Dynamic Modeling of Trust in Automation in Human-Autonomy Teaming

Abstract

Quantitative analysis of the relationship between humans and automation becomes increasingly important as the reliance of humans upon automation becomes more commonplace. We present a literature review of key factors—categorized as effects from automation, operator, and the environment—that influence trust in or reliance upon automation. Those factors are treated as parameters in a dynamical systems analysis (DSA) model whose manipulation induces phase transitions in the decision to use automation. A review of the most recent dynamical models indicates a trend toward including increasingly more parameters in increasingly sophisticated models. We review the challenges inherent in that approach and suggest an alternative with precedence in the broader DSA literature that is more parsimonious and amenable to real-time analysis.