Operator workload reduced in unmanned aerial vehicles: Making Command and control (C2) maps more useful

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Command and control (C2) maps in military unmanned aerial vehicles (UAVs) are often cluttered beyond the needs of operators. Unfortunately, information overload increases the operators' mental effort and mission performance suffers. To make C2 maps more useful and improve operator performance, this study proposes a triangular approach to highlighting mission-critical information. First, the underlying value of map information and its relevance to mission success are examined. Second, algorithms based on machine learning are developed to facilitate information integration and generate visualization items, via tagging in time and space, where the appropriate area of relevance for each item is defined. Third, the algorithms are improved to dynamically update the visualizations. The proposed approach and developed algorithms are being evaluated based on four experiments with professional operators in simulated UAV and C2 environments. Hopefully, it would be possible to generalize the algorithms developed in this research-in-progress to other spatial and temporal domains where workload must be reduced.

Original languageEnglish
Title of host publication62nd Human Factors and Ergonomics Society Annual Meeting, HFES 2018
PublisherHuman Factors and Ergonomics Society Inc.
Pages1057-1061
Number of pages5
ISBN (Electronic)9781510889538
StatePublished - 1 Jan 2018
Event62nd Human Factors and Ergonomics Society Annual Meeting, HFES 2018 - Philadelphia, United States
Duration: 1 Oct 20185 Oct 2018

Publication series

NameProceedings of the Human Factors and Ergonomics Society
Volume2
ISSN (Print)1071-1813

Conference

Conference62nd Human Factors and Ergonomics Society Annual Meeting, HFES 2018
Country/TerritoryUnited States
CityPhiladelphia
Period1/10/185/10/18

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