Conference article

Transforming Automatic Scheduling in a Working Application for a Railway Infrastructure Manager

Florian H.W. Dahms
Vulpes AI GmbH, Frankfurt am Main, Germany

Anna-Lena Frank
neXt Lab, Timetable and Capacity Management, DB Netz AG, Franfurt am Main, Germany

Sebastian Kühn
neXt Lab, Timetable and Capacity Management, DB Netz AG, Franfurt am Main, Germany

Daniel Pöhle
neXt Lab, Timetable and Capacity Management, DB Netz AG, Franfurt am Main, Germany

Download article

Published in: RailNorrköping 2019. 8th International Conference on Railway Operations Modelling and Analysis (ICROMA), Norrköping, Sweden, June 17th – 20th, 2019

Linköping Electronic Conference Proceedings 69:19, p. 280-289

Show more +

Published: 2019-09-13

ISBN: 978-91-7929-992-7

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

In this article, we present a practical approach for the optimized creation of railway timetables. The algorithms are intended to be used by Deutsche Bahn, Germanys largest railway infrastructure provider. We show how our methods can be used, both for creating a timetable in advance and for answering ad-hoc requests coming in via a digital app. Numerical ex-periments are provided to show that our solution exceeds manual creation of timetables in terms of capacity usage, travel times and the time taken for creating the timetable.

Keywords

railway timetable computation, traffic networks, network optimization

References

No references available

Citations in Crossref