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

Authors :
Louis Heuveline
Julien Cegarra
Eugénie Avril
Jordan Navarro
Laboratoire d'Etude des Mécanismes Cognitifs (EMC)
Université Lumière - Lyon 2 (UL2)
Sciences de la Cognition, Technologie, Ergonomie (SCoTE)
Institut national universitaire Champollion [Albi] (INUC)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées
ANR-11-IDEX-0007,Avenir L.S.E.,PROJET AVENIR LYON SAINT-ETIENNE(2011)
Source :
Ergonomics, Ergonomics, Taylor & Francis, 2018, 61 (12), pp.1601-1612. ⟨10.1080/00140139.2018.1501517⟩
Publication Year :
2018
Publisher :
Informa UK Limited, 2018.

Abstract

International audience; 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.

Details

ISSN :
13665847 and 00140139
Volume :
61
Database :
OpenAIRE
Journal :
Ergonomics
Accession number :
edsair.doi.dedup.....e74f11c9d59a075e2ef168bd9f818b04
Full Text :
https://doi.org/10.1080/00140139.2018.1501517