Quantifying the effects of running time variability on the capacity of rail corridors

Traffic variability is well known to have a substantial effect on railway capacity. Varying train running and stopping times entail larger train separations and yield non-usable time slots in train timetables and operations. In this paper, we aim to assess the effects of uncertainty in running and dwell times on the capacity of railway corridors in long term planning of rail traffic. Our main focus are commuter and metro systems, where the effects of fluctuations of running and stopping times are particularly pronounced due to dense operations. To analyze the effects of variability in train operations, we propose a new stochastic approach based on a serial queuing network with finite-capacity service stations. The corridor is modeled as a sequence of heavily correlated service stations representing line segments and stations, for which effective throughput, distributions of train running times and service quality are calculated. The performance of the model is tested in a case study for the central link of the mass transit system in Cologne. In addition, an outlook on how the model can be extended to general heavy-rail corridors with different types of train services is provided.