Publication detail

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.

Original Title

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

Type

article in a collection out of WoS and Scopus

Language

English

Original 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.

Keywords

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

Authors

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.

Released

5. 6. 2023

Publisher

EUROPEAN ORGANISATION FOR THE SAFETY OF AIR NAVIGATION

Location

Savannah, Georgia

Pages from

1

Pages to

11

Pages count

11

URL

https://drive.google.com/file/d/1XPAoL576LZ8p6Cr7HO5Op-TfNLERSFNa/view

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"
}

Documents

helmke_ATM2023_paper_4.pdf