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

几十年来，分析模型在铁路运力分析中得到了成功的应用。除其他事项外，它们用于确定列车的预定和非预定等待时间。现有的模型通常假设所有系统组件的可用性不受限制。中断，如列车故障或基础设施故障，只被认为是隐含的随机主要延误的来源，即。e.不是由于列车之间的相互依赖而造成的延误。故障，维修和维护过程的明确建模超出了当前模型的范围，但他们是非常重要的实际能力的调查。考虑到预计的交通量增长以及德国铁路系统需要进行的大量大修，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容量调查的模型。其目标是开发一个综合能力和可靠性模型，该模型允许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运营程序的相互依赖性和铁路基础设施的状况，并可能证明是一种宝贵的手段，以改善对未来铁路基础设施项目的评估，该项目将依赖于铁路网及其组成部分的分析建模研究的现状，这主要是由亚琛的工作推动的。现有方法的潜在更新后，为了将最近的发展，在嵌入理论的可靠性方面，包括故障和恢复过程中，必须包括在内。这可以使用以下三种建模方法来实现：-由取决于中断的演变的条件概率分布替代主要延迟的现有概率分布，-轨道占用时间的延长，e. G.在列车故障或部分故障的情况下，这些故障不需要组件的不可用性，但会导致服务质量的下降（最大速度的降低等），- 系统组件不可用。恢复（可能有限的）可用性状态所需的停机时间和服务时间由预定义的（经验）概率分布确定。如适用，必须考虑相互依赖性，如荷载诱导效应。通过结合这三种方法，铁路系统本身的能力成为一个随机量，这是从根本上依赖于故障和恢复过程。日后，这个指标可用作量度整个铁路系统的客观质素。

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.