工作量
试验台
计算机科学
适应(眼睛)
眼动
凝视
过程(计算)
视觉搜索
实时计算
人机交互
计算机视觉
人工智能
心理学
计算机网络
操作系统
神经科学
作者
Shannon P. Devlin,Jake R. Flynn,Sara L. Riggs
标识
DOI:10.1177/1071181320641083
摘要
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.
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