Studentische Arbeiten

Im Zuge der politisch wie gesellschaftlich gewollten Verkehrswende und zur Erreichung der ge­setzten Klimaziele ist eine deutliche Steigerung des Güterverkehrsanteils der Schiene notwendig. Abseits der großen Ballungsräume findet jedoch gegenwärtig oft nur ein sehr kleiner Anteil des Gesamtgüterverkehrs auf der Schiene und der größte Anteil auf der Straße statt. Dies gilt auch im Bereich des Erzgebirgskreises in Sachsen. Daher soll in der anzufertigenden Arbeit untersucht werden, welches Aufkommenspotenzial für den Schienengüterverkehr im südlichen Teil dieses Kreises besteht, mit welchen Leistungsangeboten es erschlossen werden kann und wie die infrastrukturelle Gestaltung sowie die betriebliche Einbindung der dafür vorzusehenden Zugangs­stellen aussehen muss.

Kontakt: Dr.-Ing. Jan Eisold Tel: 0351 463-42390   

Zur Gestaltung und Bemessung von Gleisgruppen können unterschiedliche eisenbahn­betriebs­wissen­schaftliche Ansätze und Verfahren genutzt werden. Neben bestehenden Verfahren auf Basis der Bedienungstheorie und der Simulation werden aktuell auch neuartige Modelle und Verfahren ent­wickelt, welche auf Grundlage der mathematischen Optimierung arbeiten. Mit den einzelnen Verfahren können unterschiedliche Kenngrößen bestimmt werden, die nur bedingt vergleichbar sind und für die nur teilweise bereits wissenschaftlich fundierte Qualitätsmaßstäbe existieren. Es ist daher zu untersuchen, inwieweit verallgemeinerbare Abhängigkeiten zwischen den verschiedenen Kenngrößen bestehen, welche Kenngrößen und Qualitätsmaßstäbe für die Einführung neuartiger Verfahren zweckmäßig erscheinen und wie man für diese belastbare Grenzwerte bestimmen kann.

Kontakt: Dr.-Ing. Jan Eisold Tel: 0351 463-42390   

Problem description

The concept of “flying cars” originated in the early 1900s and has recently re-emerged in public consciousness as urban air mobility (UAM). UAM involves the use of electric vertical take-off and landing (eVTOL) vehicles to provide air transportation services for passengers and goods. These services aim to reduce commuting times for long-distance travel in highly congested areas by utilizing eVTOLs.

The emergence of UAM could significantly and complexly impact existing railway passenger flows. On one hand, UAM could compete with long-distance railway routes due to its high speed and comfort. On the other hand, UAM’s accessibility is limited by infrastructure constraints. Integrating railway stations with UAM vertiports and using railway systems for access and egress to UAM services have been widely discussed. Understanding the interaction between UAM and railway systems can provide valuable insights for decision-makers regarding infrastructure planning, operational scheduling, and policy regulation.

This project aims to develop an integration model of UAM and railway systems to help decision-makers understand their interactions within an integrated system. The model includes supply and demand components:

• Supply Modeling: Develop a new network representation for the integrated system and analyze passenger costs within the network. The model is capable of modelling the service supply of UAM and railway separately and the connections between them.

• Demand Modeling: Propose a passenger assignment model for the integrated network that considers different passenger archetypes. The model takes the origin-destination matrix as input and assigns the passengers to various UAM and railway services.

More information: Thesis proposal - How does urban air mobility affect railway systems? An integration model and policy analysis

Train delays and cancellations occur when disruptive events create an imbalance between system capacity and demand. For example, in the Netherlands, internal factors causing failures (e.g. infrastructure, vehicle) take up to 70% of all disruptions in the network. On average, about 14 of such disruptions occur every day. Some of these disruptions remain even unnoticed by passengers; however, others generate problems spreading all over the network causing many cancelled and heavily delayed trains leading to great dissatisfaction of passengers.

© BSR

Therefore, the question is: how can we predict performance of the system during disruptions? The aim of this project is to study resilience curves (as depicted above) in railway networks and capture the magnitude and spatial impact of delays and cancellations. By using historical railway traffic data, we want to identify representative resilience curves and uncover the interaction between disruption and recovery. This will enable us to predict the future behavior of the system once a disruption occurs. Finally, such prediction system can help railway operators in better estimating and anticipating impacts of future disruptions and thus define best mitigation measures.

More Information: Thesis proposal - Modelling and predicting dynamics of disruption and recovery in railway networks

Contact: Dr. Nikola Bešinović

Power peaks are an undesirable phenomenon occurring in railway networks when multiple electric trains require large amount of power simultaneously, for instance, during acceleration. This phenomenon puts too much pressure on the power grid, which in the worst cases it can result into a blackout, and hence it represents a relevant concern for operators (Regueiro Sánchez, 2021). Furthermore, the high fluctuations in power consumption over time have a significant direct impact on operation costs, even though power peaks are generally very short in time (Albrecht, 2014). Reducing energy consumption is anyways a top priority in sustainability policies in many countries.

One solution for this is fine-tuning timetables to minimize power peaks. Nevertheless, the benefits of adjusted timetables can be lost in situations with train delays in the network. In this work, the goal is to develop a new approach to mitigate anticipated power peaks in real-time by means of train control measures, i.e. traction power limitation and departure time shift, combined with real-time rescheduling.

The goal of this project is to develop a pure optimization approach for the problem of mitigating power peaks in railway networks using train control measures in real-time, possibly including train delays. This optimization approach will be made in the form of a mixed-integer linear program. We consider power limitation and departure time shift as possible train control measures. The problem minimizes the total induced delay while capturing all relevant constraints that model feasible railway traffic (block sections, single and double track sections, technical headways between trains, train conflicts, etc.) (Pachl, 2014), for which we need to use detailed infrastructure models (Radtke, 2014). The approach will be tested in a case study consisting of the line between Giubiasco and Locarno (Canton Ticino) of the Swiss Federal Railways (SBB).

Further information: Thesis proposal - Optimization Approaches for Real-time Mitigation of Power Peaks in Railway Networks using Train Control Measures

Contact: Dr. Nikola Bešinović

Im Schienengüterverkehr nimmt der Einzelwagenverkehr (EV) weiterhin eine signifikante Position ein. Die Steuerung der Wagenströme im Netz erfolgt durch die Einzelwagenverkehrssteuerung (EV-Steuerung). Das primäre Ziel besteht darin, sowohl eine Überlastung von Strecken als auch von Zugbildungsanlagen (ZBA) zu verhindern. Eine Entlastung der Steuerung könnte durch die Ausgestaltung eines robusten Netzwerks erfolgen. Dazu sollen im Rahmen dieser Abschlussarbeit verschiedene Maßnahmen zu einer robusteren Ausgestaltung untersucht werden. Ziel ist es die Abhängigkeit zwischen Leistungsfähigkeit und Robustheit (resilience) zu bestimmen, um somit die Auswirkungen auf die Leistungsfähigkeit quantifizieren zu können.

Kontakt: Daniel Haalboom M.Sc.