自动驾驶风险需技术、伦理与政策协同评估
Risk Assessment of Autonomous Driving: Integrating Technical Failures, Ethical Dilemmas, and Policy Frameworks
- 融合事故数据、脱手报告与道德实验，分析三类风险根源
- 感知分类错误占事故报告主要比例，凸显技术短板
- 多地区法规不一加剧应用不确定性，建议协同治理
自动驾驶技术有望减少由人为失误引发的大量交通事故，但同时也带来新型风险，需从技术、伦理与政策三方面综合评估。基于美国国家公路交通安全管理局（NHTSA）的公开事故数据、加州机动车管理局（DMV）的脱手报告、麻省理工学院的Moral Machines道德实验数据集，以及对五个司法辖区的比较性监管分析，研究发现感知与分类错误是主要的技术故障模式，在事故报告中占比较高；同时，自动驾驶决策存在不同的伦理框架，而不同区域间法规不一致，增加了技术大规模应用的不确定性。技术、伦理与监管问题密切相关，需协同解决。本文建议采用更适应性强且具协作性的治理模式，整合工程标准、伦理讨论与制度监督。
原文摘要 · Abstract (English)
Autonomous driving technology has the potential to reduce the large number of road traffic accidents caused by human error each year, but it also brings new types of risks that need to be evaluated from the aspects of technology, ethics and regulations. Based on public crash data from the National Highway Traffic Safety Administration (NHTSA), disengagement reports from the California Department of Motor Vehicles (DMV), the MIT Moral Machines dataset, and a comparative regulatory analysis of five jurisdictions, we have found that the main types of technical failure modes are perception and classification errors. These account for a relatively large proportion of the reported accidents, and it can be concluded that there are different ethical frameworks for autonomous vehicle decision-making, and inconsistent regulations in different areas increase the uncertainty of widespread application. Generally speaking, the problems of technology, ethics and regulation are closely related and need to be solved together. Therefore, this paper recommends a more adaptive and cooperative governance approach that combines engineering standards, ethical discussion, and institutional supervision.
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