Assessing public transit performance using real-time data: spatiotemporal patterns of bus operation delays in Columbus, Ohio, USA

Public transit vehicles such as buses operate within shared transportation networks subject to dynamic conditions and disruptions such as traffic congestion. The operational delays caused by these conditions can propagate downstream through scheduled transit routes, affecting system performance beyond the initial delay. This paper develops an approach to measuring and assessing vehicle delay propagation in public transit systems. We fuse data on scheduled bus service with real-time vehicle location data to measure the originating, cascading and recovery locations of delay events across space with respect to time. We integrate the resulting patterns to construct stop-specific delay propagation networks. We also analyze the spatiotemporal patterns of propagating delays using parameters such as 1) transit line-based network distance, 2) total propagating delay size, and 3) distance decay. We apply our methodology using publicly available schedule and real-time location data from the Central Ohio Transit Authority (COTA) public bus system in Columbus, Ohio, USA. We find that delay initiation is spatially and temporally uneven, concentrating on specific stops in downtown and specific suburban locations. Core stops play a critical role in propagating delays to a wide range of connected stops, eventually having a disproportional impact on the on-time performance of the bus system.