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

• Applicant: Professor Dr.-Ing. Nils Nießen
• Subject Area: Traffic and Transport Systems, Intelligent and Automated Traffic
• Term: from 2015 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 283085490

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.

• DFG Programme: Research Grants