Exploring Demand Trends and Operational Scenarios for Virtual Coupling Railway Signalling Technology
Autor: | Rob M.P. Goverde, Egidio Quaglietta, Joelle Aoun |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
050210 logistics & transportation
0209 industrial biotechnology Service (systems architecture) Computer science 05 social sciences Delphi method 02 engineering and technology Transport engineering Technical feasibility Braking distance 020901 industrial engineering & automation Rail transportation 0502 economics and business Railway signalling Train Landline |
Zdroj: | Proceedings of the IEEE ITS Conference: Rhodes, Greece, 20th-23rd September, 2020 Proceedings of the IEEE ITS Conference Delft University of Technology ITSC |
Popis: | Virtual Coupling (VC) is a newly introduced concept of train-centric signalling technology that conceives trains to run autonomously in radio-connected platoons. These trains move synchronously at a relative braking distance to significantly improve railway capacity and address the forecasted increase in railway demand. The technical feasibility of VC depends on its strengths, weaknesses, opportunities and threats which can introduce radical changes to current train services, technologies and procedures. This paper investigates demand trends and operational scenarios of future train-centric signalling systems. To this end, stated travel preferences have been collected by means of a survey to have more insight on modal shares in the case of future VC applications. In addition, a Delphi method has been applied where another extensive survey has collected expert opinions about benefits and challenges of VC. Results show that VC can be very attractive to customers of high-speed and main line railways and have special benefits to the regional market where a manifest willing to pay more for using a more frequent train service was found. This concept therefore calls for a deeper understanding of possible Virtual Coupling operational scenarios and the impact on the railway industry. |
Databáze: | OpenAIRE |
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