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Evaluation of a Remote Data Collection Method to Study Human-Automation Interaction and WorkloadIntroduction
- Paradigm shift from one operator supervising a single vehicle, to an operator supervising multiple highly automated vehicles (One-to-Many)
- One-to-Many application
- Search and Rescue
- Foraging
- Military ops
- Etc.
- Calibrated trust in automation enables human operators to effectively manage highly automated vehicles
- Past studies show that trust mediates relationship between reliability and dependence (Chancey et al., 2017; Chancey et al., 2015)
- Future studies needed to further understand relationship
Document ID
20220014716
Acquisition Source
Ames Research Center
Document Type
Presentation
Authors
Meghan Chandarana
(Ames Research Center Mountain View, California, United States)
Eric Chancey
(Langley Research Center Hampton, Virginia, United States)
Lisa Le Vie
(Langley Research Center Hampton, Virginia, United States)
Michael Politowicz
(Langley Research Center Hampton, Virginia, United States)
Date Acquired
September 28, 2022
Subject Category
Behavioral Sciences
Cybernetics, Artificial Intelligence And Robotics
Meeting Information
Meeting: Human Factors and Ergonomics Society 66th International Annual Meeting (HFES 2022)
Location: Atlanta, GA
Country: US
Start Date: October 10, 2022
End Date: October 14, 2022
Sponsors: Human Factors and Ergonomics Society
Funding Number(s)
WBS: 109492.02.01.07.07
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
NASA Peer Committee
Keywords
trust
reliance
human-automation interaction
remote data collection
workload
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