Trust and Collaboration Testing in Controlled Human-Robot Environments

The need to enhance the understanding of trust dynamics in human-autonomy teams with intensive longitudinal data is pressing. As the feasibility of autonomous teammates grows, it becomes urgent to investigate how people may cultivate, sustain, and restore their trust in them. However, technological limitations have impeded previous research restricting the type of autonomous agent used. The failure to employ agents capable of executing human-like teamwork behaviors and experimental tasks designed for these teams will impede efforts to understand trust development and calibration. The current study aimed to overcome the constraints of past research by pairing participants with a fully autonomous agent in a virtual testbed. Understanding how trust fluctuates in this testbed could pave the way for a deeper understanding of trust dynamics in human-autonomy teams and lead to more effective collaboration.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/cogmi62246.2024.00026
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.64
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Trust and Collaboration Testing in Controlled Human-Robot Environments

Prashant Doshi, Brandon Kang, Kyle Johnsen, Aaron Schecter et al.
1 citations
Human-Automation Interaction and Safety
0.64
article

Trust and Collaboration Testing in Controlled Human-Robot Environments

Prashant Doshi, Brandon Kang, Kyle Johnsen, Aaron Schecter, Neal Outland, John Frericks
article en
1 citations

Abstract

The need to enhance the understanding of trust dynamics in human-autonomy teams with intensive longitudinal data is pressing. As the feasibility of autonomous teammates grows, it becomes urgent to investigate how people may cultivate, sustain, and restore their trust in them. However, technological limitations have impeded previous research restricting the type of autonomous agent used. The failure to employ agents capable of executing human-like teamwork behaviors and experimental tasks designed for these teams will impede efforts to understand trust development and calibration. The current study aimed to overcome the constraints of past research by pairing participants with a fully autonomous agent in a virtual testbed. Understanding how trust fluctuates in this testbed could pave the way for a deeper understanding of trust dynamics in human-autonomy teams and lead to more effective collaboration.

Georgia College & State University (US), University of Georgia (US)
Partnerships for the goals
Openalex Percentile: Top 23%
Human-Automation Interaction and Safety
0.64
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Trust and Collaboration Testing in Controlled Human-Robot Environments — Prashant Doshi, Brandon Kang, et al. · (2024) | TGRS Research Map | TGRS