With ridership near modern highs, New York City Transit’s (NYCT) subway network frequently operates at or near capacity. This makes maintaining a high-quality service both challenging, due to the lack of “slack,” and exceptionally important, due to the large number of riders affected by disruptions. To this end, train dispatchers constantly monitor the network and adjust service to respond to delays. This paper presents a decision support system developed by NYCT which uses real-time train movements and historical ridership information to provide dispatchers with recommendations for holds and station skips in real time. The system uses heuristic headway criteria to determine hold or skip candidate trains, and then estimates the net passenger time savings of each potential hold or skip using estimated origin–destination flows and basic assumptions about passenger behavior. Potential actions that meet a passenger benefit threshold are recommended, and communicated to dispatchers with a simple dashboard. A pilot implementation of the system has been in use at NYCT’s Rail Control Center (RCC) for several months, though many details of the system are still in development. Initial observations indicate the system is helping dispatchers manage train service more effectively, producing large passenger time savings.
Transportation Research Record Journal of the Transportation Research Board
2672(8):036119811879211
