Conference article

Optimal Real-time Line Scheduling for Trains with Connected Driver Advice Systems

Ajini Galapitage
Scheduling & Control Group, University of South Australia, Australia

Amie R. Albrecht
Scheduling & Control Group, University of South Australia, Australia

Peter Pudney
Scheduling & Control Group, University of South Australia / Future Industries Institute, University of South Australia, Australia

Peng Zhou
Scheduling & Control Group, University of South Australia, Australia

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

Linköping Electronic Conference Proceedings 69:22, p. 320-339

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Published: 2019-09-13

ISBN: 978-91-7929-992-7

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

Abstract

On most rail networks, if a train is delayed then following trains will not know about the delay until they encounter a trackside signal that tells the driver that the next section of track is still occupied. The train will usually have to slow significantly, which causes delays to propagate back along the track. By using in-cab Driver Advice Systems connected to centralised scheduling systems, train delays can be detected as they happen, and new schedules can be calculated and issued to following trains so that additional delays are avoided. It is impossible to re-schedule the whole rail network at once in real time as the problem is too large. An alternative, more practical approach is micro-scheduling to independently optimise small sections of the network. We describe and illustrate a method that can be used to ensure adequate and energy-efficient train separation. The method can be used during timetable planning to ensure robust timetables or can be used in real time to prevent trains from encountering restrictive signals, smoothing the flow of trains along a corridor.

Keywords

Optimal train control, dynamic rescheduling, line scheduling

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