Integral capacity and reliability analysis of guided transport systems based on analytical models

分析模型在铁路运力分析中已经成功应用了几十年。除其他事项外，它们还用于确定列车的预定和非预定等待时间。现有模型通常假定所有系统组件的可用性不受限制。列车故障或基础设施故障等中断仅被隐式地视为随机主要延误的来源，即不是由于列车之间的相互依赖造成的延误。故障、维修和维护过程的明确建模超出了当前模型的范围，但它们对于实际能力调查非常重要。考虑到预计交通量的增加以及德国铁路系统需要进行大规模大修，可靠性的重要性将继续增长。通过整合故障和恢复过程，该项目旨在改进目前用于铁路轨道和车站能力调查的模型。目标是开发一个整体的能力和可靠性模型，以确定铁路系统的能力作为中断和基础设施可用性的函数。预计这将有助于深入了解操作程序与铁路基础设施状况之间的相互依存关系，并可能作为改进对未来铁路基础设施项目评估的一种有价值的手段。该项目将依靠目前在铁路网及其组成部分的分析建模方面的研究状况，这主要是由亚琛的工作推动的。在现有方法的潜在更新之后，为了结合排队理论的最新发展，可靠性方面包括故障和恢复过程必须包括在内。这可以使用以下三种建模方法来实现：-根据中断的演变，用条件概率分布取代现有的主要延误概率分布；-延长轨道占用时间，例如，在列车故障或部分故障的情况下，这些故障不会导致部件不可用，但会导致服务质量下降（最大速度降低等）；-系统组件不可用。恢复可用性（可能有限）状态所需的停机时间和服务时间由预定义的（经验）概率分布决定。如果适用，必须考虑诸如负载诱导效应之类的相互依赖性。通过结合这三种方法，铁路系统本身的能力变成了一个随机量，它从根本上取决于故障和恢复过程。未来，该指标可用于推导整个铁路系统的客观质量度量。

Analytical models have been applied successfully in railway capacity analysis for several decades now. Amongst other things, they are used to determine scheduled and unscheduled waiting times of trains. Existing models generally assume the unrestricted availability of all system components. Disruptions such as train malfunctions or infrastructure breakdowns are only considered implicitly as a source of random primary delays, i. e. delays which are not due to interdependencies between trains. The explicit modelling of failure, repair and maintenance processes is beyond the scope of current models, yet they are very important for practical capacity investigations. Given the predicted increase of traffic volume as well as the substantial overhauling required in the German railway system the importance of reliability will continue to grow. By integrating failure and restoration processes this project aims to improve current models used in capacity investigations of both railway tracks and stations. The goal is to develop an integral capacity and reliability model which allows to determine a railway system's capacity as a function of disruptions and infrastructure availability. This is expected to provide insights into the interdependency of operation procedures and the state of the railway infrastructure and could prove valuable as a means of improving the assessment of future railway infrastructure projects.The project will rely on the current state of research in analytical modelling of railway networks and their components, which has notably been driven by work in Aachen. After potential updating of existing methods in order to incorporate recent developments in queueing theory reliability aspects including failure and restoration processes have to be included. This can be achieved using the following three modelling approaches: - Substitution of the existing probability distributions of primary delays by conditional probability distributions depending on the evolution of disruptions, - prolongation of track occupation times, e. g. in case of train malfunctions or partial failures which do not entail the unavailability of components, but result in a degradation of service quality (decrease of maximal velocities, etc.), - unavailability of system components. Downtimes and service times required to restore a state of (possibly limited) availability are determined by predefined (empirical) probability distributions. If applicable, interdependencies such as load induced effects have to be considered. By combining these three approaches the capacity of railway systems itself becomes a random quantity, which is fundamentally dependent on failure and restoration processes. In future, this indicator could be used to derive an objective quality measure for the entire railway system.