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Link to original content: https://unpaywall.org/10.1007/978-3-031-16245-9_11
Onboard Sensor Systems for Automatic Train Operation | SpringerLink
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Onboard Sensor Systems for Automatic Train Operation

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Dependable Computing – EDCC 2022 Workshops (EDCC 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1656))

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Abstract

This paper introduces the specific requirements of the domain of train operation and its regulatory framework to the AI community. It assesses sensor sets for driverless and unattended train operation. It lists functionally justified ranges of technical specifications for sensors of different types, which will generate input for AI perception algorithms (i.e. for signal and obstacle detection). Since an optimal sensor set is the subject of research, this paper provides the specification of a generic data acquisition platform as a crucial step. Some particular results are recommendations for the minimal resolution and shutter type for image sensors, as well as beam steering methods and resolutions for LiDARs.

Supported by German Centre for Rail Traffic Research DISCLAIMER: This is not an official statement, guideline or directive of the German Federal Railway Authority.

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Author information

Authors and Affiliations

  1. German Centre for Rail Traffic Research at Federal Railway Authority, Dresden, Germany

    Rustam Tagiew & Christian Klotz

  2. DB Systemtechnik GmbH, Minden, Germany

    Dirk Leinhos, Henrik von der Haar & Pavel Klasek

  3. Fraunhofer IOSB, Karlsruhe, Germany

    Dennis Sprute & Jens Ziehn

  4. Technische Hochschule OWL, Lemgo, Germany

    Andreas Schmelter & Stefan Witte

Authors
  1. Rustam Tagiew
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  2. Dirk Leinhos
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  3. Henrik von der Haar
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  4. Christian Klotz
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  5. Dennis Sprute
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  6. Jens Ziehn
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  7. Andreas Schmelter
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  8. Stefan Witte
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  9. Pavel Klasek
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Corresponding author

Correspondence to Rustam Tagiew .

Editor information

Editors and Affiliations

  1. University of Campania "Luigi Vanvitelli", Caserta, Italy

    Stefano Marrone

  2. Gran Sasso Science Institute, L’Aquila, Italy

    Martina De Sanctis

  3. Budapest University of Technology and Economics, Budapest, Hungary

    Imre Kocsis

  4. Fraunhofer Institute for Experimental Software Engineering IESE, Kaiserslautern, Germany

    Rasmus Adler

  5. University of York, York, UK

    Richard Hawkins

  6. Fraunhofer Institute for Cognitive Systems IKS, Munich, Germany

    Philipp Schleiß

  7. University of Naples Federico II, Naples, Italy

    Stefano Marrone

  8. Parthenope University of Naples, Naples, Italy

    Roberto Nardone

  9. Mälardalen University, Västerås, Sweden

    Francesco Flammini

  10. University of Naples Federico II, Naples, Italy

    Valeria Vittorini

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Tagiew, R. et al. (2022). Onboard Sensor Systems for Automatic Train Operation. In: Marrone, S., et al. Dependable Computing – EDCC 2022 Workshops. EDCC 2022. Communications in Computer and Information Science, vol 1656. Springer, Cham. https://doi.org/10.1007/978-3-031-16245-9_11

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  • DOI: https://doi.org/10.1007/978-3-031-16245-9_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16244-2

  • Online ISBN: 978-3-031-16245-9

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