Publication Details

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

HELMKE Hartmut, KLEINERT Matthias, AHRENHOLD Nils, EHR Heiko, MÜHLHAUSEN Thorsten, PINSKA Chauvin Ella, OHNEISER Oliver, KLAMERT Lucas, MOTLÍČEK Petr, PRASAD Amrutha, ZULUAGA-GOMEZ Juan and DOKIC Jelena. Automatic Speech Recognition and Understanding for Radar Label Maintenance Support Increases Safety and Reduces Air Traffic Controllers' Workload. In: Proceedings of ATM Seminar. Savannah, Georgia: EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION, 2023, pp. 1-11. Available from: https://drive.google.com/file/d/1XPAoL576LZ8p6Cr7HO5Op-TfNLERSFNa/view
Czech title
Automatické rozpoznávání a porozumění řeči pro podporu sledování radarových údajů zvyšuje bezpečnost a snižuje pracovní zátěž řídících letového provozu
Type
conference paper
Language
english
Authors
Helmke Hartmut (DLR)
Kleinert Matthias (DLR)
Ahrenhold Nils (DLR)
Ehr Heiko (DLR)
Mühlhausen Thorsten (DLR)
Pinska Chauvin Ella ()
Ohneiser Oliver (DLR)
Klamert Lucas (AustroC)
Motlíček Petr, doc. Ing., Ph.D. (DCGM FIT BUT)
Prasad Amrutha (DCGM FIT BUT)
Zuluaga-Gomez Juan (IDIAP)
Dokic Jelena ()
URL
Keywords

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

Abstract

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.

Published
2023
Pages
1-11
Proceedings
Proceedings of ATM Seminar
Conference
15th USA/Europe Air Traffic Management Research and Development Seminar (ATM2023), Savannah, Georgia, US
Publisher
EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION
Place
Savannah, Georgia, US
BibTeX 
@INPROCEEDINGS{FITPUB13162,
   author = "Hartmut Helmke and Matthias Kleinert and Nils Ahrenhold and Heiko Ehr and Thorsten M{\"{u}}hlhausen and Ella Chauvin Pinska and Oliver Ohneiser and Lucas Klamert and Petr Motl\'{i}\v{c}ek and Amrutha Prasad and Juan Zuluaga-Gomez and Jelena Dokic",
   title = "Automatic Speech Recognition and Understanding for Radar Label Maintenance Support Increases Safety and Reduces Air Traffic Controllers' Workload",
   pages = "1--11",
   booktitle = "Proceedings of ATM Seminar",
   year = 2023,
   location = "Savannah, Georgia, US",
   publisher = "EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/13162"
}
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