ZUZSFE 同比增长8.5 总销量强势领跑 连续6年 三大新能源品牌齐创新高 海外销量乘风破浪用 本报讯 （记者冯雨瑶）在2025年汽车行业竞争白热化的市场环境中，长安汽车（000625）以一系列突破性业绩，提交了一份企业稳健向上的出色答卷。 2026年1月2日发布的销量快报显示，长安汽车2025年全年总销量强势领跑，创近9年新高。与此同时，新能源板块首破百万辆大关，三大新能源品牌齐创新 高；海外市场亦乘风破浪，再创佳绩。2025年，长安汽车以"四大维度齐创新高"的优秀成绩，系统展现了企业高质量发展的强劲势头和可持续发展的战略韧 性。 另一方面也根植于长安汽车始终坚持以科技创新，持续夯实自身核心竞争力。新能源领域，自研"金钟罩"电池、智慧新蓝鲸，以及行业首款多合一电驱等成 果相继落地；智能化领域，"北斗天枢"计划迭代至2.0版，打造了全球领先的SDA平台，发布了"新长安 新安全——天枢智能"品牌、确立了"泛安全"体系。 特别是在智能驾驶领域，长安汽车作为首批获得L3级自动驾驶产品准入许可的汽车企业，率先推动中国汽车品牌进入L3级自动驾驶时代，将技术优势直接 转化为产品竞争力与用户信任力，智能化正成为驱动企业 ...

法规与标准层面的滞后性同样制约着行业发展。尽管京渝等地已出台地方性法规，明确L3级系统 激活期间由车企承担主要责任，驾驶员未及时接管则需自行担责，但全国性的事故认定标准仍未统一。 跨城市行驶时，不同地区对数据存证、责任划分的要求差异较大，给车企规模化推广带来合规挑战。数 据治理方面，自动驾驶系统每秒产生的海量数据涉及隐私保护与跨境存储，目前缺乏全国性统一规范， 既影响数据共享效率，也增加了企业合规成本。保险机制衔接也存在空白，尽管北京要求车企购买每车 不低于500万元的交通事故责任险，但针对L3级的专属保险产品仍处于探索阶段，EDR数据追溯机制与 理赔流程的衔接也仍需完善。 生态协同与用户认知的偏差则构成了落地的第三重障碍。L3 级自动驾驶的商业化绝非单一企业能 单打独斗完成，需要车企、通信企业、基建运营商、保险机构等多方协同。但目前路侧单元与车联网基 础设施存在区域割裂，跨区域路侧感知网络建设投入巨大，商业模式尚不清晰，导致车企配合度不足。 用户层面，认知偏差可能引发安全风险与信任危机。部分消费者对L3级"系统主导、按需接管"的规则存 在误读，过度追求"脱手脱眼"的使用体验，忽视了驾驶员的接管义务。 面对机 ...

Core Viewpoint - The Chinese automotive industry has shifted from a phase of rapid expansion driven by investment and storytelling to a focus on efficiency and realization, emphasizing cash flow, profitability models, technology compliance, and global operational capabilities [2][3]. Group 1: Market Volume - The key question for 2026 is whether the new energy vehicle (NEV) market can surpass the 20 million unit threshold, with growth driven by factors such as trade-in programs, lower-tier markets, and improved charging experiences [4][5]. - The Chinese government has introduced a new trade-in subsidy policy for 2026, which is expected to stimulate demand in the automotive sector [6][7]. - Predictions for 2026 NEV sales vary, with estimates ranging from a 10% growth (14.14 million units) to a more optimistic 28.4% growth (16.5 million units), particularly in the 150,000 to 200,000 yuan price range [8][10]. Group 2: Profit Expectations - The industry is transitioning from a focus on scale to profitability, with competition intensifying in the 200,000 to 400,000 yuan price range [9][22]. - Companies like Geely are expected to see profit growth from multiple sources, while others like GAC face significant challenges [31][32]. Group 3: L3 and Intelligent Driving - The introduction of L3 autonomous driving is expected to shift responsibility from drivers to manufacturers, leading to systemic changes in the automotive ecosystem [38][40]. - The L3 era will likely drive the standardization of L2 features across all vehicles, increasing competition in the intelligent driving space [42][43]. Group 4: Luxury Narrative - The luxury narrative in the NEV sector is becoming increasingly complex, with a need for brands to establish genuine value propositions beyond just high-end features [50][51]. - The market for luxury vehicles priced above 300,000 yuan is growing slowly, while more affordable segments are seeing significant growth [57][60]. Group 5: Overseas Expansion - Chinese automotive exports are projected to exceed 8 million units in 2025, with significant growth in markets like Mexico and the UAE [67][68]. - The establishment of overseas production facilities is crucial for meeting demand and avoiding trade barriers, with many companies rapidly expanding their international manufacturing capabilities [72][73]. Group 6: AI Cross-Industry Moves - The focus for 2026 will likely shift away from ambitious cross-industry ventures towards enhancing core automotive services through AI, as companies learn from past experiences [78][81].

