ABSTRACT

Vehicle automation is expected to reduce the cost of driving and to solve social problems, such as traffic accidents. However, despite the expected benefits of autonomous vehicles, some consumers hesitate to adopt autonomous vehicles due to fears of negative effects from vehicle automation. This study analyzes consumers’ heterogeneous preferences for autonomous vehicles using a discrete choice experiment and a latent class model, which enables the clustering of consumer preferences. As a result, consumers’ preferences for autonomous vehicles are largely divided into two groups: one group is technology-friendly users (78.0%), and the other group is change avoiders (22.0%). Technology-friendly users tend to prefer advanced vehicle automation and intend to offer their personal information for advanced functions if the information is highly secured and protected. However, change avoiders express tendencies to avoid highly active vehicle automation and are reluctant to use their personal information for operating automation systems. Change avoiders think that laws or regulations specialised for vehicle automation are redundant. In addition, technology-friendly users and change avoiders prefer conditional automation and driver assistance, respectively.

摘要

车辆自动化有望降低驾驶成本并解决交通事故等社会问题。然而，尽管自动驾驶汽车具有预期的好处，但由于担心汽车自动化的负面影响，一些消费者对采用自动驾驶汽车犹豫不决。本研究使用离散选择实验和潜在类别模型分析消费者对自动驾驶汽车的异质偏好，从而实现消费者偏好的聚类。因此，消费者对自动驾驶汽车的偏好主要分为两组：一组是技术友好型用户（78.0%），另一组是避免改变的用户（22.0%）。对技术友好的用户往往更喜欢先进的车辆自动化，并且如果信息高度安全和受保护，他们打算将他们的个人信息提供给高级功能。然而，改变避免者表达了避免高度活跃的车辆自动化的倾向，并且不愿意将他们的个人信息用于操作自动化系统。避免改变的人认为专门针对车辆自动化的法律或法规是多余的。此外，技术友好的用户和避免更改的用户分别更喜欢有条件的自动化和驾驶员辅助。避免改变的人认为专门针对车辆自动化的法律或法规是多余的。此外，技术友好的用户和避免更改的用户分别更喜欢有条件的自动化和驾驶员辅助。避免改变的人认为专门针对车辆自动化的法律或法规是多余的。此外，技术友好的用户和避免更改的用户分别更喜欢有条件的自动化和驾驶员辅助。