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Journal Article

Citation

Galapitage A, Albrecht AR, Pudney P, Vu X, Zhou P. J. Rail. Transp. Plan. Manag. 2018; 8(1): 29-41.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.jrtpm.2018.02.003

PMID

unavailable

Abstract

Many railways around the world are using driver advice systems to provide real-time advice to drivers on how to control their trains to stay on time with minimum energy use. Standalone driver advice systems use pre-prepared timetables. More recently, driver advice systems are being developed with data connections to central control systems, to allow real-time updating of schedules. Dynamic rescheduling of trains in response to disruptions can be an intractable problem for large networks. Localised junction scheduling, combined with driver advice systems, can reduce time lost at individual junctions by ensuring that trains arrive at the junction with sufficient headways to ensure smooth traffic flows. We have developed a system that combines real-time driving advice calculation with real-time junction scheduling to reduce delays at junctions, and have simulated the operation of this junction scheduling system at Neasden Junction in the UK, where about 10% of trains are slowed at the junction. When an express train was delayed by three minutes early in its journey, the result would have been three trains arriving at the junction within a 60 s interval. The junction scheduling system detected the potential conflicts 20 min before they occurred, and calculated new target times at the junction to resolve the conflicts. The connected driver advice systems responded by calculating new optimal speed profiles to meet the revised arrival times.


Language: en

Keywords

Dynamic rescheduling; Junction scheduling; Optimal train control

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