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Quantifying and Developing Countermeasures for the Effect of Fatigue-Related Stressors on Automation Use and Trust During Robotic Supervisory Control

Principal Investigator:
Debra Schreckenghost, M.E.E.

TRACLabs, Inc.

This project will develop and test adaptive automation countermeasures for the effects of stressors such as sleep deprivation (SD) on human performance related to robotic tasks, and investigate the relationship between human trust and appropriate use of these countermeasures. It will produce a diverse set of technologies and techniques for NASA relevant to human exploration missions. It will prototype and evaluate technology adaptations for NASA and other users to prevent or compensate for the cognitive deficits arising from situational stressors like SD that can degrade human task performance. It will define new measures of trust that combine subjective assessment of attitude with objective measurements relating automation reliance and task outcome. It will use these measures to investigate the effects of SD on trust in automation. It will develop a testbed for supervisory control of robots that encapsulates a rich set of human problem solving and decision-making tasks and provides an environment for testing the effects of situational stressors like SD on human performance of these tasks.

Technical Summary

Sleep deprivation (SD) is a situational stressor experienced by most astronauts and many flight controllers. Astronauts on the International Space Station (ISS) must adapt to circadian misalignment and commonly report sleep issues during the mission; sleep aids are some of the most used medications in space. These issues will be exacerbated for longer duration exploration missions. ISS flight controllers must adapt to non-standard schedules and consequent insufficient sleep when working with international partners. Crew with SD is even more likely for missions with non-standard day length.

Sleep deprivation degrades performance in several ways. Of particular concern is degradation of tasks that cannot be automated — specifically requiring higher-level reasoning and particularly for novel situations, requiring divergent or creative thinking and situations when the usual solution should not be applied. While research on these tasks is limited, evidence suggests it is precisely these types of higher-level cognitive tasks that may be seriously impacted by SD. This research will quantify SD-associated impairments in human regulatory processes that provide flexibility, intentional search for relevant information, weighing and integrating information, and assessing merit of response.

Sleep deprivation also may cause users to become complacent and inappropriately rely on automation. Thus it is important to assess the effects of SD on user trust in automation and what effect proposed countermeasures have on automation trust. Appropriate level of trust by an operator relies on assessing the relative competence of automation versus self in carrying out the specific task including indirect factors such as operator workload and demands of other tasks. Multiple factors therefore influence what appropriate trust would be for a specific context.

Recent research on trust of robotic autonomy identifies a range of contributors to trust, including robot reliability and performance, robot competency, perceived risk and user self-assessment of competency. This project will extend and contribute to this research by investigating the relationship between trust of robot autonomy and patterns of reliance on autonomy under stressed conditions due to insufficient sleep.

This project will quantify the effect of sleep deprivation on multiple tasks involving human-automation-robotic (HAR) systems. Measures and interventions will be developed for sleep deprived users when supervising robots. Appropriate adaptive technology countermeasures will be designed and prototyped. Experiments will be conducted with users performing supervisory control of simulated robots in space exploration-similar scenarios to quantify sleep-deprivation-related impairment, trust in automation, and effectiveness of adaptive countermeasure technology.

The result of this project will be guidance and technology prototypes representing effective human-automation-robotic systems in operational environments where humans and robots perform distributed, concurrent teamwork under situational stressors like sleep deprivation. These guidelines will be relevant to future human space flight missions that take astronauts deeper into space and require increased crew independence from Earth (crew autonomy). They enable greater reliance on robotic and spacecraft automation by improving understanding of the effects of stress from sleep deprivation on human performance during supervisory control of robots and countermeasures for these effects.

Earth Applications

We live in a world of increasing automation. Smart buildings adjust our environment, robotic appliances perform routine tasks such as housekeeping, and self-driving cars will drive us around. Inevitably sleepy users will interact with these systems. When they are tired, humans interact differently with automation/robotic systems according to anecdotal reports and a scarce literature. For example, tired individuals (i) may misperceive information or see what is expected (e.g., perceive expected 350 PPM CO2 instead of elevated 3500 PPM), (ii) may ignore information (e.g., warning light for a secondary task while focused on a primary task), or (iii) may perseverate or rapidly respond without fully understanding implications (e.g., click "yes" in response to “Are you sure?”). The consequences of these mistakes can range from the inconvenient to the severe. Quantification of these effects and countermeasures for impaired human-automation/robot interactions will have significant safety and productivity effects for future human exploration missions and earth-based tasks This understanding also can inform the design of robots and automation for human space exploration and earth-based applications by identifying the types of adaptations needed to implement countermeasures.

This project will document the ways that human interaction with automation/robotic systems degrades under conditions of stress from SD. The tasks performed by the sleep-deprived users in our experiments are more sophisticated and the robotic work domain more complex than is typical in studies of human performance under SD. Consequently, a unique contribution of our research is how sleep-deprived people perform in work circumstances that are both complex and controlled.  These results should be valuable and immediately applicable to many Earth-based domains.