文 陈燕南 最近，在北京的道路上出现了一组特殊的汽车号牌——京AA0001Z、京AA0733Z、京AA0880Z。不同 于普通号牌的编码逻辑，这组号牌的字母组合与数字序列，承载着中国智能网联汽车产业的历史性突 破：它们是全国首批自动驾驶专用正式号牌。 据了解，近期，工业和信息化部正式公布我国首批L3级有条件自动驾驶车型准入许可，两款分别适配 城市拥堵、高速路段的车型将在北京、重庆指定区域开展上路试点，标志着我国L3级自动驾驶从测试 阶段迈入商业化应用的关键一步。 车百会理事长张永伟对《中国经营报》记者表示，此次放开L3试点，意味着智能驾驶的竞争"真正开 始"。但这只是第一步，关键在于 "技术要一步一步进行验证"。L3车型上路后，将实际检验并推动交通 管理、保险理赔、责任认定、政策法规等整个社会配套体系的同步完善。 中国汽车工业协会常务副会长兼秘书长付炳锋则对记者表示，这标志着我国自动驾驶汽车产业正从"技 术验证"加速迈向"量产应用"的新阶段。 2025年，对于全球自动驾驶产业而言，是L3级有条件自动驾驶从"技术验证"迈向"商业化落地"的关键一 年。从我国首批L3车型获准入许可，到首块专用号牌正式发放；从多传感 ...

今天是2026年的第一天，也是躺倒鸭陪伴大家的第十年。 回望过去的一年，可以用一句话概括："本以为从从容容、游刃有余，没想到是匆匆忙忙、连滚带爬。" 科技浪潮翻涌不息，从汽车、数码到AI、机器人等，一切皆在加速迭代，令人目不暇接。 这一年的大小事，鸭鸭都写成了一篇篇文章，在每个中午与大家准时相见。现在，一起共同翻开这份回忆。 AI：从Chat到Agent 年初，DeepSeek R1如同一声春雷般，在网络上形成一股强烈的冲击波，打破闭源模型的统治，以前所未有的影响力轰动全球科技圈。 GPT-5、Gemini 3.0、xAI Grok、Sora 2等正面冲击传统互联网，你追我赶。 各家大厂开始AI Agent化，AI不再只是回答问题，开始能自主调用外部工具来完成复杂任务。 年末豆包手机的爆火，让普通人最直观最近距离感受到AI如何代替人类进行复杂操作。 而英伟达成为全球首家5万亿美元公司，或许它才是AI时代的最大赢家。 人形机器人：量产元年 3月新修订的《电动汽车用动力蓄电池安全要求》强制性国家标准正式发布，要求动力电池要实现"不起火、不爆炸"。 4月，相关部门接连出手，明确要求车企不得进行夸大和虚假宣传，严禁使 ...

深蓝汽车董事长邓承浩在接受新京报贝壳财经等媒体采访时表示，目前的L3级自动驾驶尚处于探索 期，更侧重于B端。L2级与L3级的最大区别就是从辅助驾驶变成自动驾驶，这一跨越的背后也是责任主 体的变化。 深蓝已基本实现盈亏平衡 获得工信部首批L3级有条件自动驾驶车型准入许可后，长安汽车旗下深蓝汽车首批46辆L3级自动驾驶 号牌车辆12月26日在重庆正式上路通行。 新京报贝壳财经：深蓝汽车此次获得C轮融资主要投向哪些方面？ 邓承浩：发生交通事故，首先，车与车之间的责任是按照现行的交规认定。如果最后责任落到车辆上， 则需要划分是车的责任还是驾驶员的责任。如果是驾驶员在开，则是驾驶员责任；如果是车在开，那就 是车的责任。而车的责任背后兜底方是企业及系统供应商。 邓承浩：深蓝汽车核心产品正进入全新一代关键期。面向全新一代产品要做三件事：一是代际化的全新 技术供给，二是品牌定位，扩大消费者对品牌的认知；第三是提升营销能力，包括终端品牌渠道等。 深蓝汽车已基本实现盈亏平衡，未来必须走向盈利自循环和资产负债率自主下降的过程。这一轮融资将 主要投入上述三个领域，用2-3年的时间让深蓝汽车真正进入全新的阶段。 新京报贝壳财经：如何判 ...

