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 has the potential to improve crew resource management and task performance over time, and reduce errors and fatigue. Paired with a real-time workload measurement system, the CWLM could help teams manage their own task load distribution.
Highlights
The capacity of the existing Air Traffic Management (ATM) systems are restricted due to current procedures and the workload limitations of air traffic controllers (Quon, 2010)
This enabled the experimenters to assess the validity of displaying the workload distribution to pilots via the Crew Workload Manager (CWLM) without confounding the results with the accuracy of the cognitive state assessment itself
This work takes a novel approach of replacing the decision logic, normally performed by the automation, with human decision logic
Summary
The capacity of the existing Air Traffic Management (ATM) systems are restricted due to current procedures and the workload limitations of air traffic controllers (Quon, 2010). For the work presented in this paper, cognitive state was manipulated using the SAT-B (see section) This enabled the experimenters to assess the validity of displaying the workload distribution to pilots via the CWLM without confounding the results with the accuracy of the cognitive state assessment itself (an area of future work). The pilot study determined the distribution of tasks (and each task rate) between two users to produce levels of low, medium, and high task load. The pilot study determined that 30 min of practice time enabled participants to become practiced in the SAT-B tasks, with negligible learning effect with subsequent practice. This was used to set the training and practice time in the experiment at 60 min to ensure there was no learning effect
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