Literature DB >> 11539855

Automation-induced monitoring inefficiency: role of display location.

I L Singh1, R Molloy, R Parasuraman.   

Abstract

Operators can be poor monitors of automation if they are engaged concurrently in other tasks. However, in previous studies of this phenomenon the automated task was always presented in the periphery, away from the primary manual tasks that were centrally displayed. In this study we examined whether centrally locating an automated task would boost monitoring performance during a flight-simulation task consisting of system monitoring, tracking and fuel resource management sub-tasks. Twelve nonpilot subjects were required to perform the tracking and fuel management tasks manually while watching the automated system monitoring task for occasional failures. The automation reliability was constant at 87.5% for six subjects and variable (alternating between 87.5% and 56.25%) for the other six subjects. Each subject completed four 30 min sessions over a period of 2 days. In each automation reliability condition the automation routine was disabled for the last 20 min of the fourth session in order to simulate catastrophic automation failure (0 % reliability). Monitoring for automation failure was inefficient when automation reliability was constant but not when it varied over time, replicating previous results. Furthermore, there was no evidence of resource or speed accuracy trade-off between tasks. Thus, automation-induced failures of monitoring cannot be prevented by centrally locating the automated task.

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Year:  1997        PMID: 11539855     DOI: 10.1006/ijhc.1996.0081

Source DB:  PubMed          Journal:  Int J Hum Comput Stud        ISSN: 1071-5819            Impact factor:   3.632


  3 in total

Review 1.  Automation bias: a systematic review of frequency, effect mediators, and mitigators.

Authors:  Kate Goddard; Abdul Roudsari; Jeremy C Wyatt
Journal:  J Am Med Inform Assoc       Date:  2011-06-16       Impact factor: 4.497

2.  Automation-Induced Complacency Potential: Development and Validation of a New Scale.

Authors:  Stephanie M Merritt; Alicia Ako-Brew; William J Bryant; Amy Staley; Michael McKenna; Austin Leone; Lei Shirase
Journal:  Front Psychol       Date:  2019-02-19

Review 3.  From Trust in Automation to Decision Neuroscience: Applying Cognitive Neuroscience Methods to Understand and Improve Interaction Decisions Involved in Human Automation Interaction.

Authors:  Kim Drnec; Amar R Marathe; Jamie R Lukos; Jason S Metcalfe
Journal:  Front Hum Neurosci       Date:  2016-06-30       Impact factor: 3.169

  3 in total

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