A hybrid Delphi-AHP multi-criteria analysis of Moving Block and Virtual Coupling railway signalling

Journal Article (2021)
Authors

J. Aoun (Transport and Planning)

Egidio Quaglietta (Transport and Planning)

Rob Goverde (Transport and Planning)

Martin Scheidt (Technical University of Braunschweig)

Marcelo Blumenfeld (University of Birmingham)

Anson Jack (University of Birmingham)

Bill Redfern (PARK Signalling ltd.)

Affiliation
Transport and Planning
Copyright
© 2021 J. Aoun, E. Quaglietta, R.M.P. Goverde, Martin Scheidt, Marcelo Blumenfeld, Anson Jack, Bill Redfern
To reference this document use:
https://doi.org/10.1016/j.trc.2021.103250
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 J. Aoun, E. Quaglietta, R.M.P. Goverde, Martin Scheidt, Marcelo Blumenfeld, Anson Jack, Bill Redfern
Related content
Affiliation
Transport and Planning
Volume number
129
Pages (from-to)
1-22
DOI:
https://doi.org/10.1016/j.trc.2021.103250
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Abstract

The railway industry needs to investigate overall impacts of next generation signalling systems such as Moving Block (MB) and Virtual Coupling (VC) to identify development strategies to face the forecasted railway demand growth. To this aim an innovative multi-criteria analysis (MCA) framework is introduced to analyse and compare VC and MB in terms of relevant criteria including quantitative (e.g. costs, capacity, stability, energy) and qualitative ones (e.g. safety, regulatory approval). We use a hybrid Delphi-Analytic Hierarchic Process (AHP) technique to objectively select, combine and weight the different criteria to more reliable MCA outcomes. The analysis has been performed for different rail market segments including high-speed, mainline, regional, urban and freight corridors. The results show that there is a highly different technological maturity level between MB and VC given the larger number of vital issues not yet solved for VC. The MCA also indicates that VC could outperform MB for all market segments if it reaches a comparable maturity and safety level. The provided analysis can effectively support the railway industry in strategic investment planning of VC.