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Crew Resource Management Doctrine Applicability to Human-Machine Interaction in Commercial Aircraft

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Intelligent Human Systems Integration (IHSI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 722))

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Abstract

Automated systems are quietly entering our lives in many different forms. These include speech recognition, smart home systems, intelligent assistants, as well as unmanned aerial vehicles (UAV), highly automated aircraft, trains, nuclear power plants, and cars. Automation has many potential benefits. It can limit human operator error and improve efficiency. What happens when automated systems reach the limits of their capabilities? Current automated systems typically have performance limits and need operators who are in the loop in all modes of automated control. If humans cannot be removed completely from these automated systems it is essential to help the human monitors of these systems. One method to improve the human/machine interaction seen in commercial aviation could be to develop requirements to regulate and monitor these systems in regards to how they adhere to crew resource management (CRM) rules that human pilots are required to meet. This could reduce the risk of catastrophic loss in the event of an automation failure in an airliner that requires human pilots to suddenly take manual control of their airplanes. A survey [1] found the majority the pilots agreed that automation should adhere to CRM rules.

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Authors and Affiliations

  1. Old Dominion University, 2101 Engineering Systems Building, Norfolk, USA

    Aysen K. Taylor

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  1. Aysen K. Taylor
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Correspondence to Aysen K. Taylor .

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Editors and Affiliations

  1. University of Central Florida, Orlando, Florida, USA

    Waldemar Karwowski

  2. University of Central Florida, Orlando, Florida, USA

    Tareq Ahram

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Taylor, A.K. (2018). Crew Resource Management Doctrine Applicability to Human-Machine Interaction in Commercial Aircraft. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-73888-8_88

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  • DOI: https://doi.org/10.1007/978-3-319-73888-8_88

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73887-1

  • Online ISBN: 978-3-319-73888-8

  • eBook Packages: EngineeringEngineering (R0)

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