A Machine Learning and Statistical Analysis Framework for Enhanced Engineer's Estimate Accuracy in Highway Infrastructure Projects, Phase I

State Transportation Agencies (STAs) rely on accurate engineer's estimates for budget allocation and contractor bid evaluation in highway projects. However, recent assessments reveal significant inaccuracies, with up to 25% deviations between engineers' estimates and awarded bids in the Wyoming Department of Transportation (WYDOT) in 2019. These deviations also resonate with similar findings published by other STAs. Challenges persist due to poor data quality and variations in estimating methods. This study aims to evaluate WYDOT's engineer's estimates' accuracy against historical bid data and assess consequences on project performance. Methodologically, a literature review and questionnaire survey will inform quantitative analysis of survey data and statistical analysis of bid tabulation data. By enhancing engineer's estimate accuracy, this research seeks to minimize budget deviations, improve project performance, and promote efficiency and transparency in transportation project planning and execution.


  • English


  • Status: Active
  • Funding: $103220
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

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

    Center for Transformative Infrastructure Preservation and Sustainability

    North Dakota State University
    Fargo, ND  United States  58108
  • Project Managers:

    Tolliver, Denver

  • Performing Organizations:

    University of Wyoming, Laramie

    Department of Civil and Architectural Engineering
    1000 East University Avenue
    Laramie, WY  United States  82071
  • Principal Investigators:

    Abdelaty, Ahmed

  • Start Date: 20240607
  • Expected Completion Date: 20260606
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program
  • Source Data: CTIPS-015

Subject/Index Terms

Filing Info

  • Accession Number: 01922769
  • Record Type: Research project
  • Source Agency: Center for Transformative Infrastructure Preservation and Sustainability
  • Contract Numbers: 69A3552348308
  • Files: UTC, RIP
  • Created Date: Jun 26 2024 12:25PM