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Proceedings Paper

Situation awareness-based agent transparency for human-autonomy teaming effectiveness
Author(s): Jessie Y. C. Chen; Michael J. Barnes; Julia L. Wright; Kimberly Stowers; Shan G. Lakhmani
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Paper Abstract

We developed the Situation awareness-based Agent Transparency (SAT) model to support human operators’ situation awareness of the mission environment through teaming with intelligent agents. The model includes the agent's current actions and plans (Level 1), its reasoning process (Level 2), and its projection of future outcomes (Level 3). Human-inthe-loop simulation experiments have been conducted (Autonomous Squad Member and IMPACT) to illustrate the utility of the model for human-autonomy team interface designs. Across studies, the results consistently showed that human operators’ task performance improved as the agents became more transparent. They also perceived transparent agents as more trustworthy.

Paper Details

Date Published: 18 May 2017
PDF: 6 pages
Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 101941V (18 May 2017); doi: 10.1117/12.2263194
Show Author Affiliations
Jessie Y. C. Chen, U.S. Army Research Lab. (United States)
Michael J. Barnes, U.S. Army Research Lab. (United States)
Julia L. Wright, U.S. Army Research Lab. (United States)
Kimberly Stowers, Univ. of Central Florida (United States)
Shan G. Lakhmani, Univ. of Central Florida (United States)


Published in SPIE Proceedings Vol. 10194:
Micro- and Nanotechnology Sensors, Systems, and Applications IX
Thomas George; Achyut K. Dutta; M. Saif Islam, Editor(s)

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