获得工信部首批L3级有条件自动驾驶车型准入许可后，长安汽车（000625）旗下深蓝汽车首批46辆L3 级自动驾驶号牌车辆12月26日在重庆正式上路通行。 深蓝汽车董事长邓承浩在接受新京报贝壳财经等媒体采访时表示，目前的L3级自动驾驶尚处于探索 期，更侧重于B端。L2级与L3级的最大区别就是从辅助驾驶变成自动驾驶，这一跨越的背后也是责任主 体的变化。 深蓝已基本实现盈亏平衡 新京报贝壳财经：深蓝汽车此次获得C轮融资主要投向哪些方面？ 邓承浩：深蓝汽车核心产品正进入全新一代关键期。面向全新一代产品要做三件事：一是代际化的全新 技术供给，二是品牌定位，扩大消费者对品牌的认知；第三是提升营销能力，包括终端品牌渠道等。 深蓝汽车已基本实现盈亏平衡，未来必须走向盈利自循环和资产负债率自主下降的过程。这一轮融资将 主要投入上述三个领域，用2-3年的时间让深蓝汽车真正进入全新的阶段。 新京报贝壳财经：如何判断明年汽车市场的发展趋势？ 汽车行业将从高速增长风口转向低速增长但高质量发展的阶段，这时候比拼的是企业能力。这也是此次 深蓝汽车融资的原因之一，要提升能力，练内功。 L3级交通责任划分更复杂 新京报贝壳财经：为何重庆和北京 ...

当2025年底工信部公布我国首批L3级有条件自动驾驶车型准入许可时，许多人下意识地发出疑问：这 次开车真的可以"脱手"了吗？ "目前，每辆L3级自动驾驶车辆上，都必须配备一名经过专业认证的驾驶员进行驾驶，(C端用户)还不能 单独驾驶。"12月26日，深蓝汽车董事长邓承浩在接受《每日经济新闻》记者采访时表示，眼下，L3级 自动驾驶(以下或简称L3级)尚处探索期，更侧重于B端。 在邓承浩的阐述中，深蓝汽车从2023年开始申报L3级路测资格牌照，到进入我国首批L3级有条件自动 驾驶车型准入许可名单，再到拿到国内首块L3级自动驾驶专用正式号牌"渝AD0001Z"，其过程就像是 一场"资格考试"。 "我到北京去'答辩'过很多次，还有很多(长安员工)都去'答辩'过。"据邓承浩透露，全国参与L3级测试准 入的企业多达几十家，进入上路通行试点的有9家，而获得产品准入许可的只有长安深蓝和北汽极狐两 家。 出事故后怎么判定？ 与北汽极狐"可实现高速公路和城市快速路单车道内最高时速80公里的自动驾驶功能"不同的是，深蓝汽 车被允许"在交通拥堵环境下的高速公路和城市快速路单车道内以最高时速50公里进行自动驾驶功能"。 关于两者最高时 ...

