Dynamic and data-rich domains, like those found in the military, primarily rely on multiple operators’ visual attention. Of interest is to understand how shared visual attention impacts performance when workload changes and whether this informs the adaptation process between collaborators. Ten pairs of participants completed a simulated Unmanned Aerial Vehicle control task under two different workload conditions - first under low workload and then under high workload. The best and worst performing pairs were identified and further analyzed by assessing pairs’ percent gaze overlap and strategy when workload changed. The findings showed the best performing pairs not only had higher levels of percent gaze overlap on average, but also increased their percent gaze overlap as workload increased. Additionally, the best performing pairs engaged in the adaptation process with not only their actions, but their overall visual attention allocation strategy. These findings suggest systems and technology in these domains should allow operators to have access to their collaborator’s visual data, in order to provide the opportunity to adapt and dynamically collaborate under different workload conditions.
Data-rich environments rely on operators to collaborate, especially in light of workload changes. This work explores the relationship between the operators’ shared visual attention patterns on a target area of interest (AOI), i.e. the AOI causing a workload change, and how it affects collaborative performance. Eye tracking data was collected from ten pairs of participants who completed two scenarios, the first being low workload and the second being high workload, in an unmanned aerial vehicle (UAV) command and control testbed. Then, best and worst performing pairs were compared in terms of two shared visual attention metrics: (1) percent gaze overlap and (2) the phi coefficient for the target AOI. The results showed that coordinated visits to and from the target AOI were associated with better performance during high workload. These results suggest including quantitative measures of visual attention can be indicators of the adaptation process in real- time.
Dynamic and data-rich domains, like those found in the military, rely heavily on teamwork for their operations. Previous work has attempted to understand how the personality of individuals contributes to overall team performance, but specific links between individual traits and team dimensions are needed. This study aims to link the dimensions from the original Big Five Trait Taxonomy to the Big Five in teamwork. Specifically, the focus was identifying which dimensions in the Big Five Trait Taxonomy influenced the Big Five in teamwork’s core component of adaptability. Ten pairs of participants completed a simulated Unmanned Aerial Vehicle control task. The best and worst performing pairs were identified and further analyzed to assess how pairs enabled adaptability when workload transitioned. The findings showed the best performing pairs enabled team adaptability effectively and had high levels of extraversion, lower levels of diversity across all dimensions, and adopted collaborative strategies to complete all the tasks. These findings suggest operational standards, technology, and training programs should be developed to foster these personality traits and collaborative-base strategies.
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