Year: 2025
Type: article
Abstract: 随着人工智能技术的快速发展，无人驾驶汽车正逐步从概念走向现实。然而，这一新兴技术也带来了诸多法律挑战，责任主体难以确定、归责原则适用混乱、法律法规滞后等问题。特别是在交通事故侵权责任方面，需要从几个方面入手，如明确责任主体认定标准、完善归责原则体系、加强无人驾驶汽车方面法律法规的完善、建立强制保险制度、推动技术创新与标准化、采用差别化的归责原则。文章旨在对无人驾驶汽车交通事故的侵权责任进行深入研究，分析现行法律框架下的归责原则和责任主体认定，探讨现有法律体系的不足，并提出相应的立法建议；探讨当下司法实践的疑难点，提出相应的实践应对方案。通过综合多篇相关文献资料，借鉴域外法律实践，立足本土实践，本文试图为无人驾驶汽车交通事故侵权责任的法律规制提供理论参考和实践指导。With the rapid development of artificial intelligence technology, autonomous vehicles are gradually moving from concept to reality. However, this emerging technology has also brought many legal challenges, such as difficulty in determining the responsible parties, confusion in the application of attribution principles, and lagging laws and regulations. Especially in terms of liability for traffic accident infringement, it is necessary to start from several aspects, such as clarifying the criteria for identifying the responsible party, improving the system of attribution principles, strengthening the improvement of laws and regulations concerning driverless cars, establishing a compulsory insurance system, promoting technological innovation and standardization, and adopting differentiated attribution principles. This article aims to conduct in-depth research on the tort liability of autonomous vehicle traffic accidents, analyze the attribution principles and identification of responsible parties under the current legal framework, explore the shortcomings of the existing legal system, and propose corresponding legislative suggestions; Explore the difficulties in current judicial practice and propose corresponding practical response plans. By synthesizing multiple relevant literature materials, drawing on foreign legal practices, and based on local practices, this article attempts to provide theoretical references and practical guidance for the legal regulation of infringement liability in autonomous vehicle traffic accidents.
Source: Advances in Social Sciences
Author: 进松 郑
Language: English
Subfield: Law
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4412734563