Determination of Pavement Surface Type

An accurate knowledge of the pavement surface type is fundamental to efficient pavement management. Knowledge of the surface type is important for tracking the performance of different surfaces and predicting skid numbers and noise. While surface type is already a data element in Pavement Analyst, it lacks the necessary accuracy. Previous Texas Department of Transportation (TxDOT) projects have attempted to populate this field by combining different data sources, but the results have not been implemented because of lack of accuracy. Laser, video, and 3D technologies have made it possible to scan large networks and obtain full coverage on an annual basis. Artificial intelligence and these technologies can be used to predict surface type with an accuracy higher than 90%. This research project will utilize the latest technologies to develop equipment and a methodology for determining surface type. To accomplish this goal, the research team will conduct a literature review to identify potential technologies, evaluate them and determine the technology with the highest potential, develop a set of technical specifications for the system, set a target for the degree of accuracy, develop an experimental design, use the system developed to determine surface type, evaluate its performance, and assemble and deliver a final system.

• Record URL:
  https://library.ctr.utexas.edu/Presto/project=7139

Language

• English

Project

• Status: Active
• Funding: $414535
• Contract Numbers:

  0-7139

• 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:

  Pridgen, Shelley

• Performing Organizations:

  Center for Transportation Research

  3925 W. Braker Lane
  Austin, TX  United States  78759
• Principal Investigators:

  Prozzi, Jorge

• Start Date: 20220901
• Expected Completion Date: 20240831
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Accuracy; Artificial intelligence; Data collection; Pavement management systems; Performance based specifications; Surface course (Pavements)
• Subject Areas: Data and Information Technology; Highways; Materials; Pavements;

Filing Info

• Accession Number: 01863334
• Record Type: Research project
• Source Agency: Texas Department of Transportation
• Contract Numbers: 0-7139
• Files: RIP, STATEDOT
• Created Date: Nov 3 2022 2:20PM