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
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Contract Numbers:
69A3551847102
CAIT-UTC-REG68
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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 08625Center for Advanced Infrastructure and Transportation
Rutgers University
100 Brett Road
Piscataway, NJ United States 08854-8058 -
Project Managers:
Delwadi, Nisharg
Szary, Patrick
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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
- TRT Terms: Decision support systems; Machine learning; Project delivery
- Subject Areas: Administration and Management; Planning and Forecasting; Transportation (General);
Filing Info
- Accession Number: 01866252
- Record Type: Research project
- Source Agency: Center for Advanced Infrastructure and Transportation
- Contract Numbers: 69A3551847102, CAIT-UTC-REG68
- Files: UTC, RIP
- Created Date: Nov 30 2022 2:24PM