Development of an ML-based Georgia Pavement Structural Condition Evaluation System

The objective of this research is to develop a machine learning-based Georgia Pavement Structural Condition Evaluation System (ML-GPSCES) that reliably and accurately evaluates and categorizes pavement structural health conditions by processing and analyzing data collected by Georgia Department of Transportation (GDOT) using advanced sensing technologies, including TSD, ground penetrating radar (GPR), and 3D laser technology.

Language

• English

Project

• Status: Active
• Funding: $250000
• Contract Numbers:

  GDOT RP 23-04

• Sponsor Organizations:

  Georgia Department of Transportation

  One Georgia Center
  600 West Peachtree Street, NW
  Atlanta, GA  United States  30308
• Project Managers:

  Jordan, Kamari

• Performing Organizations:

  Georgia Tech Research Corporation

  505 Tenth Street
  Atlanta, GA  United States  30332-0420
• Principal Investigators:

  Tsai, Yichang (James)

• Start Date: 20240122
• Expected Completion Date: 20260122
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Machine learning; Pavement maintenance; Structural health monitoring
• Geographic Terms: Georgia
• Subject Areas: Highways; Maintenance and Preservation; Pavements;

Filing Info

• Accession Number: 01908277
• Record Type: Research project
• Source Agency: Georgia Department of Transportation
• Contract Numbers: GDOT RP 23-04
• Files: RIP, STATEDOT
• Created Date: Feb 15 2024 3:19PM