Detail výsledku

Automatic Speech Recognition and Understanding for Radar Label Maintenance Support Increases Safety and Reduces Air Traffic Controllers' Workload

HELMKE, H.; KLEINERT, M.; AHRENHOLD, N.; EHR, H.; MÜHLHAUSEN, T.; PINSKA, E.; OHNEISER, O.; KLAMERT, L.; MOTLÍČEK, P.; PRASAD, A.; ZULUAGA-GOMEZ, J.; DOKIC, J. Automatic Speech Recognition and Understanding for Radar Label Maintenance Support Increases Safety and Reduces Air Traffic Controllers' Workload. Proceedings of ATM Seminar. Savannah, Georgia: EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION, 2023. p. 1-11.
Typ
článek ve sborníku konference
Jazyk
anglicky
Autoři
HELMKE, H.
KLEINERT, M.
AHRENHOLD, N.
EHR, H.
MÜHLHAUSEN, T.
PINSKA, E.
OHNEISER, O.
KLAMERT, L.
Motlíček Petr, doc. Ing., Ph.D., UPGM (FIT)
Prasad Amrutha, UPGM (FIT)
ZULUAGA-GOMEZ, J.
DOKIC, J.
Abstrakt

Air traffic controllers (ATCos) from Austro Control together
with DLR quantified the benefits of automatic speech
recognition and understanding (ASRU) on workload and flight
safety. As the baseline procedure, ATCos enter all clearances manually
(by mouse) into the aircraft radar labels. As part of our proposed
solution, the ATCos are supported by ASRU, which is capable
of delivering the required inputs automatically. The ATCos are
only prompted to make corrections, when ASRU provided incorrect
output. Overall amount of time required for manually inserting
clearances, i.e., by clicking and selecting the correct input on
the screen, reduced from 12,800 seconds during 14 hours of simulations
time down to 405 seconds, when ATCos were supported by
ASRU. A reduction of radar label maintenance time through
ASRU might not be surprising given earlier experiments. However,
a factor greater than 30 outperforms earlier findings. In addition,
this paper also considers safety aspects, i.e., how often
ATCos support provided an incorrect input into the aircraft radar
labels with and without ASRU. This paper shows that ASRU systems
based on artificial intelligence are reliable enough for their
integration into air traffic control operations rooms.

Klíčová slova

automatic speech recognition, automatic speech understanding, situation awareness, saftety, artificial intelligence, human factors, air traffic controller's workload

URL
Rok
2023
Strany
1–11
Sborník
Proceedings of ATM Seminar
Konference
15th USA/Europe Air Traffic Management Research and Development Seminar (ATM2023)
Vydavatel
EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION
Místo
Savannah, Georgia
BibTeX
@inproceedings{BUT187934,
  author="HELMKE, H. and KLEINERT, M. and AHRENHOLD, N. and EHR, H. and MÜHLHAUSEN, T. and PINSKA, E. and OHNEISER, O. and KLAMERT, L. and MOTLÍČEK, P. and PRASAD, A. and ZULUAGA-GOMEZ, J. and DOKIC, J.",
  title="Automatic Speech Recognition and Understanding for Radar Label Maintenance Support Increases Safety and Reduces Air Traffic Controllers' Workload",
  booktitle="Proceedings of ATM Seminar",
  year="2023",
  pages="1--11",
  publisher="EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION",
  address="Savannah, Georgia",
  url="https://drive.google.com/file/d/1XPAoL576LZ8p6Cr7HO5Op-TfNLERSFNa/view"
}
Soubory
Projekty
Soudobé metody zpracování, analýzy a zobrazování multimediálních a 3D dat, VUT, Vnitřní projekty VUT, FIT-S-23-8278, zahájení: 2023-03-01, ukončení: 2026-02-28, řešení
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