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Safety and Workload Benefits of Automatic Speech Understanding for Radar Label Updates

Helmke, Hartmut and Kleinert, Matthias and Ohneiser, Oliver and Ahrenhold, Nils and Motlicek, Petr and Klamert, Lucas (2024) Safety and Workload Benefits of Automatic Speech Understanding for Radar Label Updates. Journal of Air Transportation, pp. 1-14. American Institute of Aeronautics and Astronautics (AIAA). doi: 10.2514/1.D0419. ISSN 2380-9450.

Full text not available from this repository.

Abstract

Air traffic controllers (ATCos) quantified the benefits of automatic speech recognition and understanding (ASRU) on workload and flight safety. As baseline procedure, ATCos manually enter all verbal clearances into the aircraft radar labels by mouse. In our proposed solution, ATCos are supported by ASRU, which is capable of delivering the required radar label updates automatically. ATCos need to visually review the ASRU-based label updates and only have to make corrections in case of misinterpretations. Overall, the amount of time required for manually inserting clearances, i.e., by selecting the correct input in the radar labels, reduced from 12,700 seconds during 14 hours of simulation time down to 405 seconds, when ATCos were supported by ASRU. Considering the additional time of mental workload for verifying ASRU output, there is still a saving of more than one third of the time for radar label updates. This paper also considers safety aspects, i.e., how often incorrect inputs into aircraft radar labels occurred with ASRU. The number of wrong or missing inputs is less than without ASRU support. This paper advances the use case that ASRU could potentially improve safety and efficiency for ATCo operations for arrivals.

Item URL in elib:https://elib.dlr.de/204792/
Document Type:Article
Title:Safety and Workload Benefits of Automatic Speech Understanding for Radar Label Updates
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Helmke, HartmutUNSPECIFIEDhttps://orcid.org/0000-0002-1939-0200UNSPECIFIED
Kleinert, MatthiasUNSPECIFIEDhttps://orcid.org/0000-0002-0782-4147UNSPECIFIED
Ohneiser, OliverUNSPECIFIEDhttps://orcid.org/0000-0002-5411-691X175951710
Ahrenhold, NilsUNSPECIFIEDhttps://orcid.org/0000-0001-8731-8959UNSPECIFIED
Motlicek, PetrUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Klamert, LucasUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:8 June 2024
Journal or Publication Title:Journal of Air Transportation
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI:10.2514/1.D0419
Page Range:pp. 1-14
Publisher:American Institute of Aeronautics and Astronautics (AIAA)
ISSN:2380-9450
Status:Published
Keywords:National Airspace SystemAviation SafetySingle European Sky ATM ResearchMilitary TechnologyAir Navigation Service ProviderConvolutional Neural NetworkNatural Language ProcessingAdvanced Surface Movement Guidance and Control SystemAutomatic Speech RecognitionAutomatic Speech Understanding
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Air Transportation and Impact
DLR - Research area:Aeronautics
DLR - Program:L AI - Air Transportation and Impact
DLR - Research theme (Project):L - Integrated Flight Guidance
Location: Braunschweig
Institutes and Institutions:Institute of Flight Guidance > Controller Assistance
Deposited By: Diederich, Kerstin
Deposited On:31 Jul 2024 13:09
Last Modified:17 Jan 2025 09:08

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