Deep Learning-Based Pavement Condition Monitoring for Coastal Highways
Principal Investigators
Feng Wang, Texas State University
Project Dates
September 1, 2023 to December 10, 2025
Coastal roads face constant stress from saltwater, extreme weather, tides, and wind-driven water, making condition monitoring both critical and difficult. Traditional image-based pavement assessment tools lose accuracy in these environments. This project developed AI and machine learning models trained specifically on coastal pavement conditions to detect and classify pavement distress more accurately. The research produced a library of coastal pavement surface images, validated models for real-world conditions, and a technology transfer plan to help highway agencies adopt and implement the tools.