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.

This dataset provides data on how fast buses are traveling between pairs of subsequent timepoints (the major stops on a bus route) for every bus route in the system. It will provide the average speed in miles per hour between pairs of timepoints, the average travel time in minutes, the road distance in miles, and the number of bus trips for each bus route aggregated by month, day of the week, and hour of day. It also provides the type of bus trip (Local, Limited, SBS, Express, School), the borough of the bus route, the names of the timepoints, their coordinates, and the stop sequence order of the first two timepoints in a pair.

This dataset contains information on customer feedback submitted by riders of the transit system on the MTA’s website. For each piece of feedback provided, it is categorized as a complaint or commendation, and there is information provided for the agency (Buses, Subway, Long Island Rail Road, or Metro-North Railroad), the subject matter, the subject detail, the issue detail, the year, the quarter, and, if applicable, the branch/line/route.

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.

Service alerts in the MTA system are generated to inform passengers of both scheduled and unscheduled events that affect the transit network. These events can range from planned maintenance and construction activities to unexpected incidents such as accidents, track maintenance or planned work and more. The process of creating alerts involves the continuous monitoring of the transit system, including station locations, track statuses, and external factors that might impact service. When a potential disruption is identified, an alert is generated to provide passengers with timely and accurate information about how their travel might be affected.