The document discusses research into the impact of maintenance activities on New York City subway and taxi ridership. It finds that the over 100-year-old MTA subway system requires 2500+ scheduled maintenance activities per year, which can cause partial or full station shutdowns. This leads to passenger inconvenience and a switch to other transit modes. The research objectives are to examine if maintenance reduces subway ridership, identify causes of ridership loss, and examine if taxi ridership surges in affected areas. Preliminary analysis of 3 lines found a ridership loss of over 1.45 million riders due to maintenance over one year. Next steps include expanding the analysis and quantifying impacts on taxi ridership.

1. Impact of MTA
Maintenance
Activities on
Subway and
Taxi Riderships
in NYC

2. Introduction:
● New York City MTA Subway system is more than 100 years old.
● System breakdown lead to significant delays in system; the cost of subway
delays in lost work time translates to $1.23 million daily.
● Tracks and Signals are old and need constant maintenance.
● 2500+ Scheduled Maintenance activity takes place every year to keep
system healthy.
● Maintenance causes a complete or partial shutdown of the subway
services at various stations.
● Due to these frequent maintenance, commuters face inconvenience, and
they have to switch to other modes for transportation.

3. Research Objectives:
Research Outcomes:
1. To examine whether maintenance leads to loss in subway ridership or not?
2. What are the leading causes for loss in ridership due to maintenance on different
subway lines?
3. To examine whether taxi ridership experience surge in taxi zones where
maintenance was present?
4. How can we quantify this surge in taxi ridership?
The outcomes of this research can benefit majorly two clients:
● MTA: To understand about the quantum of loss in ridership due to maintenance,
and identify key focus areas to reduce this loss.
● Taxi Companies: To learn about a new potential way to gather demand, and
methods to integrate this demand with the existing supply chain.

4. Methodology:
● All the datasets used are available through online open-sources :
○ MTA Turnstile Data.
○ MTA Real-Time GTFS Feed Data.
○ NYC Taxi Data.
● MTA subway Ridership can be quantified using the equation:
○ Ridership = f(trend,periodicity) + f(maintenance features) + f(normal features)
○ Ridership from MTA Turnstile Data
○ Parse MTA Real-Time GTFS Feed Data for Maintenance Features
● Remove trend, periodicity by rolling mean and standard deviation standardization. Model
ridership with maintenance features as input using tree based decision models.

5. POC Analysis on F, N and R Lines
● Data used: 106 Stations x 45 weeks x 2 days ~ 9340 data points( Station+Date Combination)

6. Results
● Total loss in ridership due
to maintenance on F, N &
R line from October 2017 to
October 2018 is 1.45
Million riders.

7. Next Steps:
● Scale the analysis: Include all the
stations in NYC Subway System
and evaluate impact on all the 23
lines.
● Include weekday maintenance and
system delays in the analysis.
● Understand the impact on taxi
ridership
● Quantify the impact on taxi
ridership.

8. Thank You

9. Impact of Maintenance on Subway
Network Connections:
● Severity of impact of maintenance
depends upon the number of station’s
links affected by the maintenance.
● Corner nodes: experience similar or
increased ridership in comparison to
regular days.
● We term these data points as
Maintenance with Entry Gain.