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

基于分析模型的引导运输系统整体容量和可靠性分析

基本信息

批准号：
283085490
负责人：
Professor Dr.-Ing. Nils Nießen
金额：
--
依托单位：
Lehrstuhl für Schienenbahnwesen und Verkehrswirtschaft
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2015
资助国家：
德国
起止时间：
2014-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/283085490?language=en
关键词：
Integral capacity reliability analysis guided

项目摘要

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.

几十年来，分析模型已成功应用于铁路容量分析。除其他外，它们还用于确定火车的计划和非计划等待时间。现有模型通常假设所有系统组件的可用性不受限制。火车故障或基础设施故障等中断仅被隐含地视为随机主要延误的来源，即。 e.非由于列车之间的相互依赖性造成的延误。故障、维修和维护过程的显式建模超出了当前模型的范围，但它们对于实际容量调查非常重要。鉴于预计交通量的增加以及德国铁路系统所需的大规模检修，可靠性的重要性将继续增长。通过整合故障和恢复过程，该项目旨在改进铁路轨道和车站容量调查中使用的当前模型。目标是开发一个完整的容量和可靠性模型，该模型可以根据中断和基础设施可用性来确定铁路系统的容量。预计这将有助于深入了解运营程序和铁路基础设施状况的相互依赖性，并可能作为改进未来铁路基础设施项目评估的一种手段而发挥重要作用。该项目将依赖于铁路网络及其组成部分的分析建模的当前研究状况，这主要是由亚琛的工作推动的。在对现有方法进行潜在更新以纳入排队论的最新发展之后，必须包括可靠性方面，包括故障和恢复过程。这可以使用以下三种建模方法来实现： - 根据中断的演变，用条件概率分布替换主要延迟的现有概率分布， - 轨道占用时间的延长，例如。 g。如果列车发生故障或部分故障，不会导致组件不可用，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（可能有限）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。如果适用，必须考虑诸如负载引起的影响等相互依赖性。通过将这三种方法结合起来，铁路系统本身的容量就变成了一个随机量，这从根本上取决于故障和恢复过程。将来，该指标可用于得出整个铁路系统的客观质量衡量标准。