Supervisors in military command and control (C2) environments face dynamic conditions. Dynamically changing information continuously flows to the supervisors through multiple displays. In this environment, important pieces of information can be overlooked due to the complexity of tasks and environments. This study examined the efficacy of an eye-tracker-based adaptive attention-guided decision support tool (DST) for supervisors in a simulated C2 environment. The DST monitors supervisors' visual attention allocation in real time and displays visually salient cues if critical changes or events are missed. Twenty-five military students participated in a simulated intelligence task. Results indicated significant performance enhancement when the adaptive DST was present. Eye-tracking analysis also showed that longer, more frequent fixations on critical areas of interest were negatively correlated with performance. Additionally, post-experiment interviews revealed that the adaptive DST was unobtrusive and positively received. These findings underscore the potential of real-time gaze-based interventions to optimize supervisory decision-making. Future research could incorporate AI-driven approaches to better support supervisors in complex task environments.

翻译：军事指挥与控制（C2）环境中的监督人员面临着动态变化的复杂条件。动态变化的信息通过多个显示屏持续流向监督人员。在此环境中，由于任务与环境的复杂性，重要信息片段可能被忽视。本研究检验了一种基于眼动追踪的自适应注意力引导决策支持工具（DST）在模拟C2环境中对监督人员的效能。该DST实时监测监督人员的视觉注意力分配，并在其错过关键变化或事件时显示视觉显著性提示。二十五名军事学员参与了一项模拟情报任务。结果表明，当自适应DST启用时，任务绩效得到显著提升。眼动追踪分析亦显示，对关键兴趣区更长、更频繁的注视与任务绩效呈负相关。此外，实验后访谈表明自适应DST具有非侵入性且获得积极评价。这些发现凸显了基于实时注视的干预措施在优化监督决策方面的潜力。未来研究可整合人工智能驱动方法，以在复杂任务环境中为监督人员提供更优支持。