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

Fuente: arXiv
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Hauptverfasser: Avetisyan, Lilit, Abolarin, Emmanuel, Zakarian, Vanik, Yang, X. Jessie, Zhou, Feng
Format: Preprint
Veröffentlicht: 2025
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author Avetisyan, Lilit
Abolarin, Emmanuel
Zakarian, Vanik
Yang, X. Jessie
Zhou, Feng
author_facet Avetisyan, Lilit
Abolarin, Emmanuel
Zakarian, Vanik
Yang, X. Jessie
Zhou, Feng
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2504_04508
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Mediating Effects of Emotions on Trust through Risk Perception and System Performance in Automated Driving
Avetisyan, Lilit
Abolarin, Emmanuel
Zakarian, Vanik
Yang, X. Jessie
Zhou, Feng
Human-Computer Interaction
Robotics
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.
title The Mediating Effects of Emotions on Trust through Risk Perception and System Performance in Automated Driving
topic Human-Computer Interaction
Robotics
url https://arxiv.org/abs/2504.04508