CIAM-UTC-REG49
Research Team
PI: Monty Abbas, Virginia Tech
Co-PI: Elise Miller-Hooks, George Mason University
Funding Sources
Virginia Tech Federal Share — $75,000
George Mason University Federal Share — $37,500
Virginia Tech Match Share — $75,000
George Mason University Match Share — $37,500
Total Project Cost — $225,000
Agency ID or Contract Number
69A3551847103
Start and End Dates
01/04/2022 — 07/03/2023
Project Description
In this project, we will build on knowledge gained from this earlier work and our expertise in artificial intelligence (AI), stochastic optimization, and Markovian processes to develop a practical, deployable tool to support decision-makers not only in long-term investment planning but also short-term maintenance and rehabilitation activities that are equally important to protecting our roadways and other critical infrastructure components and lifelines. The developed tool will also account for societal costs due to changes in demographics and land use from SLR, long-term effects of flooding resettlement, and other societal and economic challenges.
The work has three key objectives:
- Development of a multi-objective, meta-simulation framework that can be used to evaluate the life-cycle cost and economic benefits for specific rehabilitation and/or infrastructure climate protection policies
- Development of metrics, including equity-inspired metrics, to capture the current infrastructure serviceability level and detect and emphasize deteriorated conditions of roadway segments and infrastructure installations/land-use changes that may positively or negatively impact road users and local inhabitants inequitably across different socioeconomic groups
- Development of AI-based learning and optimization methods for determination of optimal roadway system rehabilitation and improvement policies, utilizing the meta-simulation framework, while considering feasible alternate options