共探新营销，共创新可能 设计 | 甄 尤美 撰文 | 胡 俊成（ 知行科 技产 品经理 ） 编辑 | 杜咏 芳 Editor's notes 编者按 "2026年的重点，将是高速NOA向L3级别的商业化落地迈进。" 知行科技产品经理胡俊成以此判断锚定了行业下一阶段的核心方向。 这不仅是技术的跃迁，更是责任归属的根本性转变。 相比2024年，高速及城区NOA的平均接管里程跃升，系统可靠性显著提升； 智能驾驶场景覆盖持续扩展，停车场出入口成为新的能力"试金石"； 车辆与人的交互方式也在悄然进化，它甚至能理解"靠边停到白色车后面"这类模糊、自然的语音指令。 更重要的是，车辆不再只是机械地遵守规则，而是开始真正理解场景。面对施工围挡、临时导流区、无标线道路等复杂情境， 越来越多车型展现出类似老司机的灵活应变能力。 正如胡俊成所感慨的那样："它不是呆板的按线行驶，是真有自己的判断。" 这句话，恰是中国智驾从L2迈向高阶可用性的关键 缩影。 他表示："L2的责任主体始终是驾驶员，L3的量产将进一步释放驾驶员，但这并没有将人彻底解放出来，L3在中国市场有可能 知识短暂的过渡，全力实现L4智驾普及。" 从L2到L3，还有哪些 ...

Core Viewpoint - The article emphasizes that smart driving is currently undervalued and is transitioning from a future concept to a core competitive factor in the automotive industry, as the market shifts focus from electrification to smart driving technologies [5][14]. Industry Analysis - Smart driving is at a stage where technological feasibility has been validated, but commercial scale is yet to be fully realized, indicating a ripe opportunity for long-term investors [7]. - The industry is moving from exploratory phases to cost and efficiency optimization, which is a significant signal for accelerated commercialization [8]. - The essence of smart driving lies in platform capabilities rather than mere functional upgrades, highlighting the importance of a comprehensive system that includes hardware, algorithms, and data platforms [10]. Commercialization Path - Revenue sources and realization timelines in the smart driving sector are becoming clearer, with high-level driving transitioning from one-time sales to subscription models, enhancing profit quality [11][12]. - Applications of smart driving technology are already being implemented in various business scenarios, such as ports and logistics, providing a solid revenue foundation [13]. Investment Opportunities - In the Hong Kong stock market, companies with comprehensive smart driving capabilities are limited, with Baidu being a notable example due to its long-term strategic investments and unique data accumulation capabilities [15]. - Companies like Pony.ai and WeRide serve as critical benchmarks for the industry's potential, focusing on complex urban driving scenarios and L4-level automation, which could unlock significant replication potential if successful [16][17]. Strategic Approach - The smart driving theme is better suited for long-term investment strategies rather than short-term trading, with a focus on platform companies that maintain stable cash flows while investing in smart driving [22]. - The article concludes that smart driving represents a gradual but inevitable trend, with real opportunities arising from a deep understanding of the industry and companies before market sentiment fully aligns [23][24].

智通财经APP获悉，中信证券发布研究报告称，预计2026年汽车行业以旧换新政策延续的概率较大，但 Q1行业或仍将面临一段时间的需求透支期。建议投资人聚焦具有全球竞争力的中国企业，全面拥抱产 业新趋势。2026年上半年有望跑赢的投资标的包括：1)出海景气延续、出海盈利弹性大的乘用车和商用 车龙头企业;2)自动驾驶加速渗透带来的头部智驾公司、上游产业链、L4公司的投资机会;3)人形机器人 的产业趋势，将继续为板块提供业绩和估值的双重驱动，建议聚焦特斯拉等人形机器人企业的上游核心 零部件公司。 中信证券主要观点如下： 乘用车总量：以旧换新政策有望延续，2026Q1或是行业最差时间，优先选择出海品种进行长期布局。 根据中汽协数据，2025年1-10月，我国乘用车批发销量为2417万辆，同比+12.8%，新能源乘用车批发销 量为1218万辆，同比+32%，渗透率为50.4%。今年乘用车同比增长超预期，主要受益于以旧换新补贴政 策的延续、海外多个市场出口销量的增长。根据商务部发布的1-11月补贴总量数据，预计2025全年总补 贴申请合计将达1240万份，预计总补贴金额将达1650亿元，对2025年的实际销量增量拉动可能达 ...

Group 1 - The core narrative of the article revolves around the evolution of Chery's autonomous driving strategy, highlighting the rise and fall of Dazhuo Intelligent, which was initially seen as a key player in Chery's self-research ambitions [4][6] - Chery's approach to autonomous driving has shifted from "fully controllable" to "fully self-researched," with Dazhuo Intelligent representing a significant milestone in this transition [5][10] - The partnership with Bosch and WeRide has positioned Chery as a leading player in the domestic autonomous driving sector, despite the absence of Dazhuo Intelligent [5][6] Group 2 - Dazhuo Intelligent was founded with the aim of developing autonomous driving technologies, but faced challenges in establishing a viable business model and securing necessary resources [8][14] - The initial strategy of Dazhuo Intelligent included targeting both low-level integrated machine markets and L4 commercial vehicle markets, but the vast scope led to difficulties in execution [11][12] - Internal conflicts arose regarding the financial responsibilities and operational independence of Dazhuo Intelligent, leading to tensions with Chery's commercial vehicle division [16][28] Group 3 - The leadership of Dazhuo Intelligent underwent changes, with the appointment of CTO Cao Guangzhi, who brought significant technical expertise from Tesla, signaling a renewed focus on self-research [19][21] - Despite initial successes, Dazhuo Intelligent struggled with internal processes and budget constraints imposed by Chery, which hindered its ability to recruit talent and accelerate development [25][27] - The integration of Dazhuo Intelligent into Chery's broader strategy culminated in its eventual dissolution, as Chery sought to streamline its autonomous driving efforts and collaborate more closely with external suppliers [41][43] Group 4 - Chery's decision to merge Dazhuo Intelligent with its other technology divisions reflects a strategic pivot towards leveraging external partnerships while maintaining a focus on core competencies [41][44] - The launch of the "Falcon" autonomous driving system marks a new chapter for Chery, emphasizing collaboration with established suppliers like Horizon and Momenta, thereby enhancing its competitive positioning in the market [35][44] - The article concludes with a recognition of Chery's ability to adapt and evolve its autonomous driving narrative, moving from a self-research focus to a more integrated approach with external partners [44]

