Human Trust Measurement Using an Immersive Virtual Reality Autonomous Vehicle Simulator

Shervin Shahrdar, Corey Park, Mehrdad Nojoumian
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引用次数: 20

Abstract

Recent studies indicate that people are negatively predisposed toward utilizing autonomous systems. These findings highlight the necessity of conducting research to better understand the evolution of trust between humans and growing autonomous technologies such as self-driving cars (SDC). This research presents a new approach for real-time trust measurement between passengers and SDCs. We utilized a new structured data collection approach along with a virtual reality SDC simulator to understand how various autonomous driving scenarios can increase or decrease human trust and how trust can be re-built in the case of incidental failures. To verify our methodology, we designed and conducted an empirical experiment on 50 human subjects. The results of this experiment indicated that most subjects could rebuild trust during a reasonable time frame after the system demonstrated faulty behavior. Our analysis showed that this approach is highly effective for collecting real-time data from human subjects and lays the foundation for more-involved future research in the domain of human trust and autonomous driving.
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基于沉浸式虚拟现实自动驾驶汽车模拟器的人类信任测量
最近的研究表明,人们对使用自主系统有负面倾向。这些发现强调,为了更好地理解人类与自动驾驶汽车(SDC)等不断发展的自动驾驶技术之间信任的演变,有必要进行研究。本研究提出了一种乘客与SDCs之间实时信任测量的新方法。我们利用一种新的结构化数据收集方法以及虚拟现实SDC模拟器来了解各种自动驾驶场景如何增加或减少人类的信任,以及在意外故障的情况下如何重建信任。为了验证我们的方法,我们设计并对50名人类受试者进行了实证实验。实验结果表明,在系统表现出错误行为后,大多数被试能够在合理的时间框架内重建信任。我们的分析表明,这种方法对于收集人类受试者的实时数据非常有效,并为未来在人类信任和自动驾驶领域的更多研究奠定了基础。
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