Weekday Pull Out Performance is a monthly legacy service performance metric that indicates the percent of required buses and operators available in the AM and PM peak periods.

This dataset provides information on various indicators of safety measured by MTA Bridges & Tunnels, along with targets for some indicators. The indicators are a combination of preventative measures taken to prevent unsafe incidents, as well as occurrences of unsafe incidents.

The 2025-2044 20-Year Needs Assessment outlines capital work the MTA needs to do over the next two decades to keep the region moving. The MTA developed a three-part plan to secure the foundation of the system and ensure another 100 years of service by reconstructing, renewing, and modernizing the system. This dataset includes data on all revenue fleets, except for cars and locomotives used for Metro-North service owned by New Jersey Transit and the Connecticut Department of Transportation that are used in pooled service. The dataset, for each fleet asset, includes the fleet type, its number of units, its useful life, and the years its cars were first and last accepted.

The dataset provides financial information on total positions in Function/Occupational Group related to different MTA Agencies budgetary estimates and actuals. For a more comprehensive view of this data, please use MTA Headcount at data.ny.gov/d/ui26-n8p4.

This dataset provides data showing the number of vehicles (including cars, buses, trucks and motorcycles) using E-ZPass that pass through each of the nine bridges and tunnels operated by the MTA each day.

This dataset consists of a set of polygons that will allow users of New York City Taxi and Limousine Commission data on trip records for taxi and for-hire vehicle trips to determine which trips originate and/or end in a Taxi Zone in the Central Business District and are thus subjected to the CBD Tolling Program. TLC trip record data is available on NYC Open Data in separate datasets each year for yellow taxis, green taxis, for-hire vehicles (FHVs) dispatched by a high-volume for-hire vehicle service (HVFHVs), and other FHVs.

This dataset reflects the monthly number of employee-reported incidents of workplace violence, as defined by New York State Labor Law Section 27-B, against on-duty MTA employees. This dataset divides workplace violence incidents into groupings as reported pursuant to New York State Labor Law Section 27-B. The same data is available in the MTA Workplace Violence Penal Law Incidents dataset, which divides the data according to New York State Penal Law Related Offenses.

The MTA contracts with Transit Wireless WIFI (http://www.transitwirelesswifi.com) to provide WIFI access in its subway locations. Transit Wireless maintains location data where WIFI access is available.

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. This dataset uses the old methodology in which trips were considered on-time if they arrived at the drop-off location no more than five minutes after the requested time. The Drop-off On-Time Performance dataset with the new methodology can be found at https://data.ny.gov/Transportation/MTA-NYCT-Paratransit-Drop-off-On-Time-Performance-/nxai-wcbd/

This dataset provides information on various indicators of safety measured by Metro-North Railroad. The indicators are a combination of preventative measures taken to prevent unsafe incidents, as well as occurrences of unsafe incidents.

The MTA contracts with Transit Wireless WIFI (http://www.transitwirelesswifi.com) to provide WIFI access in its subway locations. Transit Wireless maintains location data where WIFI access is available.

This dataset provides information on various indicators of safety measured by Long Island Rail Road. The indicators are a combination of preventative measures taken to prevent unsafe incidents, as well as occurrences of unsafe incidents.

This dataset lists all Metro-North trains that are delayed, defined as those that are canceled, terminated, substituted by bus service during unplanned circumstances, or arrive at their destination with a delay of a specified number of minutes, the train number, and the branch the train operates on.

The 2025-2044 20-Year Needs Assessment outlines capital work the MTA needs to do over the next two decades to keep the region moving. The MTA developed a three-part plan to secure the foundation of the system and ensure another 100 years of service by reconstructing, renewing, and modernizing the system. This dataset includes data on the fleet inventory for MTA Police, with information on the number of units for each asset type, the useful life of each type, the year the assets were built, and number of years of remaining useful life. It includes all vehicles used by the MTA Police Department that are eligible for capital funding.

This dataset is a list of MTA bus routes that intersect with the CBD, and how each route relates to the CBD (whether it crosses the CBD or is entirely in the CBD). It is meant to be a dimension table that can easily be used with other bus route-level datasets so that data users can easily distinguish between routes serving the CBD and routes that do not.

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.

This dataset consists of a set of polygons that will allow users of New York City Taxi and Limousine Commission data on trip records for taxi and for-hire vehicle trips to determine which trips originate and/or end in a Taxi Zone in the Central Business District and are thus subjected to the CBD Tolling Program. TLC trip record data is available on NYC Open Data in separate datasets each year for yellow taxis, green taxis, for-hire vehicles (FHVs) dispatched by a high-volume for-hire vehicle service (HVFHVs), and other FHVs.

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.

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

This dataset provides information on the actual end-to-end running times for subway trips between their origin and destination stations, including the average, and 25th, 50th (median), and 75th percentile running times in minutes, along with the scheduled end-to-end running time in minutes for these trips.

Data is available for a combination of each month, day type (Weekday, Saturday, Sunday), time period (AM Peak, Midday, PM Peak, Evening, Overnight), subway line, and stop path id (each distinct set of subway stops made by trains). The dataset also includes the direction, number of stops, origin station, and destination station for each stop path, the distance and average actual speed in miles per hour along the stop path, and the actual and scheduled number of trains running along the stop path.

This dataset is a table of each distinct set of stations, or path, made by all normal and extra subway trips that run in service, excepting those that skipped one or more planned stops due to service disruptions.

There is a row for each subway stop made by a stop path. These rows also contain the unique id for each path, the number of stops made by the path, the distance in miles along the path, the origin and destination stations, and the order a stop is in the stop path.

This dataset is a dimension table that provides a list of every bus timepoint and whether it falls within or outside of Manhattan’s Central Business District.

This dataset provides information on the implementation dates of Automated Bus Lane Enforcement (ABLE) and Automated Camera Enforcement (ACE) systems across MTA bus routes. ABLE, launched as a pilot in 2019, and later expanded and rebranded as ACE in 2024, uses cameras mounted on buses to capture vehicles obstructing bus lanes, double parked, or parked illegally at bus stops.

This dataset provides monthly aggregated data for Taxi and For-Hire Vehicle (FHV) trips operating in and around Manhattan's Central Business District (CBD). Each record represents a summary of trips classified by key dimensions, including service type, CBD relation, day type, and time period.

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