Trust towards using autonomous taxis: Evidence from Germany

IF 3.5 2区工程技术 Q1 PSYCHOLOGY, APPLIED

Transportation Research Part F-Traffic Psychology and Behaviour Pub Date : 2025-05-15 DOI:10.1016/j.trf.2025.05.007

Wieland Müller , Michael Leyer , Marek Gaugel

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引用次数: 0

Abstract

The emergence of autonomous driving technologies, particularly autonomous taxis (ATs), promises significant benefits for transportation but depends on building user trust. So far there are few ATs, but governments are considering integrating AT offers into their public transportation network worldwide. Despite the fact that it is the ideal time to identify trust factors that must be considered for successful launch, surprisingly little is known. Thus, this study examines the specific dimensions of trust necessary to accept and adopt ATs. We propose a multidimensional model of trust that integrates dispositional, situational, and learned trust across social, data, and technical levels. Using a two-stage approach comprising confirmatory factor analysis and structural equation modelling, we empirically validate these different trust dimensions through a two-point-in-time survey conducted in Germany. The results indicate that each trust dimension positively influences risk behaviour, with situational technical trust having the most substantial influence. Contrary to previous assumptions, perceived relationship risk does not significantly reduce trust, and perceived situational risk does not moderate the trust–risk relationship. Risk propensity is found to be a strong predictor of risk-taking behaviour. Our research provides valuable insights for developers, providers, and policymakers to promote trust and support the introduction of ATs.

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对使用自动驾驶出租车的信任：来自德国的证据

自动驾驶技术的出现，尤其是自动驾驶出租车（at），有望为交通运输带来巨大的好处，但这取决于建立用户的信任。到目前为止，无人驾驶汽车还很少，但各国政府正在考虑将无人驾驶汽车纳入其全球公共交通网络。尽管这是确定成功发行必须考虑的信任因素的理想时机，但令人惊讶的是，我们所知甚少。因此，本研究考察了接受和采用人工智能所需的信任的具体维度。我们提出了一个多维信任模型，该模型整合了社会、数据和技术层面的性格、情境和习得信任。采用两阶段的方法，包括验证性因素分析和结构方程模型，我们通过在德国进行的两个时间点调查，实证验证了这些不同的信任维度。结果表明，各信任维度均对风险行为产生正向影响，其中情境技术信任的影响最为显著。与之前的假设相反，感知到的关系风险并没有显著降低信任，感知到的情境风险也没有调节信任-风险关系。风险倾向被发现是冒险行为的一个强有力的预测因子。我们的研究为开发人员、供应商和政策制定者提供了有价值的见解，以促进信任并支持引入ai。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Transportation Research Part F-Traffic Psychology and Behaviour Multiple-

CiteScore

7.60

自引率

14.60%

发文量

239

审稿时长

71 days

期刊介绍： Transportation Research Part F: Traffic Psychology and Behaviour focuses on the behavioural and psychological aspects of traffic and transport. The aim of the journal is to enhance theory development, improve the quality of empirical studies and to stimulate the application of research findings in practice. TRF provides a focus and a means of communication for the considerable amount of research activities that are now being carried out in this field. The journal provides a forum for transportation researchers, psychologists, ergonomists, engineers and policy-makers with an interest in traffic and transport psychology.