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Articles

Influence of human-machine interactions and task demand on automation selection and use

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Pages 1601-1612 | Received 29 Nov 2017, Accepted 04 Jul 2018, Published online: 05 Sep 2018
 

Abstract

A seminal work by Sheridan and Verplank depicted 10 levels of automation, ranging from no automation to an automation that acts completely autonomously without human support. These levels of automation were later complemented with a four-stage model of human information processing. Next, human-machine cooperation centred models and associated cooperation modes were introduced. The objective of the experiment was to test which human-machine theorie describe automation use better. The participants were asked to choose repeatedly between four automation types (i.e. no automation, warning, co-action, function delegation) to complete three multi-attribute task battery tasks. The results showed that the participants favour the selection of automation types offering the best human-machine interactions quality rather that the most effective automation type. Contrary to human-machine cooperation models, technology centred models could not predict accurately automation selection. The most advanced automation was not the most selected.

Practitioner Summary: The experiment dealt with how people select different automation types to complete the multi-attribute task battery that emulates recreational aircraft pilot tasks. Automation performance was not the main criteria that explain automation use, as people tend to select an automation type based on the quality of the human-machine cooperation.

Acknowledgements

The program is operated by the French National Research Agency (ANR). The authors are thankful to Jérôme Larvi-Perasso and Emily Guindi for their support in running the experiments.

Additional information

Funding

This study was supported by the LABEX CORTEX (ANR-11-LABX-0042) of the program ‘Investissements d’Avenir’ (ANR-11-IDEX-0007) at the Université de Lyon.

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