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Return-to-Manual Performance can be Predicted Before Automation Fails.
Natalie Griffiths1, Vanessa Bowden1, Serena Wee1
1The University of Western Australia, Crawley, WA, Australia.
Human Factors
|December 20, 2022
Summary
Operator trust in automation can hinder return-to-manual (RTM) performance, especially for those with high trust. Fatigue can improve RTM performance in some individuals, highlighting the need for adaptive automation systems to monitor operator states.
Area of Science:
- Human-Computer Interaction
- Cognitive Engineering
- Automation Safety
Background:
- Current adaptive automation relies on reactive performance indicators.
- Proactive automation control requires predicting operator return-to-manual (RTM) performance.
- Within-person analyses are crucial for predicting RTM performance.
Purpose of the Study:
- To investigate operator state variables predicting RTM performance.
- To examine workload, fatigue, and trust in automation.
- To understand RTM performance in simulated air traffic control.
Main Methods:
- Participants managed aircraft with imperfect automation.
- Intervention was required when automation failed to detect conflicts.
- Operator workload, fatigue, and trust were periodically assessed.
Main Results:
- Increased trust slowed RTM response time for high-trust individuals.
- Increased fatigue improved RTM response time for low-fatigue individuals.
- Workload did not significantly affect RTM performance.
Conclusions:
- RTM performance degrades with increased trust in automation for average/high trust users.
- Operator state variables can predict RTM performance decrements.
- Adaptive automation can leverage operator states for proactive control.
Keywords:
air traffic controlautomationhuman-automation interactionmental workloadtrust in automationMore Related Videos
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