Physics-Informed AI-Enhanced Multimodal Modeling and Governance: Improving Safety and Resilience for Data-Limited Transit Corridors
Limited sensor coverage and fragmented, mode-specific modeling infrastructure hinder the holistic monitoring of modern transportation networks. The resulting data blind spots prevent current models from capturing dynamic, cross-modal dependencies, where a disruption in one mode, such as a metro closure, triggers cascading surges in others, forcing planners and Traffic Management Centers to rely on reactive, siloed strategies. To improve the state of the art, this project proposes a Virtual Sensor paradigm driven by physics-informed generative artificial intelligence (AI). By integrating fundamental transportation physics with generative deep learning, the framework synthesizes high-fidelity data for sensor-sparse regions by inferring correlations from existing sensing infrastructure, creating cost-effective virtual data streams that simulate physical sensors and provide more complete multimodal network data for real-time operations and long-term planning. The project also evaluates the policy and governance dimensions of integrating emerging AI use cases, such as AI-generated data, into the Delaware Department of Transportation (DelDOT)’s planning, design, and operations.
Language
- English
Project
- Status: Active
- Funding: $55,000.00
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Contract Numbers:
69A3552348303
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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:
Safety and Mobility Advancements Regional Transportation and Economics Research Center
Morgan State University
Baltimore, MD United States -
Performing Organizations:
Safety and Mobility Advancements Regional Transportation and Economics Research Center
Morgan State University
Baltimore, MD United States -
Principal Investigators:
Faghri, Ardeshir
Nejad, Mark
Barnes, Philip
Pierce, Andrea
- Start Date: 20260801
- Expected Completion Date: 20270730
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Advanced traffic management systems; Machine learning; Multimodal transportation; Public transit; Traffic safety; Transportation corridors
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Public Transportation; Safety and Human Factors;
Filing Info
- Accession Number: 01997686
- Record Type: Research project
- Source Agency: Sustainable Mobility and Accessibility Regional Transportation Equity Research Center
- Contract Numbers: 69A3552348303
- Files: UTC, RIP
- Created Date: Jul 30 2026 4:41PM