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Advancing the AI-Based Realization of ACAS X Towards Real-World Application

Christensen, Johann Maximilian und Anilkumar Girija, Akshay und Stefani, Thomas und Durak, Umut und Hoemann, Elena und Köster, Frank und Krüger, Thomas und Hallerbach, Sven (2024) Advancing the AI-Based Realization of ACAS X Towards Real-World Application. In: 36th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2024, Seiten 57-64. IEEE. 2024 IEEE 36th International Conference on Tools with Artificial Intelligence (ICTAI), 2024-10-28 - 2024-10-30, Herndon, VA, USA. doi: 10.1109/ICTAI62512.2024.00017. ISBN 979-833152723-5. ISSN 1082-3409.

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Kurzfassung

In recent years, artificial intelligence (AI) has been applied to a wide range of safety-critical domains, such as automotive, robotics, and aviation. Especially the automotive and robotics domains have seen a rapid increase in the number of AI-based systems that are being deployed in real-world applications. However, real-world applications in the aviation domain are still sparse, given the challenges of AI engineering in combination with strict safety requirements. A first possible application of AI in the aviation domain might be the future collision avoidance system Airborne Collision Avoidance Systems X (ACAS X). The goal of collision avoidance systems is to issue advisories to the pilot to avoid near mid-air collisions (NMACs). The two important variants of ACAS X for this work are ACAS XA, providing vertical advisories and meant as a drop-in replacement for current systems in commercial air flight, and ACAS XU, providing horizontal advisories for the ever-growing unmanned aircraft systems market. This work brings both variants closer to real-world deployment by implementing a vertical collision avoidance system, based upon ACAS XA, and a horizontal collision avoidance system, based upon ACAS XU, for the research flight simulator FlightGear. Using advisories given by this implementation, this work furthermore provides an auto-avoid function that can command an airplane in FlightGear to safely avoid NMACs. Finally, this work will show that the ACAS X implementation can avoid collisions in a simulated environment. For this task, an Operational Design Domain will be defined serving as a basis for safety considerations and evaluating the implementation of the ACAS X. In the end, simulation-based testing will be used separately for VCAS and HCAS showing the successful utilization of advisory predictions as autopilot inputs. Summarizing, this work not only presents an open-source implementation of ACAS XA and ACAS XU for FlightGear but also shows how the generated advisories can be used to successfully avoid NMACs.

elib-URL des Eintrags:https://elib.dlr.de/207945/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Advancing the AI-Based Realization of ACAS X Towards Real-World Application
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Christensen, Johann Maximilianjohann.christensen (at) dlr.dehttps://orcid.org/0000-0001-9871-122X177203909
Anilkumar Girija, Akshayakshay.anilkumargirija (at) dlr.dehttps://orcid.org/0000-0002-4384-9739177203910
Stefani, ThomasThomas.Stefani (at) dlr.dehttps://orcid.org/0000-0001-7352-0590177203911
Durak, UmutUmut.Durak (at) dlr.dehttps://orcid.org/0000-0002-2928-1710177203912
Hoemann, Elenaelena.hoemann (at) dlr.dehttps://orcid.org/0000-0001-9315-548X177203913
Köster, FrankFrank.Koester (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Krüger, Thomasthomas.krueger (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Hallerbach, SvenSven.Hallerbach (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:Oktober 2024
Erschienen in:36th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2024
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Nein
DOI:10.1109/ICTAI62512.2024.00017
Seitenbereich:Seiten 57-64
Verlag:IEEE
ISSN:1082-3409
ISBN:979-833152723-5
Status:veröffentlicht
Stichwörter:Artificial Intelligence, ACAS X, Python, FlightGear
Veranstaltungstitel:2024 IEEE 36th International Conference on Tools with Artificial Intelligence (ICTAI)
Veranstaltungsort:Herndon, VA, USA
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:28 Oktober 2024
Veranstaltungsende:30 Oktober 2024
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Technik für Raumfahrtsysteme
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R SY - Technik für Raumfahrtsysteme
DLR - Teilgebiet (Projekt, Vorhaben):R - Synergieprojekt Resilienz intelligenter Cyber-Physical Systems of Systems
Standort: andere
Institute & Einrichtungen:Institut für KI-Sicherheit
Institut für Flugsystemtechnik > Sichere Systeme und System Engineering
Hinterlegt von: Christensen, Johann Maximilian
Hinterlegt am:04 Nov 2024 08:59
Letzte Änderung:17 Feb 2025 10:03

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