Document Detail


Automation reliability in unmanned aerial vehicle control: a reliance-compliance model of automation dependence in high workload.
MedLine Citation:
PMID:  17063963     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
OBJECTIVE: Two experiments were conducted in which participants navigated a simulated unmanned aerial vehicle (UAV) through a series of mission legs while searching for targets and monitoring system parameters. The goal of the study was to highlight the qualitatively different effects of automation false alarms and misses as they relate to operator compliance and reliance, respectively. BACKGROUND: Background data suggest that automation false alarms cause reduced compliance, whereas misses cause reduced reliance. METHOD: In two studies, 32 and 24 participants, including some licensed pilots, performed in-lab UAV simulations that presented the visual world and collected dependent measures. RESULTS: Results indicated that with the low-reliability aids, false alarms correlated with poorer performance in the system failure task, whereas misses correlated with poorer performance in the concurrent tasks. CONCLUSION: Compliance and reliance do appear to be affected by false alarms and misses, respectively, and are relatively independent of each other. APPLICATION: Practical implications are that automated aids must be fairly reliable to provide global benefits and that false alarms and misses have qualitatively different effects on performance.
Authors:
Stephen R Dixon; Christopher D Wickens
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Human factors     Volume:  48     ISSN:  0018-7208     ISO Abbreviation:  Hum Factors     Publication Date:  2006  
Date Detail:
Created Date:  2006-10-26     Completed Date:  2006-12-14     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0374660     Medline TA:  Hum Factors     Country:  United States    
Other Details:
Languages:  eng     Pagination:  474-86     Citation Subset:  IM; S    
Affiliation:
University of Illinois, Institute of Aviation, Aviation Human Factors Division, 1 Airport Rd., Savoy, IL 61874, USA. srdixon1@uiuc.edu
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MeSH Terms
Descriptor/Qualifier:
Aircraft*
Automation / instrumentation,  standards*
Equipment Failure
Humans
Man-Machine Systems*
Task Performance and Analysis*
United States

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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