bai, 2019; Chen, Liang, Wu, & Sun, 2019). In fact, there is some skepticism and fear of the loss of transparency, despite demonstrated gains realized in the application of the more complex models (Wang & Pyle, 2019). This project develops a framework that addresses this concern. The project begins with a complex model developed as part of a previous CIAMTIS project “Strategic prioritization and planning for multi-asset transportation infrastructure maintenance, rehabilitation, and improvements: Phase 1 – Prioritization through optimization” (Zhou, Miller-Hooks, Papakonstantinou, Stoffels, & McNeil, 2021). The framework will be developed by defining scenarios, parameterizing scenarios, running the model, comparing the results to simpler tools such as decision trees and thresholds, and translating them into updated tools that are more accessible to state DOTs. The objective is to use hybrid network analysis and machine learning tools to understand when the complex model can be reduced to the simpler tools and when the application of the more complex model are warranted.

• Record URL:
  • Developing Meta Data for State DOTs from Complex Optimization Problems to Support Asset Management

Language

• English

Project

• Status: Active
• Funding: $124376
• Contract Numbers:

  69A3551847103

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)

  Pennsylvania State University
  University Park, PA  United States  16802
• Project Managers:

  Donnell, Eric

• Performing Organizations:

  Delaware Center for Transportation

  University of Delaware
  Newark, DE  United States  19716
• Principal Investigators:

  McNeil, Sue

  Attoh-Okine, N

• Start Date: 20220304
• Expected Completion Date: 20231003
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Asset management; Infrastructure; Life cycle costing; Machine learning; Network analysis (Planning); State departments of transportation
• Subject Areas: Highways; Maintenance and Preservation; Planning and Forecasting;

Filing Info

• Accession Number: 01838326
• Record Type: Research project
• Source Agency: Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)
• Contract Numbers: 69A3551847103
• Files: UTC, RIP
• Created Date: Mar 9 2022 6:12PM