Roughly 400,000 people ride the L-train with 225,000 of them riding between Brooklyn and Manhattan daily. With the L train set to shut down in 2019 for repairs, solutions have to be created to accomodate daily commuters.
The L Train Challenge was a day-long hackathon organized by Forum for the Future, Dell, NYC Open Data, Collectively, and hosted at Grand Central Tech in New York City.
One of the major concerns of the L train shutdown is the impact on local businesses and real estate. Even global corporations headquartered in the city may be affected, with many workers relying on the L train for their daily commute. The areas on either side of the Canarsie Tunnel – Union Square and Bedford Avenue – are major commercial hubs and attract many people, locals and tourists alike, to their shops, restaurants, and sights.
How might we predict the impact of the L train shutdown on pedestrian flows through the surrounding community? How might we accurately model the daily (or more fine grained if possible) pedestrian volumes at the block or intersection level for the existing conditions? What are the best ways to validate models?
To model pedestrian data, we decided to take a look at exisiting open data from the city of New York to understand where clusters of pedestrians may be found and how they evolve over time. We used available data from citi bike pick up and drop off, MTA subway turnstyle, and taxi and For-Hire Vehicule pick up and drop offs.
Using those data points, we created a D3 vizualization of pedestian flows and cluster over time, specifically around Bedford Avenue and Williamsburg.
With this vizualization, we can now also understand how transportation habits may change over time (before, during and after the L train shutdown) and see which locations become more or less popular areas.
This was a very fun challenge and we are glad we were able to be part of it.