Artificial Intelligence for Pavement Condition Assessment from 2D/3D Surface Images

In phase I, the research team selected/annotated a library of two-dimensional/three-dimensional (2D/3D) pavement surface images in AASHTO standard and developed Artificial Intelligence (AI) Machine Learning (ML) models, using the established dataset. Phase I achieved a Technology Readiness Level (TRL) of 6, significantly below TRL 8 required for implementation. This gap was compounded by the lack of sufficient data for several pavement distress types and a new functional requirement requested by TxDOT to include distress segmentation to the scope of work. In phase II, the research team will prepare more pavement image data provided by TxDOT to achieve the needed diversity on all pavement distress types in the 2D/3D image data library. The research team will revisit the tasks of literature review and AI/ML model selection, revise and optimize the trained models to make improvements, and develop new models to more accurately detect/segment and quantify pavement distresses for TxDOT.

• Supplemental Notes:
  • TxDOT Research Project 0-7150: https://library.ctr.utexas.edu/Presto/project=7150

Language

• English

Project

• Status: Active
• Funding: $499,920.00
• Contract Numbers:

  0-7150-01

• Sponsor Organizations:

  Texas Department of Transportation

  125 E. 11th Street
  Austin, TX  United States  78701-2483
• Managing Organizations:

  Texas Department of Transportation

  125 E. 11th Street
  Austin, TX  United States  78701-2483
• Project Managers:

  Adediwura, Jade

• Performing Organizations:

  Texas State University, San Marcos

  JCK Building, Suite 489
  San Marcos, TX  United States 
• Principal Investigators:

  Wang, Feng

• Start Date: 20260401
• Expected Completion Date: 20280331
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Artificial intelligence; Automatic data collection systems; Computer vision; Condition surveys; Image analysis; Machine learning; Pavement distress
• Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation; Pavements;

Filing Info

• Accession Number: 01995308
• Record Type: Research project
• Source Agency: Texas Department of Transportation
• Contract Numbers: 0-7150-01
• Files: RIP, STATEDOT
• Created Date: Jul 10 2026 5:50PM