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TWO GREAT TASTES IN
ONE CANDY BAR
A Half-Baked Idea About How We Can
Redesign New York Around Citi Bike
Dr. Anthony Townse...
Trips That :
• Are Too Far to Walk ~ 1 mile
• Span Gaps in Transit
• On Heavily Congested Bus Routes (the f***ing M42)
• B...
Now, When Foursquare Dares You to Explore…
Hop on a Citi Bike!
Win Points and Badges!
Grow Your Heat Map!
B.F.D.
What If We Re-Design A Neighborhood
Around These New Tools
How?
1. Mine entire Foursquare check-in database to figure out
...
6
How Can We Test This?
• Look at how mobility patterns evolve for a group
of subjects by looking at personal data for both
...
Bike hack night townsend
Bike hack night townsend
Bike hack night townsend
Bike hack night townsend
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Bike hack night townsend

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Transcript of "Bike hack night townsend"

  1. 1. TWO GREAT TASTES IN ONE CANDY BAR A Half-Baked Idea About How We Can Redesign New York Around Citi Bike Dr. Anthony Townsend NYU Rudin Center for Transportation Policy and Management
  2. 2. Trips That : • Are Too Far to Walk ~ 1 mile • Span Gaps in Transit • On Heavily Congested Bus Routes (the f***ing M42) • Between Spokes on the Wheel • Beyond Your Comfort Zone? Citi Bike’s killer apps: niches in NYC’s transportation system
  3. 3. Now, When Foursquare Dares You to Explore… Hop on a Citi Bike!
  4. 4. Win Points and Badges! Grow Your Heat Map!
  5. 5. B.F.D.
  6. 6. What If We Re-Design A Neighborhood Around These New Tools How? 1. Mine entire Foursquare check-in database to figure out what anchors/attractors entice people out from subway stations 2. Now you can move those out further because you have Citi Bike 3. Use incentives to move those anchors further out 4. Allows you to spread the enormous value of the subway over a larger area 5. Increase density in that larger area 6. BOOM! With no public money spend, you’ve solved New York’s biggest long-term problem: where do we put the next 1 million New Yorkers!
  7. 7. 6
  8. 8. How Can We Test This? • Look at how mobility patterns evolve for a group of subjects by looking at personal data for both systems – A) as they learn to use Foursquare – B) as they learn to use citibike – C) as they learn to use the two together • Do their heat maps grow? Can we leverage that to increase the “ridership shed” of a transit stop? • Maybe one day… mash both entire data sets together
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