Conceptualized low-altitude flight operations specify highly autonomous vehicles and communication systems with humans responsible for monitoring and supervising such technologies. Parallel efforts suggest that the overall performance of such operations may be improved by supporting the interactions between technologies and humans, which is particularly useful in diagnosing off-nominal behavior. To work towards integrating human and machine decision-making, this paper details the information representation designs and scenarios challenging automation monitoring tasks specified to projected operations. The designs have been implemented as a plugin to the popular BlueSky Air Traffic Management simulation software, with future work planned to test the usefulness of such designs via Human-in-the-Loop investigations. Additionally, a discussion is provided detailing how the developed plugin fits into broader human-automation teaming design and evaluation methodologies (e.g., computational simulation and cognitive walkthroughs), informing the foundation of overall system resilience and supporting the integration of human and machine decision-making in safety-critical systems.


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    Titel :

    Towards Informing Joint Contingency Diagnosis for Autonomous Low-Altitude Flight


    Beteiligte:
    Kannally, Connor (Autor:in) / Furl, Isabel (Autor:in) / McSherry, Luke (Autor:in) / Paladugu, Abhinay (Autor:in)


    Erscheinungsdatum :

    29.09.2024


    Format / Umfang :

    597624 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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