Eyes on the Mission: Mixed Methods Assessment of Eye-Tracker-Enabled Interactive Decision Support in a Simulated Unmanned Aerial Vehicle System

2026-01-25

AI Summary

This study addresses the challenge of information overload in military command and control, where supervisors often overlook critical dynamic events, impairing decision-making effectiveness. To mitigate this issue, the authors propose and evaluate an adaptive attention-guidance system based on eye-tracking, which monitors operators’ visual attention in real time within a simulated unmanned aerial system environment and delivers salient visual cues when key information is neglected. This approach represents the first integration of real-time eye-tracking with an adaptive prompting mechanism to enable dynamic intervention in attention allocation. Experimental results demonstrate that the system significantly enhances task performance and situational awareness. Eye-movement analyses further reveal a negative correlation between excessive fixation on critical regions and performance. User feedback indicates that the system is non-intrusive and yields a positive user experience.

Technology Category

• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Computer Vision: Motion & Tracking
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements

Abstract

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.

Problem

• command and control
• information overload
• visual attention
• decision support
• unmanned aerial vehicle

Innovation

• eye-tracking
• adaptive decision support
• attention guidance
• human-computer interaction
• command and control