CDTA is a public transportation authority in the Capital Region. This dataset presents information that reflects the organizations performance levels. This dataset includes customer boarding’s, miles operated, accidents, preventative maintenance inspections, and complaints.

This dataset includes ridership for the eight transportation subsidiaries managed by the Rochester Genesee Regional Transportation Authority. Ridership includes the total number of riders, passengers or boardings.

This dataset includes ridership for the eight transportation subsidiaries managed by the Rochester Genesee Regional Transportation Authority. Ridership includes the total number of riders, passengers or boardings.

NYCT Paratransit ridership measures both total trips, the count of trips provided to registered NYCT Paratransit clients in a given month, and total ridership, the count of personal care attendants (PCAs) and guests who join clients on the trips.

This dataset provides subway ridership estimates on an hourly basis by subway station complex and class of fare payment.

This dataset provides bus ridership estimates on an hourly basis by bus route and class of fare payment.

This dataset provides the load percentage for each express bus route at its maximum load point (the bus stop where the highest number of passengers are on the bus) by direction, hour, day type (weekday, weekends and holidays), aggregated by week.

Quarterly estimated Fare Evasion rate for Subways with margin of error. Rate estimated using surveys conducted by traffic checkers and applying stratified sampling.

These metrics reflect the quality of fare collection by LIRR conductors, as observed by MTA Auditors.

This metric tracks the monthly dollar amount of chargebacks and the percentage of transactions that have been disputed with the customer receiving a refund.

This retired dataset contains information on entry/exit values for individual control areas and is posted purely for archival purposes. More detailed subway ridership data is now supported through the Subway hourly dataset (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s).

Pickup On-Time Performance (OTP) measures the quality of provider service, comparing actual to promised pickup time. Trips are considered on-time if they arrive no more than 20 minutes after the promised time. This dataset also includes trips that arrive within 15 and 30 minutes of the promised time.

Max Ride Time Performance presents the percentage of trips performed with Access-A-Ride’s established max ride time standards between 2018 and 2023. This dataset is now retired as this metric can be calculated from MTA NYCT Paratransit Ride Time (https://data.ny.gov/Transportation/MTA-NYCT-Paratransit-Ride-Time-Beginning-2017/wtm4-vjm7/).

Drop-off On-Time Performance (OTP) measures the quality of provider service, comparing actual to customer-requested drop-off time for trips scheduled with an appointment time. Trips are considered on-time if they are no more than 30 minutes early, and no later than the appointment time.

This archival dataset shows the number of MetroCard swipes made each week by customers entering each station of the New York City Subway, Staten Island Railway, PATH, AirTrain JFK and the Roosevelt Island Tram, broken out to show the relative popularity of the various types of MetroCards. Please use the subway hourly ridership dataset (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s/) for up-to-date data which includes OMNY fares

Ride Time measures customer trip duration. Actual vs. Scheduled presents travel time variance, Average Travel Time presents the average actual trip duration, and Max Ride Time by trip distance category.

This retired dataset contains information on entry/exit values for individual control areas and is posted purely for archival purposes. More detailed subway ridership data is now supported through the Subway hourly dataset (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s).

The bus fare evasion (BFE) rate is the estimated percentage of riders who illegally board buses. It is calculated systemwide quarterly using Automated Passenger Counters. Rates are calculated and reported separately for Local/Limited, Express and Select Bus Service. Prior to Q1 2020, fare evasion was estimated using surveys conducted by traffic checkers.

The daily ridership dataset provides systemwide ridership and traffic estimates for subways (including the Staten Island Railway), buses, Long Island Rail Road, Metro-North Railroad, Access-A-Ride, and Bridges and Tunnels, beginning 3/1/2020, and provides a percentage comparison against a comparable pre-pandemic date.

This indicator shows the number of subway and bus journeys made each month by passengers using Reduced-Fare MetroCards between 2018 and 2023. This dataset is now retired, with data on reduced-fare usage of the transit system available in the hourly bus (https://data.ny.gov/Transportation/MTA-Bus-Hourly-Ridership-Beginning-February-2022/kv7t-n8in/) and subway (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s/) ridership datasets.

This retired dataset contains information on entry/exit values for individual control areas and is posted purely for archival purposes. More detailed subway ridership data is now supported through the Subway hourly dataset (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s).

This retired dataset contains information on entry/exit values for individual control areas and is posted purely for archival purposes. More detailed subway ridership data is now supported through the Subway hourly dataset (https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-Beginning-February-202/wujg-7c2s).

This dataset provides an estimate of subway travel patterns based on scaled-up OMNY and MetroCard return swipe data. It provides estimated passenger volumes for all populated origin-destination (O-D) pairs aggregated by month, day of the week, and hour of day. It also provides the name, ID, and approximate latitude and longitude of the origin and destination subway complexes.