AI-Driven Infrastructure Prioritization: Vision-Language Model Framework for Capital Planning

This project develops a scalable, artificial intelligence (AI)-powered framework for automated condition assessment and capital investment prioritization of road and bridge infrastructure across Colorado. Current manual inspection methods are costly, slow, and limited in coverage, often missing early signs of degradation. Leveraging recent advances in Vision-Language Models (VLMs), the project proposes a novel approach that extracts Pavement Condition Index (PCI) and bridge deck ratings from satellite and street-level imagery using VLMs guided by prompt engineering and in-context learning, requiring no retraining, and will be validated against Colorado Department of Transportation (CDOT) inspection records using machine learning model accuracy metrics. The framework integrates three components: (1) Infrastructure condition (2) network criticality, computed via graph-theoretic metrics and traffic data, and (3) hazard exposure, based on geospatial data for landslides, wildfires, and floods. These layers will be synthesized into a weighted prioritization model to rank road segments for capital upgrades, refined through CDOT expert review. A web-based geographic information system (GIS) tool will visualize prioritization results, supporting interactive exploration and decision-making. The tool will be pilot-tested with CDOT districts, and outcomes will be disseminated through a final report, peer-reviewed publication, Transportation Learning Network (TLN) webinar, and Colorado LTAP training. By integrating AI, geospatial analytics, and network modeling, this project addresses data-driven infrastructure planning needs—enhancing efficiency, reliability, and resilience—while offering a replicable model nationwide.

• Record URL:
  • https://www.ctips.org/projects/details.php?id=652

Language

• English

Project

• Status: Active
• Funding: $178,000.00
• Contract Numbers:

  69A3552348308

• 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 Transformative Infrastructure Preservation and Sustainability

  North Dakota State University
  Fargo, North Dakota  United States  58108-6050
• Project Managers:

  Tolliver, Denver

• Performing Organizations:

  Colorado State University

  Department of Civil and Environmental Engineering
  Campus Delivery 1372
  Fort Collins, CO  United States  80523
• Principal Investigators:

  Jana, Debasish

• Start Date: 20251028
• Expected Completion Date: 20271027
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program
• Source Data: CTIPS-054

Subject/Index Terms

• TRT Terms: Artificial intelligence; Bridge decks; Inspection; Machine learning; Maintenance management; Pavement management systems; Spatial analysis; Strategic planning
• Geographic Terms: Colorado
• Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation; Pavements; Planning and Forecasting;

Filing Info

• Accession Number: 01970711
• Record Type: Research project
• Source Agency: Center for Transformative Infrastructure Preservation and Sustainability
• Contract Numbers: 69A3552348308
• Files: UTC, RIP
• Created Date: Nov 10 2025 4:24PM