Anticipated emotions associated with trust in autonomous vehicles

TL;DR

This study investigates how 19 anticipated emotions relate to different trust levels in autonomous vehicles, considering vehicle performance and trust types, revealing emotional patterns that influence trust in automation.

Contribution

It explores the relationship between emotions and trust in AVs across multiple trust levels and identifies emotional factors underlying situational trust, a novel approach in AV trust research.

Findings

High trust correlates with positive emotions

Failure impacts emotional responses and trust levels

Emotional patterns differ across trust types

Abstract

Trust in automation has been mainly studied in the cognitive perspective, though some researchers have shown that trust is also influenced by emotion. Therefore, it is essential to investigate the relationships between emotions and trust. In this study, we explored the pattern of 19 anticipated emotions associated with two levels of trust (i.e., low vs. high levels of trust) elicited from two levels of autonomous vehicles (AVs) performance (i.e., failure and non-failure) from 105 participants from Amazon Mechanical Turk (AMT). Trust was assessed at three layers i.e., dispositional, initial learned, and situational trust. The study was designed to measure how emotions are affected with low and high levels of trust. Situational trust was significantly correlated with emotions that a high level of trust significantly improved participants' positive emotions, and vice versa. We also identified the underlying factors of emotions associated with situational trust. Our results offered important implications on anticipated emotions associated with trust in AVs.