Real-Time Decision Support System for Transportation Infrastructure Management under a Hurricane Event
CAIT project no.: CAIT-UTC-REG51
Fiscal Year: 2020/2021
Principal investigator(s): Teng Wu, Ph.D. (PI), SUNY-University at Buffalo
Kallol Sett, Ph.D. (Co-PI), SUNY-University at Buffalo
Performing organization(s): SUNY-University at Buffalo
Managing organization: Rutgers CAIT
In cooperation with: Arup
Partner project manager: Matt Carter, Global Lead, Long-Span Bridges
Supported by: USDOT-OST-R
UTC, grant, or agreement no.: 69A3551847102
This project will lay the groundwork for the development of a real-time decision support system for transportation infrastructure management under a hurricane event. Beginning with a systematic review of current decision-making practices, this project will investigate hurricane impacts on the critical infrastructures and effects of various traffic control policies on traffic network performance. The project will then identify the optimal traffic control policy to minimize hurricane-induced losses.
The intended outcome of the project is to deliver a tool to rapidly identify optimal traffic control policies under hurricane events. This platform will be implemented using three integrated modules, namely, 1) traffic network simulation, 2) traffic control policy evaluation, and 3) identification of the optimal control policy. The direct benefit of the developed platform to the transportation community (and planners/emergency responders) would be immense. It could be used in real time by first responders in hurricane events, by DOTs and state and local Offices of Emergency Services for scenario planning, and by engineers and planners for risk assessment.