自动化错误发生后,人们对自动化车辆的信任如何变化?自动驾驶中动态信任的实证研究

IF 2.2 3区 工程技术 Q3 ENGINEERING, MANUFACTURING
Hao Tan, Yuyue Hao
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引用次数: 0

摘要

当自动驾驶汽车出现错误时,驾驶员的信任很容易被破坏,导致自动驾驶汽车的使用减少。本研究旨在检验AV的错误如何通过影响驾驶员的主观感知来降低驾驶员的信任。进行了驾驶模拟器实验,其中104名参与者(男性 = 58;女的 = 46)经历了自动化错误的自动驾驶,并对其信任度进行了评级。结果表明,自动化错误会影响驾驶员的感知可预测性、感知可靠性和感知安全性,从而导致信任度下降和放弃自动驾驶。随着自动驾驶汽车自动化错误的发生,感知安全对驾驶员的信任起着至关重要的作用。此外,当自动化错误发生在风险较低的特定任务中时,驾驶员的信任度会比高风险任务下降得更快。本文探讨了AVs自动化错误后驾驶员信任度下降的内在影响,并进一步考虑了不同外部风险对这些感知因素和信任度的影响。这项研究可以帮助电动汽车制造商根据不同的驾驶任务和事故严重程度制定不同程度的信任维修策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How does people's trust in automated vehicles change after automation errors occur? An empirical study on dynamic trust in automated driving

When errors of automated vehicles (AVs) occur, drivers' trust can easily be destroyed, resulting in the reduction of the use of AVs. This study aims to examine how error of AVs declines driver's trust by impacting their subjective perceptions. A driving simulator experiment is conducted, in which 104 participants (male = 58; female = 46) experienced automated driving with automation errors and rated their trust. The results indicate that automation error will affect the driver's perceived predictability, perceived reliability, and perceived safety, which will lead to the decline of trust and abandonment of automated driving. With the occurrence of automation error of AVs, perceived safety plays a more critical role in drivers' trust. In addition, when automation errors occur in specific tasks with low risk, the trust of drivers will drop faster than that in high-risk tasks. This paper has explored the internal effects of the decline of driver's trust after automation errors of AVs, and further considers the influence of different external risks on these perception factors and trust. This study can help AVs manufacturers to formulate different degrees of trust repair strategies according to different driving tasks and accident severity.

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来源期刊
CiteScore
5.20
自引率
8.30%
发文量
37
审稿时长
6.0 months
期刊介绍: The purpose of Human Factors and Ergonomics in Manufacturing & Service Industries is to facilitate discovery, integration, and application of scientific knowledge about human aspects of manufacturing, and to provide a forum for worldwide dissemination of such knowledge for its application and benefit to manufacturing industries. The journal covers a broad spectrum of ergonomics and human factors issues with a focus on the design, operation and management of contemporary manufacturing systems, both in the shop floor and office environments, in the quest for manufacturing agility, i.e. enhancement and integration of human skills with hardware performance for improved market competitiveness, management of change, product and process quality, and human-system reliability. The inter- and cross-disciplinary nature of the journal allows for a wide scope of issues relevant to manufacturing system design and engineering, human resource management, social, organizational, safety, and health issues. Examples of specific subject areas of interest include: implementation of advanced manufacturing technology, human aspects of computer-aided design and engineering, work design, compensation and appraisal, selection training and education, labor-management relations, agile manufacturing and virtual companies, human factors in total quality management, prevention of work-related musculoskeletal disorders, ergonomics of workplace, equipment and tool design, ergonomics programs, guides and standards for industry, automation safety and robot systems, human skills development and knowledge enhancing technologies, reliability, and safety and worker health issues.
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