若说过去十年是移动互联网重塑生活的黄金期，未来十年，自动驾驶必将成为改写人类出行逻辑的核心 力量。 从科技巨头到传统车企，再到资本市场的敏锐玩家，都清楚这不仅是技术革新，更是对万亿级市场蛋糕 的激烈角逐。 如今FSDV12已实现"端到端决策"，无需依赖预设规则，直接输出驾驶指令，复杂场景应对能力显著提 升。但短板也突出：暴雨、大雾、强光等场景下，摄像头感知精度易受影响。 技术路线之争：两条路径的较量与进化 如今试驾主流新能源车，L2+级辅助驾驶已不新鲜：自动跟车、车道保持、高速领航，部分车型甚至能 实现城市道路自主变道。 2023年起，城市NOA快速落地，标志着自动驾驶从"简单高速场景"迈向"复杂城市环境"，但这只是行业 序幕。 按国际汽车工程师学会（SAE）标准，自动驾驶分L0至L5六级。目前量产车型多处于L2向L3过渡阶 段，真正的"无人驾驶"（L4/L5）仍局限于特定场景——如Waymo在旧金山的全无人出租车、封闭园区 的自动驾驶物流车。 即便头部企业有局部突破，L4级大规模落地仍面临技术可靠性、法规适配性与成本控制三重考验，而 行业在技术路线选择上已形成两大阵营： 1.纯视觉派：特斯拉的"数据驱动"之 ...

Core Viewpoint - The emergence of Vision-Language-Action (VLA) models is set to revolutionize the intelligent assisted driving industry, moving from traditional modular systems to a more integrated end-to-end architecture, enhancing driving experience and capabilities [1][2][3]. Industry Trends - The intelligent assisted driving sector is witnessing a shift from "usable" to "user-friendly" experiences, driven by the increasing adoption of new energy vehicles and the demand for improved driving assistance [3]. - VLA models are expected to dominate the market, with projections indicating that by 2030, VLA-driven end-to-end solutions could capture 60% of the L4 market share, leading to a reevaluation of the value chain for traditional Tier 1 suppliers [4]. Technological Advancements - The VLA model integrates visual, language understanding, and action decision-making, significantly enhancing scene reasoning and generalization capabilities compared to previous models [2][3]. - The VLA architecture is seen as a more comprehensive evolution of the end-to-end and VLM (Vision-Language Model) combination, addressing limitations in complex driving scenarios [3]. Competitive Landscape - Tesla is positioned as a potential beneficiary of this transformation, with its FSD Beta V12 showing a 76% reduction in intervention frequency compared to the previous version [4]. - Domestic automakers are also actively exploring VLA technologies, with companies like Li Auto emphasizing the importance of VLA in their future models [4]. Manufacturing Innovations - AI is driving a paradigm shift in automotive manufacturing, moving from traditional assembly line methods to more efficient, data-driven "smart island" models [2][5]. - The integration of AI in manufacturing processes is seen as essential for overcoming challenges such as long changeover times and quality fluctuations [6][7]. Future Outlook - The VLA technology is expected to redefine the competitive landscape of the intelligent assisted driving market, leading to a layered market structure rather than a single dominant technology [6]. - The acceptance of AI for process optimization in manufacturing is growing, with companies recognizing the need for comprehensive AI integration to enhance operational efficiency [8].