Trust Modeling and Estimation in Human-Autonomy Interactions

Fuente: arXiv
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Main Authors: Williams, Daniel A., Chapman, Airlie, Little, Daniel R., Manzie, Chris
Format: Preprint
Published: 2025
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author Williams, Daniel A.
Chapman, Airlie
Little, Daniel R.
Manzie, Chris
author_facet Williams, Daniel A.
Chapman, Airlie
Little, Daniel R.
Manzie, Chris
contents Advances in the control of autonomous systems have accompanied an expansion in the potential applications for autonomous robotic systems. The success of applications involving humans depends on the quality of interaction between the autonomous system and the human supervisor, which is particularly affected by the degree of trust that the supervisor places in the autonomous system. Absent from the literature are models of supervisor trust dynamics that can accommodate asymmetric responses to autonomous system performance and the intermittent nature of supervisor-autonomous system communication. This paper focuses on formulating an estimated model of supervisor trust that incorporates both of these features by employing a switched linear system structure with event-triggered sampling of the model input and output. Trust response data collected in a user study with 51 participants were then used identify parameters for a switched linear model-based observer of supervisor trust.
format Preprint
id arxiv_https___arxiv_org_abs_2510_09013
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Trust Modeling and Estimation in Human-Autonomy Interactions
Williams, Daniel A.
Chapman, Airlie
Little, Daniel R.
Manzie, Chris
Robotics
Systems and Control
Advances in the control of autonomous systems have accompanied an expansion in the potential applications for autonomous robotic systems. The success of applications involving humans depends on the quality of interaction between the autonomous system and the human supervisor, which is particularly affected by the degree of trust that the supervisor places in the autonomous system. Absent from the literature are models of supervisor trust dynamics that can accommodate asymmetric responses to autonomous system performance and the intermittent nature of supervisor-autonomous system communication. This paper focuses on formulating an estimated model of supervisor trust that incorporates both of these features by employing a switched linear system structure with event-triggered sampling of the model input and output. Trust response data collected in a user study with 51 participants were then used identify parameters for a switched linear model-based observer of supervisor trust.
title Trust Modeling and Estimation in Human-Autonomy Interactions
topic Robotics
Systems and Control
url https://arxiv.org/abs/2510.09013