Intelligent systems for aviation need to be capable of understanding and representing anomalous events as they happen in real-time. We explore this problem with a proof of concept framework based on contextual one-shot learning, run on a human-in-the-loop flight simulator. We ran a total of 24 trials, with variations in training, fliers, and set values within the framework, and found that our framework was able to detect and reason about anomalies in all trials. In future work, we would like to explore different heuristics for anomaly reasoning, including nonlinear interactions of cockpit data, and feedback from the flight crew through psychophysiology sensors or natural language interactions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Knowledge Acquisition in the Cockpit Using One-Shot Learning


    Contributors:


    Publication date :

    2018-07-01


    Size :

    2252008 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Cockpit Cockpit

    Trzesniowski, Michael | Springer Verlag | 2019


    Cockpit Cockpit

    Trzesniowski, Michael | Springer Verlag | 2017


    Aircraft cockpit video acquisition and recording system configuration

    LI SHUANG / LI CHAOCHAO / MU CHAO et al. | European Patent Office | 2024

    Free access

    Cockpit pur. Cockpit Design

    Ostle,D. / VDO,Schwalbach,DE | Automotive engineering | 1999


    Cockpit

    Trzesniowski, Michael | Springer Verlag | 2023