An Event-Triggered Framework for Trust-Mediated Human-Autonomy Interaction

TL;DR

This paper introduces a hybrid systems framework that models human trust and interaction dynamics with autonomous systems, using event-triggered sampling to improve human-autonomy collaboration in scenarios like robotic search and rescue.

Contribution

The paper presents a novel hybrid systems framework integrating models from autonomous systems and psychology, with event-triggered sampling to enhance human-autonomy interaction design.

Findings

Framework effectively models trust dynamics in human-autonomy interactions.

Application to robotic search and rescue demonstrates improved interaction management.

Parameter tuning insights for practical deployment.

Abstract

Inspired by the increased cooperation between humans and autonomous systems, we present a new hybrid systems framework capturing the interconnected dynamics underlying these interactions. The framework accommodates models arising from both the autonomous systems and cognitive psychology literature in order to represent key elements such as human trust in the autonomous system. The intermittent nature of human interactions are incorporated by asynchronous event-triggered sampling at the framework's human-autonomous system interfaces. We illustrate important considerations for tuning framework parameters by investigating a practical application to an autonomous robotic swarm search and rescue scenario. In this way, we demonstrate how the proposed framework may assist in designing more efficient and effective interactions between humans and autonomous systems.