Preparing for Future Pandemics: Subway Crowd anagement to Minimize Airborne Transmission of REspiratory Viruses (Way-CARE)

The goal is to equip public transit communities for greater preparedness and resilience to future pandemics with a crowd management system leveraging sensing, data science, and digital twin. The research
question is: how should crowds be managed in realtime during the pandemic to mitigate risk and ease
the public fear of taking mass transit? This question will be addressed by bridging engineering and scientific models at the intersection of indoor pedestrian mobility, epidemiology, and travel behavior. Rather
than investing in transit infrastructure and services in a short timeframe (which is especially challenging when transit agencies are struggling with staffing shortage and financial crisis), reshaping public transport mobility could be a more viable way.

NSF Link SCC Link


Xuan Sharon Di

Jeffrey L. Shaman Xiaofan (Fred) Jiang Marco Giometto Kai Ruggeri Ester Fuchs V. Faye McNeill


Tackling Crowd Management in Subways During Pandemics

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Strengthening the Pandemic Resilience of the Subway System with a Crowd Management System

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Sharon Di wins NSF grant to work with NYC’s MTA

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