Eye-Tracking Metrics for Task-Based Supervisory Control
This work addresses usability evaluation for human operators in supervisory control missions, but it is incremental as it focuses on a pilot study without broad SOTA claims.
The study tackled the problem of evaluating usability in task-based supervisory control interfaces by exploring eye-tracking metrics for the RESCHU interface, with results aimed at augmenting standard metrics and modeling operator behavior.
Task-based, rather than vehicle-based, control architectures have been shown to provide superior performance in certain human supervisory control missions. These results motivate the need for the development of robust, reliable usability metrics to aid in creating interfaces for use in this domain. To this end, we conduct a pilot usability study of a particular task-based supervisory control interface called the Research Environment for Supervisory Control of Heterogenous Unmanned Vehicles (RESCHU). In particular, we explore the use of eye-tracking metrics as an objective means of evaluating the RESCHU interface and providing guidance in improving usability. Our main goals for this study are to 1) better understand how eye-tracking can augment standard usability metrics, 2) formulate initial models of operator behavior, and 3) identify interesting areas of future research.