The mediating effects of emotions on trust through risk perception and system performance in automated driving

IF 5.1 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS
Lilit Avetisyan , Emmanuel Abolarin , Vanik Zakarian , X. Jessie Yang , Feng Zhou
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引用次数: 0

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 moves beyond correlation to formally test the mechanisms through which emotions mediate the relationship between real-time AV performance and trust. We conducted an experimental study with 70 participants (42 male, 28 female) who viewed real-life AV recordings operating with or without errors, coupled with varying levels of risk information (high, low, or none). Participants reported their anticipated emotional responses using 19 discrete emotion items, while trust was assessed through dispositional, learned, and situational trust measures. Through factor analysis, 4 key emotional components were extracted, namely hostility, confidence, anxiety, and loneliness, that were influenced by risk perception and AV performance. Using mediation analysis, the extent to which four emotional factors explain the effect of AV performance on trust was quantified. 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. The mediation analysis revealed major asymmetry in the power of emotional mediators: confidence emerged as the primary psychological pathway to trust, mediating 46.7% of the performance–trust effect. In contrast, negative emotions showed substantially weaker mediating effects. Hostility (11.3%) and anxiety (17.7%) were significant but substantially weaker negative mediators, while loneliness did not significantly mediate the relationship between AV performance and trust. Linear mixed modeling supported these patterns, confirming that unlike risk perception, AV performance and individual differences serve as the primary predictors of trust. These findings quantify trust’s emotional architecture, revealing that fostering positive emotional responses is more powerful than mitigating negative ones. AV development should therefore prioritize performance reliability and confidence building over safety communication or anxiety reduction.
自动驾驶中情绪对信任的中介作用:风险感知和系统绩效
传统上,对自动驾驶汽车(av)的信任一直是通过认知视角来探索的,但越来越多的证据表明,情感在塑造信任方面发挥着重要作用。本研究超越了相关性,正式测试了情绪调节实时AV性能与信任之间关系的机制。我们对70名参与者(42名男性,28名女性)进行了一项实验研究,他们观看了真实的AV录音,有或没有错误,同时有不同程度的风险信息(高、低或无)。参与者报告了他们预期的情绪反应,使用19个离散的情绪项目,而信任是通过性格、学习和情境信任来评估的。通过因子分析,提取敌意、自信、焦虑和孤独4个关键情绪成分,分别受风险感知和AV表现的影响。运用中介分析,量化了四种情绪因素对AV绩效对信任影响的解释程度。结果表明,实时自动驾驶汽车行为对信任的影响大于预先存在的风险感知,表明自动驾驶汽车的信任可能更多地基于经验,而不是由先前的信念塑造。中介分析揭示了情绪中介力量的不对称性:信心成为信任的主要心理途径,中介了46.7%的绩效信任效应。相反,负面情绪的中介作用明显较弱。敌意(11.3%)和焦虑(17.7%)是显著但明显较弱的负向中介,而孤独感在AV表现与信任之间的中介作用不显著。线性混合模型支持这些模式,证实与风险感知不同,AV表现和个体差异是信任的主要预测因子。这些发现量化了信任的情感结构,揭示了培养积极的情绪反应比减轻消极的情绪反应更有力。因此,自动驾驶汽车的开发应优先考虑性能可靠性和建立信心,而不是安全沟通或减少焦虑。
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来源期刊
International Journal of Human-Computer Studies
International Journal of Human-Computer Studies 工程技术-计算机:控制论
CiteScore
11.50
自引率
5.60%
发文量
108
审稿时长
3 months
期刊介绍: The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities. Research areas relevant to the journal include, but are not limited to: • Innovative interaction techniques • Multimodal interaction • Speech interaction • Graphic interaction • Natural language interaction • Interaction in mobile and embedded systems • Interface design and evaluation methodologies • Design and evaluation of innovative interactive systems • User interface prototyping and management systems • Ubiquitous computing • Wearable computers • Pervasive computing • Affective computing • Empirical studies of user behaviour • Empirical studies of programming and software engineering • Computer supported cooperative work • Computer mediated communication • Virtual reality • Mixed and augmented Reality • Intelligent user interfaces • Presence ...
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