Multi machine approaches for conflict resolution under moving block signalling

Master Thesis (2022)
Author(s)

M.L. Janssens (TU Delft - Mechanical Engineering)

Contributor(s)

V. Reppa – Mentor (TU Delft - Transport Engineering and Logistics)

E. Quaglietta – Mentor (TU Delft - Transport and Planning)

R. Negenborn – Graduation committee member (TU Delft - Transport Engineering and Logistics)

Rob Goverde – Graduation committee member (TU Delft - Transport and Planning)

Dick Middelkoop – Coach

Faculty
Mechanical Engineering
Copyright
© 2022 Mathilde Janssens
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Mathilde Janssens
Graduation Date
23-02-2022
Awarding Institution
Delft University of Technology
Programme
['Mechanical Engineering | Multi-Machine Engineering']
Faculty
Mechanical Engineering
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Abstract

Railway networks are to play an increasingly large role in European transportation. This has boosted the urgency of railway innovations, of which the development of decision support systems for conflict resolution is an important aspect. This research contributes to this development by formulating a suitable mathematical approach for railway networks equipped with moving block signalling systems. Two dispatching actions to reschedule trains are applied, namely retiming and reordering. The designed approach is an extension to an existing method, based on graph theory, that is able to reschedule trains in case of conflict. The novel method uses additional node- and arc types in order to ensure moving block suitability. The new node type enables the possibility to create nodes that are related to trains, rather than infrastructure. The new arc type ensures a continuously safe time interval between two trains in the absence of trackside signals. An optimization problem, with the objective of minimizing the maximum propagated delay, is formulated. Hereafter, the performance is evaluated by a case study in the Rotterdam-The Hague corridor. According to the experimental results, the designed model is able to reduce delay propagation up to 50% for the majority of input situations within 10 seconds of computation time. Overall, the designed method shows promising results, but further research will be necessary to make it applicable in practice.

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