Public perception of autonomous vehicle capability determines judgment of blame and trust in road traffic accidents
Public perception of autonomous vehicle capability determines judgment of blame and trust in road traffic accidents
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DOI：
10.1016/j.tra.2023.103887
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发表时间：
2024-01
期刊：
影响因子：
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通讯作者：
Qiyuan Zhang;Christopher D. Wallbridge;Dylan M. Jones;Phillip L. Morgan
中科院分区：
文献类型：
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作者：
Qiyuan Zhang;Christopher D. Wallbridge;Dylan M. Jones;Phillip L. Morgan
涉及自动驾驶汽车（AV）的道路事故不仅会对责任分配带来法律的挑战，而且还会普遍削弱公众的信任，这可能会减缓该技术的初步采用，并对该技术的持续采用提出质疑。了解公众对此类事件的反应，特别是它们与传统车辆的区别，对于未来的政策制定和立法至关重要，这反过来将塑造自动驾驶汽车行业的格局。在本文中，责任和信任的直觉判断进行了研究，在道路交通事故的模拟场景，涉及自动驾驶汽车或人类驾驶的车辆。在一项初步研究中，六分之五的场景显示出对自动驾驶汽车的更多指责和更少的信任，尽管这些场景在前因和后果方面与人类驾驶员相同。在一个场景中，这种不对称性被急剧逆转;在后续实验中显示的异常取决于人类驾驶员更有可能预见到的事件的程度。更一般地说，这些研究表明，而不是一个普遍的更高的性能标准对自动驾驶汽车的结果，指责和信任是由刻板的概念，机器与人类的能力，在特定的情况下应用的方式，这可能会或可能不会符合客观推导的事态。这些调查结果表明，有必要通过教育活动和立法措施定期校准公众对自动驾驶汽车的知识和期望，这些措施要求对用户进行培训，并及时披露汽车制造商/开发商的产品能力。
Road accidents involving autonomous vehicles (AVs) will not only introduce legal challenges over liability distribution but also generally diminish the public trust that may make itself manifested in slowing the initial adoption of the technology and call into question the continued adoption of the technology. Understanding the public’s reactions to such incidents, especially the way they differentiate from conventional vehicles, is vital for future policy-making and legislation, which will in turn shape the landscape of the autonomous vehicle industry. In this paper, intuitive judgments of blame and trust were investigated in simulated scenarios of road-traffic accidents involving either autonomous vehicles or human-driven vehicles. In an initial study, five of six scenarios showed more blame and less trust attributed to autonomous vehicles, despite the scenarios being identical in antecedents and consequences to those with a human driver. In one scenario this asymmetry was sharply reversed; an anomaly shown in a follow-up experiment to be dependent on the extent to which the incident was more likely to be foreseeable by the human driver. More generally these studies show—rather than being the result of a universal higher performance standard against autonomous vehicles—that blame and trust are shaped by stereotypical conceptions of the capabilities of machines versus humans applied in a context-specific way, which may or may not align with objectively derived state of affairs. These findings point to the necessity of regularly calibrating the public’s knowledge and expectation of autonomous vehicles through educational campaigns and legislative measures mandating user training and timely disclosure from car manufacturers/developers regarding their product capabilities.