Literature DB >> 22046719

Mitigation of conflicts with automation: use of cognitive countermeasures.

Frédéric Dehais1, Mickaël Causse, Sébastien Tremblay.   

Abstract

OBJECTIVE: The aim of this study was to empirically assess the efficacy of cognitive countermeasures based on the technique of information removal to enhance human operator attentional disengagement abilities when facing attentional tunneling.
BACKGROUND: Lessons learned from human factors studies suggest that conflict with automation leads to the degradation of operators' performance by promoting excessive focusing on a single task to the detriment of the supervision of other critical parameters.
METHOD: An experimental setup composed of a real unmanned ground vehicle and aground station was developed to test the efficiency of the cognitive countermeasures.The scenario (with and without countermeasure) involved an authority conflict between the participants and the robot induced by a battery failure.The effects of the conflict and, in particular, the impact of cognitive countermeasures on the participants' cognition and arousal were assessed through heart rate measurement and eye tracking techniques.
RESULTS: In the control group (i.e., no countermeasure), 8 out of 12 participants experienced attentional tunneling when facing the conflict, leading them to neglect the visual alarms displayed that would have helped them to understand the evolution of the tactical situation. Participants in the countermeasure group showed lower heart rates and enhanced attentional abilities, and 10 out of 11 participants made appropriate decisions.
CONCLUSIONS: The use of cognitive countermeasures appeared to be an efficient means to mitigate excessive focus issues in the unmanned ground vehicle environment. APPLICATIONS: The principle of cognitive countermeasures can be applied to a large domain of applications involving human operators interacting with critical systems.

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Year:  2011        PMID: 22046719     DOI: 10.1177/0018720811418635

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  1 in total

Review 1.  A Neuroergonomics Approach to Mental Workload, Engagement and Human Performance.

Authors:  Frédéric Dehais; Alex Lafont; Raphaëlle Roy; Stephen Fairclough
Journal:  Front Neurosci       Date:  2020-04-07       Impact factor: 4.677

  1 in total

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