- Matthew Bolton (Chairperson) – SIE
- Sara Riggs (Advisor) – SIE
- Rupa Valdez – SIE
- Seongkook Heo – CS
- Shannon McGarry - U.S. Naval Research Laboratory
Please contact sie-programs for Zoom information.
Title: Enhancing Team Performance and Situational Awareness in UAV Military Operations: A Real-Time Eye Tracking Approach to Display Design
Dynamic and data-rich domains are environments characterized by frequent and rapid changes, often accompanied by substantial volumes of data available for decision-making and task execution, making them challenging and requiring effective coordination and adaptation between operators. Aircraft pilots, for example, need to understand what is happening across a large number of gauges and systems in the aircraft, as well as track their location and that of other aircraft in three-dimensional space, ensure adherence to changing air traffic control clearances, and avoid turbulence and weather systems that can disrupt flight. Data overload is a significant challenge, as are periods of high workload (when there might be too much information changing too rapidly to process) and periods of low workload (when vigilance might be low and other distractions prevalent). The increasing complexity of technology and automation has amplified the need for teamwork, presenting both opportunities and challenges in human-machine interaction. Shared situational awareness (SA) is crucial for successful collaboration, yet lapses in SA contribute significantly to accidents and incidents in safety-critical systems, motivating the need for quantitative measures that capture real-time collaboration dynamics. The central research question explores how eye tracking metrics can enhance our understanding of team collaboration and attention allocation in Unmanned Aerial Vehicle (UAV) military operations. This dissertation evaluates existing scanpath similarity metrics and real-time gaze sharing to quantify team collaboration and adaptation under varying workloads. Two major studies have been conducted to date, contributing insights towards developing practical solutions, including visual display designs and decision support systems, to empower operators in high-stakes environments where teamwork and attention allocation are critical components of success. The ultimate goal is to develop predictive models that assess real-time team cohesion and enhance overall team performance and SA in collaborative tasks, particularly in safety-critical and high-pressure scenarios such as UAV military operations, emergency response, and air traffic control.