Using Real-Time Data to Detect Delays and Improve Customer Communications at New York City Transit

Document Type

Journal Article

Publication Date


Subject Area

place - north america, place - urban, mode - bus, mode - rail, mode - subway/metro, technology - intelligent transport systems, planning - signage/information


Real-Time Data, delays, Transit Visualization


New York City Transit operates one of the world’s largest transit systems, and it can be difficult for the agency’s communications team to keep track of the numerous service disruptions that need to be communicated to customers. This paper introduces the Transit Visualization tool, which processes real-time train location data to automatically identify areas of the system where service may not be living up to customers’ expectations. Specifically, the Transit Visualization is set up to identify areas of the system where trains are operating at lower-than-normal speeds and areas of the system where there are atypically long gaps between trains. Any occurrence of slow speeds or long gaps is assigned a severity level (Moderate, Severe, or Very Severe) to indicate the magnitude of the problem. An overview of any problems the application identifies is shown on an interactive web map, as well as on several easy-to-digest summary tables. The map also displays real-time locations of trains and buses throughout the transit system. The Transit Visualization has been successfully rolled out to the subways communications team and has become a mission-critical tool for communicating delays to customers, especially during the course of the COVID-19 pandemic.


Permission to publish the abstract has been given by SAGE, copyright remains with them.