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        Chapter Adaptive Automation and the Third Pilot

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        Author(s)
        Cahill, Joan
        Callari, Tiziana C.
        Fortmann, Florian
        Suck, Stefan
        Javaux, Denis
        Hasselberg, Andreas
        Stoeve, Sybert
        Language
        English
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        Abstract
        Currently, automation does not take into consideration the cognitive and emotional state of the crew. Rather, automation provides assistance based on explicit and static task assignments, with no adaptive capabilities, even though it is capable of providing higher or lower levels of support depending on the crew state and/or complexity of the operational situation. This chapter presents a new adaptive automation concept which offers an innovative ‘team’ centred approach to solving crew awareness/workload management problems and enhancing flight safety. Partnership underpins the ‘Third Pilot’ approach. The crew (pilot flying and pilot monitoring), automation and the ‘Third Pilot’ are in charge together. Overall, partnership is proposed. This replaces existing paradigms involving dynamic changes in control function, where changes can be autonomously controlled by the system. Moreover, a new multimodal cockpit concept is advanced providing enhanced assessment of crew state/workload.
        URI
        https://library.oapen.org/handle/20.500.12657/49234
        Keywords
        adaptive automation, teamwork, workload, human factors, situation awareness, pilot decision making, stakeholder evaluation, cockpit
        DOI
        10.5772/intechopen.73689
        Publisher
        InTechOpen
        Publisher website
        https://www.intechopen.com/
        Publication date and place
        2018
        Classification
        Astronautics
        Rights
        https://creativecommons.org/licenses/by/3.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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