The Mediating Effects of Emotions on Trust through Risk Perception and System Performance in Automated Driving

TL;DR

This study investigates how emotions mediate trust in automated driving by examining the interplay between risk perception and AV performance. Using a mixed-design experiment with 70 participants, it identifies four emotion factors and demonstrates that real-time AV performance is a stronger determinant of trust than pre-existing risk beliefs. Mediation analyses reveal Confidence as the primary emotional mediator linking AV performance to trust, with hostility and anxiety also contributing negatively, while Loneliness plays no mediating role. The findings have practical implications for user experience design to calibrate trust through positive emotional experiences and transparent system behavior in AVs.

Abstract

Trust in automated vehicles (AVs) has traditionally been explored through a cognitive lens, but growing evidence highlights the significant role emotions play in shaping trust. This study investigates how risk perception and AV performance (error vs. no error) influence emotional responses and trust in AVs, using mediation analysis to examine the indirect effects of emotions. In this study, 70 participants (42 male, 28 female) watched real-life recorded videos of AVs operating with or without errors, coupled with varying levels of risk information (high, low, or none). They reported their anticipated emotional responses using 19 discrete emotion items, and trust was assessed through dispositional, learned, and situational trust measures. Factor analysis identified four key emotional components, namely hostility, confidence, anxiety, and loneliness, that were influenced by risk perception and AV performance. The linear mixed model showed that risk perception was not a significant predictor of trust, while performance and individual differences were. Mediation analysis revealed that confidence was a strong positive mediator, while hostile and anxious emotions negatively impacted trust. However, lonely emotions did not significantly mediate the relationship between AV performance and trust. The results show that real-time AV behavior is more influential on trust than pre-existing risk perceptions, indicating trust in AVs might be more experience-based than shaped by prior beliefs. Our findings also underscore the importance of fostering positive emotional responses for trust calibration, which has important implications for user experience design in automated driving.

Figures (5)

• Figure 1: Mediating relationship between AV Performance, emotions, and trust. ACME stands for Average Causal Mediation Effects, ADE stands for Average Direct Effects, Total Effect is a sum of a mediation (indirect) effect and a direct effect.
• Figure 2: Comparison of trust levels in AV before (Dispositional Trust) and after (Learned Trust) exposure to risk-related information.
• Figure 3: Average Heart Rate across groups.
• Figure 4: Temporal dynamics and of physiological markers (HR and GSR) during error-prone driving scenarios, with corresponding statistical significance indicators.
• Figure 5: Temporal dynamics and of physiological markers (HR and GSR) in high-risk versus low-risk groups during error-free driving scenarios, with corresponding statistical significance indicators.