An AI-Based Reasoning Framework for Proactive Infrastructure Monitoring and Preservation Using Connected Autonomous Vehicles

This research proposes the development of a Connected Autonomous Vehicles (CAV)-based Proactive Infrastructure Preserving (CAV-PIP) system to enhance the safety, resilience, and operational efficiency of transportation infrastructure. The system leverages the sensing and communication capabilities of CAVs to enable continuous, real-time detection and reporting of roadway anomalies, such as pavement distress and damaged traffic signage. By fusing multi-modal sensor data and incorporating a retrieval-augmented generation (RAG) framework with large language models (LLMs), the system constructs a dynamic prior knowledge base to reason about infrastructure conditions and recommend context-aware maintenance actions. The project aims to transform current reactive maintenance practices into a data-driven, proactive framework that improves decision-making for transportation agencies. The system will be validated through simulation in the CARLA (Car Learning to Act) environment and supported by curated real-world datasets. Expected outcomes include an integrated detection and reasoning framework, structured maintenance reporting tools, and publicly shareable datasets and software packages. The project’s broader impact lies in advancing intelligent infrastructure monitoring technologies, reducing long-term maintenance costs, and contributing to safer and more sustainable transportation systems.

• Record URL:
  • https://www.ctips.org/projects/details.php?id=658

Language

• English

Project

• Status: Proposed
• Funding: $100,000.00
• 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:

  University of Utah

  Department of Civil and Environmental Engineering
  110 Central Campus Drive Suite 2000
  Salt Lake City, UT  United States  84112
• Principal Investigators:

  Liu, Chenxi

  Liu, Xiaoyue "Cathy"

• Start Date: 20251213
• Expected Completion Date: 20271212
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program
• Source Data: CTIPS-061

Subject/Index Terms

• TRT Terms: Artificial intelligence; Autonomous vehicles; Connected vehicles; Data fusion; Infrastructure; Maintenance management; Monitoring; Simulation
• Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01976557
• Record Type: Research project
• Source Agency: Center for Transformative Infrastructure Preservation and Sustainability
• Contract Numbers: 69A3552348308
• Files: UTC, RIP
• Created Date: Jan 19 2026 5:01PM