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(searched for: doi:10.1080/10508414.2016.1226834)
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, Gemma J.M. Read, Paul M. Salmon
Published: 13 November 2021
Applied ergonomics, Volume 99; https://doi.org/10.1016/j.apergo.2021.103643

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Güliz Tokadlı, , Michael Matessa
International Journal of Human–Computer Interaction, Volume 37, pp 703-716; https://doi.org/10.1080/10447318.2021.1890485

Abstract:
A Playbook delegation approach was evaluated for human-autonomy teaming (HAT) in Single Pilot Operations (SPO). In SPO, a single pilot makes flight decisions, performs flight tasks, and collaborates with an autonomous teammate. The autonomous teammate shares responsibility, authority, and tasks. Challenges include the design of functions, interactions, and teaming skills. HAT often requires the ability to dynamically allocate functions, and timely methods to accurately express intent to teammates. A Playbook delegation interface was developed to enables the pilot to call and modify plays in collaboration with the autonomous teammate. Twenty pilots evaluated the Playbook interface to explore real-time function allocation, and identified teaming skills needed to support HAT. Pilots preferred the Playbook interface for better collaboration with the autonomous teammate. Interviews revealed that supporting human-like communication in HAT is critical to facilitate decision-making. Four major teaming skills (communication, coordination, cooperation, and cognition) are discussed to support HAT in SPO.
, Alex Lafont, Raphaëlle Roy, Stephen Fairclough
Published: 7 April 2020
Frontiers in Neuroscience, Volume 14; https://doi.org/10.3389/fnins.2020.00268

Abstract:
The assessment and prediction of cognitive performance is a key issue for any discipline concerned with human operators in the context of safety-critical behavior. Most of the research has focused on the measurement of mental workload but this construct remains difficult to operationalize despite decades of research on the topic. Recent advances in Neuroergonomics have expanded our understanding of neurocognitive processes across different operational domains. We provide a framework to disentangle those neural mechanisms that underpin the relationship between task demand, arousal, mental workload and human performance. This approach advocates targeting those specific mental states that precede a reduction of performance efficacy. A number of undesirable neurocognitive states (mind wandering, effort withdrawal, perseveration, inattentional phenomena) are identified and mapped within a two-dimensional conceptual space encompassing task engagement and arousal. We argue that monitoring the prefrontal cortex and its deactivation can index a generic shift from a nominal operational state to an impaired one where performance is likely to degrade. Neurophysiological, physiological and behavioral markers that specifically account for these states are identified. We then propose a typology of neuroadaptive countermeasures to mitigate these undesirable mental states.
, Gerald Matthews, Lauren Reinerman-Jones,
Published: 28 November 2019
Human-Intelligent Systems Integration, Volume 2, pp 1-15; https://doi.org/10.1007/s42454-019-00005-8

Abstract:
Potential benefits of technology such as automation are oftentimes negated by improper use and application. Adaptive systems provide a means to calibrate the use of technological aids to the operator’s state, such as workload state, which can change throughout the course of a task. Such systems require a workload model which detects workload and specifies the level at which aid should be rendered. Workload models that use psychophysiological measures have the advantage of detecting workload continuously and relatively unobtrusively, although the inter-individual variability in psychophysiological responses to workload is a major challenge for many models. This study describes an approach to workload modeling with multiple psychophysiological measures that was generalizable across individuals, and yet accommodated inter-individual variability. Under this approach, several novel algorithms were formulated. Each of these underwent a process of evaluation which included comparisons of the algorithm’s performance to an at-chance level, and assessment of algorithm robustness. Further evaluations involved the sensitivity of the shortlisted algorithms at various threshold values for triggering an adaptive aid.
Guliz Tokadli, Michael C. Dorneich, Michael Matessa, Seiya Eda
Abstract:
This paper presents preliminary results of an evaluation of a Playbook delegation interface for human-autonomy teaming (HAT) in Single Pilot Operations (SPO). In this context, autonomy is defined as a class of automation that acts with more intention and authority, and it behaves more like a team member than a tool. In SPO, there will be a single pilot who will serve as the pilot-in-command (PIC) to make all flight decisions, perform flight tasks, and collaborate with an autonomous teammate during the flight. To enable a move to SPO, an autonomous teammate would share responsibility, authority, and tasks with a human operator to achieve the mission goals. HAT is the study of how to design the functions, interaction, and skills of autonomous teammate to work best with humans as a team. A Playbook interface has been developed as a delegation interface for HAT to support the single pilot during the flights. It allows humans to express their intent to an autonomous teammate to efficiently adapt the function allocation in response to a situation. This may lead to more efficient coordination and joint team performance. The ability to delegate implies that function allocation between teammates can be dynamic and responsive to the current situation. Specifically, in HAT, the challenge in deciding the function allocation prior to and during task execution is how to enable teammates to express their intent to each other quickly and accurately. In SPO, Playbook enables the single pilot to call a template play and modify it with the collaboration of the autonomous teammate. The modification of a play allows not only the changing of task details but also allows changes in allocation between the human and the autonomous teammates. The Playbook evaluation study aims to evaluate (1) the ability of pilots to make function allocation decisions in real-time, and (2) the usability and functionality of the Playbook interface.
, Břetislav Passinger, Christopher Hamblin, Claudia Keinrath, Jiři Vašek, Stephen D. Whitlow, Martijn Beekhuyzen
Published: 28 March 2017
Frontiers in Neuroscience, Volume 11; https://doi.org/10.3389/fnins.2017.00144

Abstract:
This paper presents an adaptive system intended to address workload imbalances between pilots in future flight decks. Team performance can be maximized when task demands are balanced within crew capabilities and resources. Good communication skills enable teams to adapt to changes in workload, and include the balancing of workload between team members This work addresses human factors priorities in the aviation domain with the goal to develop concepts that balance operator workload, support future operator roles and responsibilities, and support new task requirements, while allowing operators to focus on the most safety critical tasks. A traditional closed-loop adaptive system includes the decision logic to turn automated adaptations on and off. This work takes a novel approach of replacing the decision logic, normally performed by the automation, with human decisions. The Crew Workload Manager (CWLM) was developed to objectively display the workload between pilots and recommend task sharing; it is then the pilots who “close the loop” by deciding how to best mitigate unbalanced workload. The workload was manipulated by the Shared Aviation Task Battery (SAT-B), which was developed to provide opportunities for pilots to mitigate imbalances in workload between crew members. Participants were put in situations of high and low workload (i.e. workload was manipulated as opposed to being measured), the workload was then displayed to pilots, and pilots were allowed to decide how to mitigate the situation. An evaluation was performed that utilized the SAT-B to manipulate workload and create workload imbalances. Overall, the CWLM reduced the time spent in unbalanced workload and improved the crew coordination in task sharing while not negatively impacting concurrent task performance. Balancing workload and reducing the time spent in high workload has the potential to improve crew resource management, improve task performance over time, reduce errors, and fatigue pilots less. Paired with a real-time workload measurement system, the CWLM could help teams manage their own task load distribution.
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