Development of Data Driven Digital Twin for Enhancing Pavement Performance Prediction in South-Central United States

A comprehensive survey conducted by National Cooperative Highway Research Program (NCHRP) Synthesis 501 revealed that many state departments of transportation (DOTs) update their pavement performance models only every 2 to 5 years, with some agencies updating even less frequently. Such lengthy update cycles mean that the models often fail to reflect recent trends in traffic loading and material performance, leading to outdated forecasts that diminish the accuracy and usefulness of maintenance and rehabilitation planning. The primary objective of this project is to develop a data-driven Digital Twin (DT) framework based on pavement management system data that will regularly update Artificial Intelligence (AI)-based performance models for pavements in Louisiana. This framework aims to help state agencies make smarter, more accurate maintenance decisions while reducing costs over time. The proposed Digital Twin platform will focus on the interstate network in Louisiana, given its importance to the state and its wide implications on mobility and freight movement. The work will be divided into five tasks: (1) collect and preprocess pavement management system data for the interstate network, (2) development of digital twin framework, (3) forecast future pavement conditions in digital twin platform, (4) suggest potential maintenance strategies in the digital twin platform, and (5) prepare final report. The project will address the growing need for innovative approaches that can dynamically integrate diverse datasets, learn from both historical and emerging patterns, and provide transportation agencies with actionable, real-time insights. Digital twin technology offers this dynamic capability by enabling a shift from reactive maintenance toward predictive and proactive strategies.

• Record URL:
  • https://www.sptc.org/cy3-lsu-03

Language

• English

Project

• Status: Active
• Funding: $70,000.00
• Contract Numbers:

  69A3552348306 (CY3-LSU-03)

• Sponsor Organizations:

  Southern Plains Transportation Center

  University of Oklahoma
  202 W Boyd St, Room 213A
  Norman, OK  United States  73019

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  University of Oklahoma, Norman

  School of Civil Engineering and Environmental Science
  202 West Boyd Street, Room 334
  Norman, OK  United States  73019
• Project Managers:

  Ghasemi, Hamid

• Performing Organizations:

  Louisiana State University

  3660G Patrick F. Taylor Hall
  Civil and Environmental Engineering
  Baton Rouge, LA  United States  70803
• Principal Investigators:

  Elseifi, Mostafa

• Start Date: 20260101
• Expected Completion Date: 20270101
• Actual Completion Date: 0
• USDOT Program: UTC

Subject/Index Terms

• TRT Terms: Artificial intelligence; Data analysis; Digital twins; Forecasting; Maintenance management; Pavement management systems; Pavement performance
• Geographic Terms: Louisiana
• Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation; Pavements; Planning and Forecasting;

Filing Info

• Accession Number: 01976866
• Record Type: Research project
• Source Agency: Southern Plains Transportation Center
• Contract Numbers: 69A3552348306 (CY3-LSU-03)
• Files: UTC, RIP
• Created Date: Jan 23 2026 1:50PM