Development of real-time performance metrics for manually-guided spacecraft operations

Karasinski, John; Duda, Kevin R.; Prasov, Zahar

doi:10.1109/aero.2016.7500734

Cited by 4 publications

(8 citation statements)

References 7 publications

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“…This work represents the first study to rigorously investigate a set of embedded measures of trust, workload, and SA by comparing those measures to commonly used subjective questionnaires. We also implemented three embedded measures (one each for TWSA) in a spaceflight-relevant scenario; previous studies had only implemented one or two embedded measures (Akash et al, 2018, 2020; Hainley et al, 2013; Karasinski et al, 2016, 2017; Petersen et al, 2019). Our results are consistent with studies showing the general utility of embedded measures of cognitive states (Hainley et al, 2013; Karasinski et al, 2016, 2017; Kunze et al, 2019; Petersen et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…However, operator engagement on a required low-priority subtask can serve as an embedded measure of workload. Similarly, verbal callouts in which operators report vehicle state changes were introduced as an embedded measure of SA in previous studies (Hainley et al, 2013;Karasinski et al, 2016Karasinski et al, , 2017. While this measure likely only evaluates Level 1 SA (Endsley, 1995), in some environments, callouts integrate naturally into existing tasks or are already standard tasks that operators complete (e.g., aircraft cockpits).…”

Section: Background and Motivationmentioning

confidence: 99%

“…The pushbutton lighting/response task (Hainley et al, 2013;Karasinski et al, 2016Karasinski et al, , 2017 was presented on a secondary display below and to the left of the primary display, at an angle of approximately 25°from the center of the primary display in the yaw plane and 21°f rom the center of the primary display in the pitch plane (see Figure 1). Participants were asked to press a corresponding green or blue button using their left hand when the outer ring of a "Data Link" light on the secondary display differed in hue (blue or green) from the inner circle of the light (see Figure 2).…”

Section: Scenario and Tasksmentioning

confidence: 99%

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Estimation of Subjectively Reported Trust, Mental Workload, and Situation Awareness Using Unobtrusive Measures

et al. 2022

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Objective We use a set of unobtrusive measures to estimate subjectively reported trust, mental workload, and situation awareness (henceforth “TWSA”). Background Subjective questionnaires are commonly used to assess human cognitive states. However, they are obtrusive and usually impractical to administer during operations. Measures derived from actions operators take while working (which we call “embedded measures”) have been proposed as an unobtrusive way to obtain TWSA estimates. Embedded measures have not been systematically investigated for each of TWSA, which prevents their operational utility. Methods Fifteen participants completed twelve trials of spaceflight-relevant tasks while using a simulated autonomous system. Embedded measures of TWSA were obtained during each trial and participants completed TWSA questionnaires after each trial. Statistical models incorporating our embedded measures were fit with various formulations, interaction effects, and levels of personalization to understand their benefits and improve model accuracy. Results The stepwise algorithm for building statistical models usually included embedded measures, which frequently corresponded to an intuitive increase or decrease in reported TWSA. Embedded measures alone could not accurately capture an operator’s cognitive state, but combining the measures with readily observable task information or information about participants’ backgrounds enabled the models to achieve good descriptive fit and accurate prediction of TWSA. Conclusion Statistical models leveraging embedded measures of TWSA can be used to accurately estimate responses on subjective questionnaires that measure TWSA. Application Our systematic approach to investigating embedded measures and fitting models allows for cognitive state estimation without disrupting tasks when administering questionnaires would be impractical.

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Section: Discussionmentioning

confidence: 99%

Section: Background and Motivationmentioning

confidence: 99%

Section: Scenario and Tasksmentioning

confidence: 99%

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Estimation of Subjectively Reported Trust, Mental Workload, and Situation Awareness Using Unobtrusive Measures

et al. 2022

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“…Further, most automation studies use non-expert subjects (i.e., typically students) which is likely to heavily discount manual mode expertise which has been gained by experts. Many of these prior studies use discrete decision-aiding automation rather than domains requiring continuous control automation, with the notable exceptions of adaptive cruise control (see, e.g., Goodrich & Olsen, 2003;Lu et al, 2016;Seppelt & Lee, 2007;Stanton et al, 1997;Young & Stanton, 2004) and lunar landing (see, e.g., Hainley et al, 2013;Karasinski et al, 2016;Johnson et al, 2016).…”

Section: Literature Review Of Automation Transitionsmentioning

confidence: 99%

“…Of these, only Hainley et al (2013) and Karasinski et al (2016) explicitly considered workload around automation mode transitions. They found reduced situation awareness (as measured using callouts) and higher workload (as measured using reaction times of a secondary task) after a transition from auto to manual mode.…”

Section: Literature Review Of Automation Transitionsmentioning

confidence: 99%

Measuring The Time Course of Engineer Workload During Automation Mode Transitions

Liu

Brooks

Subrahmaniyan

et al. 2019

Proceedings of the Human Factors and Ergonomics Society Annual

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In current freight railroad operations, locomotive control is shared between the human engineer and automated energy management systems such as GE Trip Optimizer. Transitions between the manual and automatic modes temporarily increase engineer workload above the demands of the current operating situation. Using the average response time and average number of secondary visual attention task stimuli presented as proxy measures of workload, we tracked the time course of workload during the mode transitions for two types of automated control system. The average response times peaked immediately after the mode change. The average number of stimuli presented peaked just before the mode change. We conclude that this technique of measuring workload would be very useful in evaluating future automated systems concepts in a train simulator.

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The Next Giant Leap for Space Human Factors: The Opportunities

Márquez

Landon²,

Salas

2023

Hum Factors

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Objective Propose areas of future space human factors research. Background Deep space, long-duration human spaceflight missions to the Moon and Mars still require advances in space human factors research. Key drivers relate to astronauts living and working in isolation, new novel technologies required to accomplish exploration missions, and the longer durations of these. Results Three areas of research are proposed for methods and techniques: (1) to enable more autonomous astronauts; (2) to monitor crew and improve ground team situation awareness; and (3) to detect and support changes in long-duration team coordination. Conclusions Future human exploration missions will benefit from advances in space human factors research. Application Human factors researchers can contribute to human spaceflight by prioritizing these research topics.

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Development of real-time performance metrics for manually-guided spacecraft operations

Cited by 4 publications

References 7 publications

Estimation of Subjectively Reported Trust, Mental Workload, and Situation Awareness Using Unobtrusive Measures

Estimation of Subjectively Reported Trust, Mental Workload, and Situation Awareness Using Unobtrusive Measures

Measuring The Time Course of Engineer Workload During Automation Mode Transitions

The Next Giant Leap for Space Human Factors: The Opportunities

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