A Machine Learning Decision-Support System for Selecting Optimal Innovative Project Delivery Methods for Bundled Transportation Projects

One of the earliest and most essential decisions that must be made in any infrastructure project is the selection of which project delivery method (PDM) to use. Since the choice of the PDM will dictate the language in the contract and the timing of its signing; state DOTs, local agencies, and tribal governments must make such decision early on during the pre-planning phase of the project. The primary goal of this proposal is to develop a data-driven decision-support system to help state departments of transportation (DOTs), local agencies, and tribal governments select the best project delivery method (PDM) for each bundled contract by leveraging machine learning algorithms, while also taking into consideration the specific goals of each bundle. The intended outcome of the project is to assist DOTs, local agencies, and tribal governments in utilizing alternative, innovative contracting methods in the development of project bundling projects, programs, and initiatives to reduce costs and streamline design, construction, and maintenance activities. It is expected that the research outcomes will present a structured approach to assist agencies in making project delivery decisions, assist agencies in determining if there is a dominant or optimal choice of a delivery method, and provide documentation of the selection decision.

Language

  • English

Project

  • Status: Active
  • Funding: $180001
  • Contract Numbers:

    69A3551847102

    CAIT-UTC-REG68

  • 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:

    New Jersey Department of Transportation

    1035 Parkway Avenue
    Trenton, NJ  United States  08625

    Center for Advanced Infrastructure and Transportation (CAIT)

    Rutgers University
    100 Brett Road
    Piscataway, New Jersey  United States  08854-8058
  • Project Managers:

    Delwadi, Nisharg

    Szary, Patrick

  • Performing Organizations:

    New Jersey Institute of Technology (NJIT)

    Department of Civil & Environmental Engineering
    University Heights
    Newark, NJ  United States  07102-1982
  • Principal Investigators:

    Assaad, Rayan

  • Start Date: 20220701
  • Expected Completion Date: 20230630
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01866252
  • Record Type: Research project
  • Source Agency: Center for Advanced Infrastructure and Transportation (CAIT)
  • Contract Numbers: 69A3551847102, CAIT-UTC-REG68
  • Files: UTC, RIP
  • Created Date: Nov 30 2022 2:24PM