Return-to-Manual Performance can be Predicted Before Automation Fails

Author:

Griffiths Natalie1ORCID,Bowden Vanessa1ORCID,Wee Serena1,Loft Shayne1ORCID

Affiliation:

1. The University of Western Australia, Crawley, WA, Australia

Abstract

Objective This study aimed to examine operator state variables (workload, fatigue, and trust in automation) that may predict return-to-manual (RTM) performance when automation fails in simulated air traffic control. Background Prior research has largely focused on triggering adaptive automation based on reactive indicators of performance degradation or operator strain. A more direct and effective approach may be to proactively engage/disengage automation based on predicted operator RTM performance (conflict detection accuracy and response time), which requires analyses of within-person effects. Method Participants accepted and handed-off aircraft from their sector and were assisted by imperfect conflict detection/resolution automation. To avoid aircraft conflicts, participants were required to intervene when automation failed to detect a conflict. Participants periodically rated their workload, fatigue and trust in automation. Results For participants with the same or higher average trust than the sample average, an increase in their trust (relative to their own average) slowed their subsequent RTM response time. For participants with lower average fatigue than the sample average, an increase in their fatigue (relative to own average) improved their subsequent RTM response time. There was no effect of workload on RTM performance. Conclusions RTM performance degraded as trust in automation increased relative to participants’ own average, but only for individuals with average or high levels of trust. Applications Study outcomes indicate a potential for future adaptive automation systems to detect vulnerable operator states in order to predict subsequent RTM performance decrements.

Funder

Australian Research Council (ARC) Discovery

ARC Future Fellowship

Publisher

SAGE Publications

Subject

Behavioral Neuroscience,Applied Psychology,Human Factors and Ergonomics

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The relationship of trust and dependence;Ergonomics;2024-05-10

2. Accelerating Understanding of Human Response to Automation Failure;Journal of Cognitive Engineering and Decision Making;2024-04-05

3. How do humans learn about the reliability of automation?;Cognitive Research: Principles and Implications;2024-02-16

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