Human-Computer Interaction Center (HCIC), RWTH Aachen University, Campus-Boulevard 57, 52074 Aachen, Germany.
Risk Anal. 2019 Feb;39(2):342-357. doi: 10.1111/risa.13190. Epub 2018 Sep 21.
The increasing development of autonomous vehicles (AVs) influences the future of transportation. Beyond the potential benefits in terms of safety, efficiency, and comfort, also potential risks of novel driving technologies need to be addressed. In this article, we explore risk perceptions toward connected and autonomous driving in comparison to conventional driving. In order to gain a deeper understanding of individual risk perceptions, we adopted a two-step empirical procedure. First, focus groups ( ) were carried out to identify relevant risk factors for autonomous and connected driving. Further, a questionnaire was developed, which was answered by 516 German participants. In the questionnaire, three driving technologies (connected, autonomous, conventional) were evaluated via semantic differential (rating scale to identify connotative meaning of technologies). Second, participants rated perceived risk levels (for data, traffic environment, vehicle, and passenger) and perceived benefits and barriers of connected/autonomous driving. Since previous experience with automated functions of driver assistance systems can have an impact on the evaluation, three experience groups have been formed. The effect of experience on benefits and barrier perceptions was also analyzed. Risk perceptions were significantly smaller for conventional driving compared to connected/autonomous driving. With increasing experience, risk perception decreases for novel driving technologies with one exception: the perceived risk in handling data is not influenced by experience. The findings contribute to an understanding of risk perception in autonomous driving, which helps to foster a successful implementation of AVs on the market and to develop public information strategies.
自动驾驶汽车（AVs）的不断发展影响着未来的交通。除了在安全、效率和舒适方面的潜在好处外，还需要解决新型驾驶技术的潜在风险。在本文中，我们探讨了与传统驾驶相比，人们对联网和自动驾驶的风险感知。为了更深入地了解个人的风险感知，我们采用了两步实证程序。首先，进行了焦点小组（ ），以确定自动驾驶和联网驾驶的相关风险因素。进一步，开发了一份问卷，由 516 名德国参与者回答。在问卷中，通过语义差异（识别技术隐含意义的评分量表）对三种驾驶技术（联网、自动驾驶、传统）进行了评估。其次，参与者评估了感知风险水平（数据、交通环境、车辆和乘客）以及联网/自动驾驶的感知收益和障碍。由于对驾驶员辅助系统自动化功能的先前经验可能会对评估产生影响，因此形成了三个经验组。还分析了经验对收益和障碍感知的影响。与联网/自动驾驶相比，传统驾驶的风险感知明显更小。随着经验的增加，新型驾驶技术的风险感知会降低，但有一个例外：处理数据的感知风险不受经验的影响。研究结果有助于理解自动驾驶中的风险感知，这有助于在市场上成功地实施自动驾驶汽车，并制定公共信息策略。
