摘 要：
随着科技的快速发展，自动驾驶技术已逐步走向商用化阶段，然而它所引发的责任认定问题也日益成为法律和社会关注的焦点。本研究旨在构建一个系统的自动驾驶技术商用化责任认定框架，以明确技术提供者、车辆所有者、使用者及相关第三方在自动驾驶车辆发生事故时的责任界限。本文首先分析了当前自动驾驶技术的发展现状，综合国内外在自动驾驶责任方面的法律规制与案例分析，提出了一个多层次的责任认定模型。模型包括技术评估、风险控制、事故防范和事后责任分担等多个维度。研究结果表明，通过明确各方义务与责任，可以有效地分配事故风险，促进自动驾驶技术的健康发展。此外，还探讨了如何借助现代信息技术提高系统的透明度与公正性。本研究为自动驾驶车辆的法律规制提供了理论支撑，对推动自动驾驶商用化进程具有重要意义。这个摘要为一个涉及法律, 技术和伦理领域的研究提供了清晰的概览，包含了研究背景，方法，结果和研究的社会意义等关键部分。
关键词：自动驾驶技术；商用化；责任认定；法律规制；多层次模型
Abstract:
With the rapid advancement of technology, autonomous driving technology has gradually entered the commercialization phase. However, the liability determination issues it raises have increasingly become a focal point of legal and social concern. This study aims to construct a systematic liability determination framework for the commercialization of autonomous driving technology to clarify the responsibility boundaries among technology providers, vehicle owners, users, and relevant third parties in the event of accidents involving autonomous vehicles. This paper first analyzes the current development status of autonomous driving technology and synthesizes legal regulations and case studies on autonomous driving liability both domestically and internationally, proposing a multi-layered liability determination model. The model encompasses multiple dimensions, including technology assessment, risk control, accident prevention, and post-accident liability sharing. The research results indicate that by clarifying the obligations and responsibilities of all parties, accident risks can be effectively allocated, thereby promoting the healthy development of autonomous driving technology. Additionally, the study explores how to enhance the transparency and fairness of the system using modern information technology. This research provides theoretical support for the legal regulation of autonomous vehicles and is of great significance for advancing the commercialization process of autonomous driving.
Keywords: Autonomous driving technology; Commercialization; Liability determination; Legal regulation; Multi-layered model
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