Pregled bibliografske jedinice broj: 1246096
Novel Artificial Situational Awareness System is Comparable with Human Situational Awareness in the En-route Air Traffic Control Domain
Novel Artificial Situational Awareness System is Comparable with Human Situational Awareness in the En-route Air Traffic Control Domain // International Scientific Conference "The Science and Development of Transport - Znanost i razvitak prometa - ZIRP 2022" / Petrović, Marjana ; Dovbischuk, Irina ; Cunha, André Luiz (ur.).
Šibenik, Hrvatska: Elsevier, 2022. str. 316-327 doi:10.1016/j.trpro.2022.09.036 (predavanje, recenziran, cjeloviti rad (in extenso), znanstveni)
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Naslov
Novel Artificial Situational Awareness System is Comparable with Human Situational Awareness in the En-route Air Traffic Control Domain
Autori
Samardžić, Kristina ; Radišić, Tomislav ; Tukarić, Ivan ; Hermann, Ruth Esther Häusler
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
International Scientific Conference "The Science and Development of Transport - Znanost i razvitak prometa - ZIRP 2022"
/ Petrović, Marjana ; Dovbischuk, Irina ; Cunha, André Luiz - : Elsevier, 2022, 316-327
Skup
International Scientific Conference “The Science and Development of Transport - Znanost i razvitak prometa” (ZIRP 2022)
Mjesto i datum
Šibenik, Hrvatska, 28.09.2022. - 30.09.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Recenziran
Ključne riječi
air traffic control ; Knowledge graph ; monitoring tasks ; Situation awareness
Sažetak
AISA project introduces human-machine distributed situational awareness (SA) in en-route air traffic control. This paper is a result of the project's preliminary study. As a part of the project, a comparison between artificial and human situational awareness is performed. To investigate if the artificial SA could undistractedly monitor traffic, air traffic controller (ATCO) tasks are defined within Knowledge Graph (KG) system. KG system serves as a database with the ability to define relationships between data points. Human-in-the-loop simulations were performed to acquire needed data. ATCOs conducted different traffic scenarios which were later analysed and assessed regarding SA indicators defined in the paper. Tasks defined within the KG-based system can produce artificial SA that can successfully identify and complement all human SA degradation occurrences, contributing to Team SA. Therefore, defined tasks are sufficient to apply to the traffic data and to produce adequate machine SA.
Izvorni jezik
Engleski
Znanstvena područja
Tehnologija prometa i transport
Napomena
Transportation Research Procedia Volume 64, Issue C
POVEZANOST RADA
Ustanove:
Fakultet prometnih znanosti, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Scopus