Group 1: Domestic Chip Replacement - The rise of domestic AI chip manufacturers is marked by significant stock price increases, with companies like Cambrian Technology surpassing major brands like Kweichow Moutai [1] - The market anticipates more AI chip companies to go public, with notable performances from companies like Moer Thread and Muxi, indicating strong investor interest in domestic chip alternatives [1] - The domestic market share for smart computing chips is projected to grow from approximately 20% in 2024 to about 60% by 2029, reflecting a shift towards local production [2] Group 2: AI Edge Computing - The emergence of AI in hardware is expected to redefine traditional devices, with predictions that mobile phones and apps may become obsolete in favor of AI-driven edge devices [3] - The global edge AI market is forecasted to grow from 321.9 billion yuan to 1.22 trillion yuan between 2025 and 2029, with a compound annual growth rate of 40% [4] - The focus of competition is shifting from hardware specifications to AI experience and ecosystem collaboration, indicating a transformation in the value chain [5] Group 3: Quantum Computing Advances - Quantum technology is recognized as a strategic frontier for technological revolution, with significant breakthroughs expected in the coming years [6] - China's advancements in quantum communication and computing are positioning it alongside global leaders, with the "Zu Chongzhi No. 3" quantum computer expected to maintain a competitive edge [7] - The practical application of quantum computing in fields like finance and protein simulation is anticipated to grow, marking a critical step towards commercialization [6] Group 4: Commercial Space Acceleration - The commercial space sector is entering a new phase of rapid evolution, supported by government policies and increased capital investment [8] - The global commercial space market is projected to grow at a compound annual growth rate of 10.5% over the next five years [8] - The demand for satellite launches is expected to surge, with significant increases in the number of satellites being deployed [9] Group 5: Solid-State Battery Development - Solid-state batteries are gaining attention as a transformative technology for electric vehicles, with major manufacturers announcing plans for testing and production [10] - The timeline for mass production is set for 2027, with initial production expected to be in small batches [11] - The industry faces challenges in cost and manufacturing processes, with a consensus that semi-solid batteries will precede full solid-state solutions [10] Group 6: L3 Autonomous Driving - The introduction of L3 autonomous driving is accelerating due to supportive policies and decreasing costs in the supply chain [12] - The commercial application of L3 technology is expected to expand significantly in 2026, with several manufacturers already in the approval process [13] - The transition from assisted to fully automated driving represents a critical milestone for the industry, with ongoing improvements in technology and data accumulation [13] Group 7: Real Estate Debt Restructuring - Major real estate companies like Country Garden and Sunac have successfully completed debt restructuring, indicating a shift in the industry’s approach to financial challenges [14] - The total scale of debt restructuring in 2025 reached approximately 1.2 trillion yuan, significantly alleviating short-term repayment pressures for affected companies [14] - The focus for 2026 will be on balancing risk management and transformation within the real estate sector, with expectations for continued progress in debt resolution [15] Group 8: "15th Five-Year Plan" Initiatives - The "15th Five-Year Plan" emphasizes high-quality development and technological self-reliance as key objectives for the next five years [16] - The plan outlines initiatives to enhance the modern industrial system and promote strategic emerging industries, including quantum technology and renewable energy [17] - Increasing the resident consumption rate is highlighted as a crucial goal, with measures aimed at boosting consumer spending and improving living standards [18]

Core Insights - The transition from L2 to L3 autonomous driving is not merely a technical upgrade but involves comprehensive challenges related to legal responsibilities, costs, and user trust [1][6][11] Group 1: Policy and Regulation - The Ministry of Industry and Information Technology (MIIT) has approved the first two L3 autonomous driving models in China: Changan Deep Blue SL03 and BAIC Blue Valley Arcfox Alpha S Pioneer Edition, set to be tested under specific conditions by the end of 2025 [2][3] - The L3 level allows for conditional automation where the driver can fully disengage from driving tasks, but responsibility for accidents may be shared between the system and the driver [2][3] - New regulations, such as the Beijing Autonomous Driving Vehicle Regulations, have established accident liability rules, requiring manufacturers to bear product liability and maintain insurance of at least 5 million yuan [3] Group 2: Technical Challenges - Transitioning from L2 to L3 involves a significant shift in responsibility, technology architecture, and business logic, necessitating redundant systems to ensure safety [6][7] - The cost of implementing redundancy in systems, such as steering, can increase significantly, with estimates suggesting costs could rise from 1,500-2,000 yuan to 4,000-6,000 yuan per unit [6][7] - The choice between in-house development and third-party suppliers complicates the responsibility chain in the event of an accident, requiring clearer regulations [7] Group 3: User Experience and Trust - Users have reported issues such as "phantom braking" and hesitation during lane changes, highlighting a gap between marketing promises and actual user experiences [5][8] - Many users express a lack of trust in autonomous systems, often feeling uncertain about when to intervene, which can lead to negative experiences and a reluctance to use the technology [8][11] - Education on the capabilities and limitations of autonomous driving systems is lacking, with few manufacturers incorporating training into the sales process [9][10] Group 4: Recommendations for Improvement - Companies must take responsibility for educating users about autonomous driving, while regulatory bodies should promote clear and understandable guidelines [11] - Enhancing human-vehicle interaction through transparent communication of system intentions can help build trust and improve user experiences [11] - The successful integration of L3 autonomous driving into everyday life requires a collective effort from the industry, regulators, and consumers to foster understanding and trust [11]