随着智能网联汽车产业的战略地位的提升，高级别自动驾驶商业落地是研究热点之一，而商业落地离不开公众接受度。作为国家重点发展的新兴产业，探究智能网联汽车自动驾驶公众接受度的影响因素，有助于加快智能网联汽车的市场渗透率，加速自动驾驶技术和相关产业的在全球供应链体系中的地位提升。本论文采用文献研究法对智能网联汽车、自动驾驶等概念进行厘清，并简要回顾了智能网联汽车产业发展背景及发展现状，梳理了主要国家的自动驾驶制度保障情况。在上述文献评述的研究基础上，基于扩展的技术接受和使用整合理论，提出了10个自动驾驶公众接受度影响因子：绩效期望、努力期望、社会影响、便利条件、享乐动机、价格价值感知、习惯、风险感知、安全和信任，构建了智能网联汽车自动驾驶公众接受度概念模型。根据自动驾驶公众接受度概念模型提出假设。构建完本文的研究模型后，通过问卷调查法获取公众对自动驾驶的接受度调研数据，通过对实证数据进行描述性分析和相关分析，并对其进行结构方程模型拟合，对提出的假设进行检验，探究模型影响因素对自动驾驶公众接受度的影响显著情况。最后，基于上述实证分析结果和研究结论，本论文基于新兴产业发展视角，提出了一些对策建议，包括：完善法律法规、加码数据治理、扩大试验范围、加强宣传引导，并对产业发展提出了未来的研究方向，以促进智能网联汽车的可持续发展和新兴产业的繁荣。

The increasing strategic importance of the Intelligent Connected Vehicles （ICVs） industry has brought the commercial deployment of high-level autonomous driving to the forefront of research. However, the successful commercialization of autonomous driving depends on widespread public acceptance. This is particularly crucial in China, where the ICV industry holds strategic significance. Understanding the factors that influence public acceptance of autonomous driving in ICVs is essential for accelerating market penetration and advancing the global supply chain position of autonomous driving technology and related industries.This paper employs a comprehensive literature review to elucidate concepts related to ICVs, autonomous driving, and provides a brief overview of the background and current status of the ICV industry. Additionally, the paper explores the autonomous driving regulatory landscape in major countries. Building upon this extensive literature review, and drawing from an extended Technology Acceptance Model, the study identifies ten critical factors that impact public acceptance of autonomous driving. These factors include performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price-value perception, habit, risk perception, safety, and trust. These factors are then integrated into a conceptual model of public acceptance of autonomous driving in ICVs.Hypotheses are formulated based on the conceptual model, and a structured questionnaire survey is conducted to collect empirical data on public acceptance of autonomous driving. The gathered data is analyzed descriptively, utilizing correlation analysis, and subjected to Structural Equation Modeling （SEM） to test the hypotheses and examine the significant effects of the model factors on public acceptance of autonomous driving.Finally, based on the empirical findings and research conclusions, the paper provides several policy recommendations from the perspective of emerging industry development. These recommendations include the enhancement of legal regulations, reinforcement of data governance, expansion of test scopes, and increased awareness campaigns. Moreover, the paper suggests future research directions for industry development to facilitate the sustainable growth of ICVs and the prosperity of emerging industries. The academic rigor of this study contributes to the scholarly discourse surrounding autonomous driving and ICVs.