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A Vision of Intelligent Train Control
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Department of Computer Science and Media Technology, Linnaeus University, Växjö, Sweden.ORCID iD: 0000-0002-2833-7196
Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy.
Department of Information Engineering, University of Florence, Florence, Italy.
Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy.
2022 (English)In: Lect. Notes Comput. Sci., Springer Science and Business Media Deutschland GmbH , 2022, p. 192-208Conference paper, Published paper (Refereed)
Abstract [en]

The progressive adoption of artificial intelligence and advanced communication technologies within railway control and automation has brought up a huge potential in terms of optimisation, learning and adaptation, due to the so-called “self-x” capabilities; however, it has also raised several dependability concerns due to the lack of measurable trust that is needed for certification purposes. In this paper, we provide a vision of future train control that builds upon existing automatic train operation, protection, and supervision paradigms. We will define the basic concepts for autonomous driving in digital railways, and summarise its feasibility in terms of challenges and opportunities, including explainability, autonomic computing, and digital twins. Due to the clear architectural distinction, automatic train protection can act as a safety envelope for intelligent operation to optimise energy, comfort, and capacity, while intelligent protection based on signal recognition and obstacle detection can improve safety through advanced driving assistance. © 2022, Springer Nature Switzerland AG.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH , 2022. p. 192-208
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 13294 LNCS
Keywords [en]
Artificial intelligence, Autonomous driving, Certification, Machine learning, Safety envelope, Smart railways, Trustworthy AI
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-58658DOI: 10.1007/978-3-031-05814-1_14Scopus ID: 2-s2.0-85131150379ISBN: 9783031058134 (print)OAI: oai:DiVA.org:mdh-58658DiVA, id: diva2:1665956
Conference
4th International Conference on Reliability, Safety and Security of Railway Systems, RSSRail 2022
Available from: 2022-06-08 Created: 2022-06-08 Last updated: 2022-06-08Bibliographically approved

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Flammini, Francesco

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CiteExportLink to record
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  • apa
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