AI-assisted Condition Assessment of Roads
The objective of this project is to develop an AI-assisted road monitoring system that enables low-cost, autonomous, and frequent condition-based assessments using a network of mobile sensing units. The system will use computer vision and machine learning to detect and quantify pavement defects, replacing traditional schedule-based inspections with continuous, data-driven monitoring. The proposed system provides transportation agencies with an affordable, scalable, and intelligent tool for real-time pavement monitoring. By using low-cost sensors on existing vehicles and automated data interpretation, it delivers accurate condition insights, reduces inspection costs, and supports timely maintenance decisions.
Language
- English
Project
- Status: Active
- Funding: $70,000.00
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Contract Numbers:
69A3552348339
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Sponsor Organizations:
University of Texas at Arlington
Box 19308
Arlington, TX United States 76019-0308 -
Managing Organizations:
1040 South River Road
West Lafayette, IN United States 47907 -
Performing Organizations:
1040 South River Road
West Lafayette, IN United States 47907 -
Principal Investigators:
Jahanshahi, Mohammad
- Start Date: 20251001
- Expected Completion Date: 20270531
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Artificial intelligence; Computer vision; Data analysis; Data collection; Machine learning; Monitoring; Pavement management systems; Probe vehicles; Sensors
- Geographic Terms: Texas
- Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation; Vehicles and Equipment;
Filing Info
- Accession Number: 01999116
- Record Type: Research project
- Source Agency: Center for Durable and Resilient Transportation Infrastructure
- Contract Numbers: 69A3552348339
- Files: UTC, RIP
- Created Date: Aug 13 2026 3:31PM