Citi Bike Station Impact Simulator

Methodology and known gaps

This tool is a Concourse research artifact. Not a permit or approval.

What this tool does

Estimates how relocating or resizing a Citi Bike station would affect ridership and rebalancing across a small neighborhood of stations, using public GBFS and S3 trip data.

What this tool does not do

This is not a NYC DOT approval, a Lyft operations tool, or a rebalancing dispatcher. It cannot see rebalancing truck routes, suppressed demand, or pricing history.

Four public-data gaps

Rebalancing truck logs are internal to Lyft.
The product infers rebalancing burden from inventory dynamics, not from observed truck routes. Rebalancing truck movements are not observed and would attenuate these effects in practice.
Suppressed demand (app searches without a trip) is internal to Lyft.
App searches that do not result in a completed trip are not in the public data. Suppressed demand is not observed here.
2019-05 to 2023-06 station-status archive gap.
No public station-status archive covers 2019-05 to 2023-06. Empty/full risk is trained on the OpenBus 2015-2019 window and live GBFS polling from ingest go-live forward. No continuity claim is made across the gap.
Pricing and promotions history is unobserved.
Pricing and promotions history is not observed. It is a confounder that may explain some observed demand shifts.

Neighbor	Distance	Observed post	Model pred.	Naive baseline	Residual (model)	Residual (naive)
9 Ave & W 33 St 2p6fwk5lqrz4	264 m	705.75	50.7	12.0	-655.0	-693.7
W 27 St & 6 Ave licyliwlekds	374 m	0	322.5	282.3	+322.5	+282.3
W 35 St & 9 Ave 7auvxw4ovmdj	341 m	160.77	325.9	260.9

8 Ave & W 33 St

Neighbor redistribution

Sources