有意义的人类控制视角下部分自动驾驶系统用户感知研究：以特斯拉用户为例
A Meaningful Human Control Perspective on User Perception of Partially Automated Driving Systems: A Case Study of Tesla Users
AI总结：
本研究以特斯拉FSD Beta用户访谈数据为基础，考察有意义的人类控制与用户安全感和信任之间的一致性，发现系统对用户驾驶理由的追踪与感知安全信任相关，但在危险情境中追踪失败始终导致低信任和不安全感，为设计安全可信的自动驾驶系统提供依据。
摘要：
部分自动驾驶系统的使用引发了对潜在责任问题的担忧，对这些技术的系统安全性、接受度和采用构成了风险。有意义的人类控制概念正是为回应责任鸿沟问题而提出的，它要求满足两个条件：追踪（tracking）和追溯（tracing）。尽管这一概念为自动驾驶系统提供了重要的哲学和设计见解，但目前关于有意义的人类控制如何与实际用户的 subjective 体验相关联的知识仍然很少。为填补这一空白，本研究旨在考察有意义的人类控制程度与驾驶员在真实世界部分自动驾驶系统中对安全性和信任的感知之间的一致性。我们利用了先前收集的来自特斯拉“全自动驾驶”（Full Self-Driving，FSD）Beta 用户的访谈数据，考察用户感知与系统追踪用户理由的程度之间的一致性。我们发现，系统对用户驾驶任务理由（如安全操控）的追踪与感知安全性和信任相关，尽管存在显著例外。令人意外的是，未能追踪变道和制动理由并不一定与对安全性的负面感知相关联。然而，系统在危险情境中未能追踪预期操控总是导致低信任和感知到的安全性缺失。总体而言，我们的分析既揭示了一致性之处，也揭示了一方面感知安全性与信任、另一方面有意义的人类控制之间可能存在的差异。我们的结果可以帮助自动驾驶技术开发者设计处于有意义的人类控制之下、并被用户感知为安全且值得信赖的系统。
英文摘要：
The use of partially automated driving systems raises concerns about potential responsibility issues, posing risk to the system safety, acceptance, and adoption of these technologies. The concept of meaningful human control has emerged in response to the responsibility gap problem, requiring the fulfillment of two conditions, tracking and tracing. While this concept has provided important philosophical and design insights on automated driving systems, there is currently little knowledge on how meaningful human control relates to subjective experiences of actual users of these systems. To address this gap, our study aimed to investigate the alignment between the degree of meaningful human control and drivers' perceptions of safety and trust in a real-world partially automated driving system. We utilized previously collected data from interviews with Tesla "Full Self-Driving" (FSD) Beta users, investigating the alignment between the user perception and how well the system was tracking the users' reasons. We found that tracking of users' reasons for driving tasks (such as safe maneuvers) correlated with perceived safety and trust, albeit with notable exceptions. Surprisingly, failure to track lane changing and braking reasons was not necessarily associated with negative perceptions of safety. However, the failure of the system to track expected maneuvers in dangerous situations always resulted in low trust and perceived lack of safety. Overall, our analyses highlight alignment points but also possible discrepancies between perceived safety and trust on the one hand, and meaningful human control on the other hand. Our results can help the developers of automated driving technology to design systems under meaningful human control and are perceived as safe and trustworthy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
