Print Email Facebook Twitter A hybrid Delphi-AHP multi-criteria analysis of Moving Block and Virtual Coupling railway signalling Title A hybrid Delphi-AHP multi-criteria analysis of Moving Block and Virtual Coupling railway signalling Author Aoun, J. (TU Delft Transport and Planning) Quaglietta, E. (TU Delft Transport and Planning) Goverde, R.M.P. (TU Delft Transport and Planning) Scheidt, Martin (Technical University of Braunschweig) Blumenfeld, Marcelo (University of Birmingham) Jack, Anson (University of Birmingham) Redfern, Bill (PARK Signalling ltd.) Date 2021 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. Subject AHPDelphiMoving block signallingMulti-criteria analysisRailway operationsVirtual coupling To reference this document use: http://resolver.tudelft.nl/uuid:b30da7f7-e730-436f-97eb-5a887e127851 DOI https://doi.org/10.1016/j.trc.2021.103250 ISSN 0968-090X Source Transportation Research. Part C: Emerging Technologies, 129, 1-22 Part of collection Institutional Repository Document type journal article Rights © 2021 J. Aoun, E. Quaglietta, R.M.P. Goverde, Martin Scheidt, Marcelo Blumenfeld, Anson Jack, Bill Redfern Files PDF 1_s2.0_S0968090X21002631_main.pdf 2.71 MB Close viewer /islandora/object/uuid:b30da7f7-e730-436f-97eb-5a887e127851/datastream/OBJ/view