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Proceedings Paper

Building a framework to manage trust in automation
Author(s): J. S. Metcalfe; A. R. Marathe; B. Haynes; V. J. Paul; G. M. Gremillion; K. Drnec; C. Atwater; J. R. Estepp; J. R. Lukos; E. C. Carter; W. D. Nothwang
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Paper Abstract

All automations must, at some point in their lifecycle, interface with one or more humans. Whether operators, end-users, or bystanders, human responses can determine the perceived utility and acceptance of an automation. It has been long believed that human trust is a primary determinant of human-automation interactions and further presumed that calibrating trust can lead to appropriate choices regarding automation use. However, attempts to improve joint system performance by calibrating trust have not yet provided a generalizable solution. To address this, we identified several factors limiting the direct integration of trust, or metrics thereof, into an active mitigation strategy. The present paper outlines our approach to addressing this important issue, its conceptual underpinnings, and practical challenges encountered in execution. Among the most critical outcomes has been a shift in focus from trust to basic interaction behaviors and their antecedent decisions. This change in focus inspired the development of a testbed and paradigm that was deployed in two experiments of human interactions with driving automation that were executed in an immersive, full-motion simulation environment. Moreover, by integrating a behavior and physiology-based predictor within a novel consequence-based control system, we demonstrated that it is possible to anticipate particular interaction behaviors and influence humans towards more optimal choices about automation use in real time. Importantly, this research provides a fertile foundation for the development and integration of advanced, wearable technologies for sensing and inferring critical state variables for better integration of human elements into otherwise fully autonomous systems.

Paper Details

Date Published: 18 May 2017
PDF: 11 pages
Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 101941U (18 May 2017); doi: 10.1117/12.2264245
Show Author Affiliations
J. S. Metcalfe, U.S. Army Research Lab. (United States)
A. R. Marathe, U.S. Army Research Lab. (United States)
B. Haynes, U.S. Army Tank Automotive Research, Development and Engineering Ctr. (United States)
V. J. Paul, U.S. Army Tank Automotive Research, Development and Engineering Ctr. (United States)
G. M. Gremillion, U.S. Army Research Lab. (United States)
K. Drnec, U.S. Army Research Lab. (United States)
C. Atwater, U.S. Army Tank Automotive Research, Development and Engineering Ctr. (United States)
DCS Corp. (United States)
J. R. Estepp, Air Force Research Lab. (United States)
J. R. Lukos, Space and Naval Warfare Systems Command (United States)
E. C. Carter, U.S. Army Research Lab. (United States)
W. D. Nothwang, U.S. Army Research Lab. (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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