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你会信任无人驾驶服务吗?使用非言语社会线索形成行人的信任和态度。

Would You Trust Driverless Service? Formation of Pedestrian's Trust and Attitude Using Non-Verbal Social Cues.

机构信息

Department of Human Environment and Design/Human Life Innovation Design, Yonsei University, Seoul 03722, Korea.

Department of Design Science, Graduate School of Techno Design, Kookmin University, Seoul 02707, Korea.

出版信息

Sensors (Basel). 2022 Apr 6;22(7):2809. doi: 10.3390/s22072809.

DOI:10.3390/s22072809
PMID:35408424
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9002600/
Abstract

Despite the widespread application of Autonomous Vehicles (AV) to various services, there has been relatively little research carried out on pedestrian-AV interaction and trust within the context of service provided by AV. This study explores the communication design strategy promoting a pedestrian's trust and positive attitude to driverless services within the context of pedestrian-AV interaction using non-verbal social cues. An empirical study was conducted with an experimental VR environment to measure participants' intimacy, trust, and brand attitude toward AV. Further understanding of their social interaction experiences was explored through semi-structured interviews. As a result of the study, the interaction effect of social cues was found, and it was revealed that brand attitude was formed by the direct effects of intimacy and trust as well as the indirect effects of intimacy through trust's mediation. Furthermore, 'Conceptual Definition of Space' was identified to generate differences in the interplay among intimacy, trust, and brand attitude according to social cues. Quantitative and qualitative results were synthesized to discuss implications considering the service context. Practical implications were also addressed suggesting specific design strategies for utilizing the sociality of AV.

摘要

尽管自动驾驶汽车 (AV) 在各种服务中得到了广泛应用,但在 AV 提供服务的背景下,针对行人和 AV 之间的互动和信任问题的研究相对较少。本研究通过非语言的社会线索,探讨了在行人和 AV 互动的背景下促进行人对无人驾驶服务的信任和积极态度的沟通设计策略。通过实验性虚拟现实环境进行了一项实证研究,以衡量参与者对 AV 的亲密感、信任和品牌态度。通过半结构化访谈进一步探讨了他们的社会互动体验。研究结果发现了社会线索的交互效应,揭示了品牌态度是由亲密感和信任的直接效应以及亲密感通过信任的中介效应的间接效应形成的。此外,还确定了“空间的概念定义”,根据社会线索产生亲密感、信任和品牌态度之间相互作用的差异。综合了定量和定性结果,讨论了考虑服务背景的意义。还提出了一些实际意义,为利用 AV 的社交性提出了具体的设计策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0f/9002600/016479d070e2/sensors-22-02809-g010.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0f/9002600/3e5babeb5ffa/sensors-22-02809-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0f/9002600/7b160435cd78/sensors-22-02809-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0f/9002600/016479d070e2/sensors-22-02809-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0f/9002600/d0b5f3fa0eba/sensors-22-02809-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0f/9002600/234d261946b7/sensors-22-02809-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0f/9002600/49c25e0e6619/sensors-22-02809-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0f/9002600/323e7fa6cc3a/sensors-22-02809-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0f/9002600/3e5babeb5ffa/sensors-22-02809-g008.jpg
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本文引用的文献

1
Development of an EEG Headband for Stress Measurement on Driving Simulators.开发一种用于驾驶模拟器应激测量的 EEG 头带。
Sensors (Basel). 2022 Feb 24;22(5):1785. doi: 10.3390/s22051785.
2
Shaping driver-vehicle interaction in autonomous vehicles: How the new in-vehicle systems match the human needs.塑造自动驾驶汽车中的驾驶员-车辆交互:新型车载系统如何满足人类需求。
Appl Ergon. 2021 Jan;90:103238. doi: 10.1016/j.apergo.2020.103238. Epub 2020 Sep 30.
3
Trust in AI Agent: A Systematic Review of Facial Anthropomorphic Trustworthiness for Social Robot Design.
对 AI 代理的信任:用于社交机器人设计的面部拟人化可信度的系统评价。
Sensors (Basel). 2020 Sep 7;20(18):5087. doi: 10.3390/s20185087.
4
Social behavior for autonomous vehicles.自主车辆的社会行为。
Proc Natl Acad Sci U S A. 2019 Dec 10;116(50):24972-24978. doi: 10.1073/pnas.1820676116. Epub 2019 Nov 22.
5
Predictors of Attitudes Toward Autonomous Vehicles: The Roles of Age, Gender, Prior Knowledge, and Personality.对自动驾驶汽车态度的预测因素:年龄、性别、先验知识和个性的作用。
Front Psychol. 2018 Dec 18;9:2589. doi: 10.3389/fpsyg.2018.02589. eCollection 2018.
6
Trust in automation: integrating empirical evidence on factors that influence trust.对自动化的信任:整合关于影响信任因素的实证证据。
Hum Factors. 2015 May;57(3):407-34. doi: 10.1177/0018720814547570. Epub 2014 Sep 2.
7
MorePower 6.0 for ANOVA with relational confidence intervals and Bayesian analysis.MorePower 6.0 用于具有关系置信区间和贝叶斯分析的方差分析。
Behav Res Methods. 2012 Dec;44(4):1255-65. doi: 10.3758/s13428-012-0186-0.
8
Trust in automation: designing for appropriate reliance.对自动化的信任:设计适度的依赖。
Hum Factors. 2004 Spring;46(1):50-80. doi: 10.1518/hfes.46.1.50_30392.