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Subway Challenge

How can we better predict subway incident impacts and serve customers?

New York City Transit serves an annual subway ridership of over 1.7 billion, runs nonstop 365 days a year and spans 472 stations. With 5.6 million passengers and over 8,200 trips per weekday on routes with multiple merge points, numerous types of incidents occur each day resulting in over 2,500 delays per weekday. Each delay requires NYCT staff to make complex decisions and communicate with customers in real-time. 

In 2019, the Transit Tech Lab sought applications from companies to better predict subway incident impacts and serve customers. 

See all program results

Challenge Finalists

Axon Vibe

About the Finalists

Axon Vibe mobile app

Axon Vibe

Provides smartphone app technology that enables public transport operators to deliver personalized communications based on users’ commuting behavior

Results: The MTA began a direct commercial engagement with Axon Vibe. Axon Vibe created the Essential Connector app for overnight travel by essential workers. Over 173,000 journeys were planned through the app over six weeks and more than 15,000 for-hire vehicle trips were delivered to essential workers during the overnight subway closures.


Veovo sensor installation at Court St subway station


Uses sensor technologies and cameras to analyze the number of people in an area and predict if crowding conditions in a train station are likely to occur

Results: Veovo installed sensors at the 14th Street Union Square subway station to count the number of passengers using the station, provide data on crowding conditions and measure how long it takes customers to pass from turnstile to platform— calculations previously performed manually. The data can be used to predict future passenger volumes, inform service changes and create an instantaneous warning system to mitigate overcrowding. Veovo has extended access to the dashboard throughout the pandemic for ongoing MTA use.

Transit Tech Lab Challenges

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Metropolitan Transportation Authority

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