Date of Award

8-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Human Factors Psychology

Abstract

Automated systems continue to transform tasks that were once manual, introducing new challenges for operators to maintain situation awareness (SA). This research examines gesture-based icon messages (GIMs) as a transparency strategy to address challenges present in human-autonomy communication (HAC). Drawing from Endsley’s (1995) three-level model of SA, GIMs were designed to convey different types of information: perception, comprehension, and projection. The goal of this work was to understand whether GIMs could be distinguished by operators, and whether they support SA under conditions that reflect the divided attention demands that are common in operational settings. Study 1 focused on assessing whether participants could differentiate between GIMs based on the intended SA level, while Study 2 and Study 3 tested how GIMs influence SA and performance in a low fidelity driving task. Findings from Study 1 showed that participants were able to distinguish between GIMs designed for perception, comprehension, and projection, supporting the idea that these messages can target specific information categories. In Study 2 and Study 3, comprehension level GIMs provided higher SA benefits under multitasking conditions than projection level GIMs, suggesting that message complexity may play a role in operator performance. Text-based messages outperformed GIMs at the projection level, which highlights the importance of considering message format and information type in transparency design. Overall, this research contributes to our understanding of how nonverbal communication strategies can be applied to support SA in HAC, and underscores the need to tailor message design to the demands of the operational context.

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