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

机译:量化运行时间变异对铁路走廊能力的影响

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摘要

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.
机译:众所周知,交通可变性对铁路容量产生了重大影响。不同的火车运行和停止时间需要更大的火车分离,并在列车时刻表和操作中产生不可用的时隙。在本文中,我们的目的是评估不确定性在铁路走廊在铁路交通长期规划中的运行和停留时间的影响。我们的主要重点是通勤和地铁系统,由于浓密的操作,运行和停止时间的波动的影响特别明显。为了分析火车操作中变异性的影响,我们提出了一种基于串行排队网络的新型随机方法,其有限能力服务站。走廊被建模为代表线段和站的一系列重相关的服务站,计算有效吞吐量,列车运行时间和服务质量的分布。在科隆批量交通系统的中央环节的情况下测试了该模型的性能。此外,还提供了如何将模型延伸到具有不同类型列车服务的一般重型铁路走廊的展望。

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