To become more competitive, railways are developing methods and technologies that enable cost reduction, higher capacity, better punctuality and greater sustainability. The authors of this study address the last two objectives and propose a method that can be used to minimise the impact of a single delay on the system by reducing both the deviation from timetabled arrival at timing points and the energy consumed by trains. The technique uses a combined macro‐ and microscopic level approach in an optimisation algorithm to calculate the maximum speed a train should travel at on different sections of its route, so that the train meets time constraints and saves energy. The algorithm interacts with the traffic management system to obtain the applicable time constraints. The initial results from a case study based on a single‐track railway line show that applying this method to a freight train that needs to pass a late running passenger train at a loop and to arrive on time at its last station allows a 9% reduction in energy use by comparison with a situation where the freight train trajectory is not adjusted as a function of the actual traffic conditions.
Delay management and energy consumption minimisation on a single‐track railway
IET Intelligent Transport Systems ; 10 , 1 ; 50-57
2016-02-01
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
sustainability , traffic conditions , energy consumption , single‐track railway line , railways , time station , energy consumption minimisation , late running passenger train , delay management , rail traffic control , cost reduction , single‐track railway , train capacity , timing points , traffic management system , optimisation algorithm , maximum speed , punctuality , time constraints , freight handling , freight train , freight train trajectory , energy saving , deviation reduction , timetabled arrival , macroscopic level approach , microscopic level approach , minimisation
Delay management and energy consumption minimisation on a single-track railway
IET | 2016
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