Group 1: Core Insights - The report emphasizes that the digital economy will continue to drive new quality productivity in 2026, supported by advancements in AI and technology innovation [2][19][21] - The transition from "technical breakthroughs" to "value release" in the technology sector is expected to create long-term value for the industry [2][19] - The automotive sector is projected to undergo a paradigm shift from "rule-driven" to "data-driven" approaches, particularly in commercial vehicles [2][33] Group 2: Digital Economy Development - The digital economy is recognized as a key force in optimizing the three elements of productivity: labor, labor objects, and labor materials [17][19] - AI will play a crucial role in enhancing productivity through technological innovation, data resource utilization, and the establishment of a modern industrial system [19][21] - The report forecasts that the AI medical sector will grow significantly, with the market size expected to reach 159.8 billion yuan by 2028 [4][24] Group 3: Intelligent Driving - The intelligent driving sector is entering a critical phase with both gradual and leapfrog developments, leading to significant value release in 2025 [26][32] - The penetration rate of L2+ intelligent driving is expected to rise from 8% in 2024 to 15% in 2025, indicating a shift towards more affordable models [37][41] - The report highlights the importance of policy and technology in driving the commercialization of L3 autonomous vehicles [40][44] Group 4: Industrial AI - Industrial AI is set to evolve from "tool-level applications" to comprehensive integration across research, production, and management processes [3][22] - The report outlines that AI will enhance efficiency in manufacturing through adaptive intelligent systems and predictive maintenance [3][22] - The integration of AI in industrial software is expected to improve operational efficiency and drive innovation in manufacturing [22][25] Group 5: Cybersecurity - The cybersecurity industry is transitioning from "passive defense" to "active immunity," with AI-driven models enhancing threat detection and operational automation [3][23] - The report emphasizes the need for a comprehensive security framework that includes AI technology, data security, and ecosystem collaboration [23][24] - AI's role in cybersecurity is projected to significantly improve threat detection accuracy and operational efficiency [3][23] Group 6: Investment Recommendations - The report suggests focusing on sectors such as automotive, industrial AI, cybersecurity, and AI healthcare for investment opportunities during the "14th Five-Year Plan" period [21][24][25] - The automotive sector is highlighted as a core area for investment due to its potential for digital technology integration and ecosystem collaboration [21][22] - The report indicates that the development of domestic AI chips will support the digital economy by overcoming current limitations in computing power [25][26]

Core Viewpoint - The article discusses the journey of Li Auto in developing its autonomous driving technology, highlighting the challenges faced and the strategic decisions made to shift from relying on suppliers to self-research and development. Group 1: Historical Context and Initial Challenges - In 2020, Li Auto sold 32,624 units of the Li ONE, significantly exceeding internal expectations, which were initially set at 3,000 units for the first year [2][6] - Despite the success, the company faced immediate pressure from competitors like NIO and Xpeng, who were launching new products and advanced autonomous driving features [4][6] - The internal celebration of sales success contrasted sharply with the external pressures of market competition and technological gaps [6][7] Group 2: Decision to Pursue In-House Development - The decision to pursue in-house development of autonomous driving technology was driven by the realization of dependency on suppliers and the need for greater control over technology [9][19] - Li Auto's leadership recognized the necessity of self-research to remain competitive, especially after observing advancements made by competitors [22][23] - The initial budget for autonomous driving research was limited, forcing the team to be resourceful and strategic in their approach [9][10] Group 3: Development Process and Key Milestones - The "Fortress Project" was initiated to develop Li Auto's first fully self-researched advanced driver assistance system, with a tight deadline of less than 100 days [27][30] - The team faced significant challenges, including high turnover and the need to recruit quickly to meet project demands [32][30] - The successful delivery of the autonomous driving system before the launch of the 2021 Li ONE marked a significant achievement for the company [34][44] Group 4: Data-Driven Approach and Technological Advancements - The establishment of a data closed-loop system named "Poseidon" was crucial for enhancing the efficiency of the autonomous driving development process [39][40] - The data-driven approach allowed the team to rapidly iterate and improve the autonomous driving features based on real-world data [41][42] - By the end of 2021, Li Auto achieved a delivery volume of 90,491 units, a 177.4% increase year-on-year, largely attributed to the new self-researched driving system [43][44] Group 5: Ongoing Challenges and Future Plans - The company faced ongoing challenges in keeping pace with competitors in the rapidly evolving autonomous driving market, particularly in urban navigation capabilities [51][52] - Li Auto's strategic pivot towards end-to-end development and the initiation of new projects like the "Golden Apple Plan" reflect its commitment to innovation and competitiveness [58][59] - The article concludes with anticipation for future developments in Li Auto's autonomous driving technology, emphasizing the need for continuous adaptation and strategic foresight [60]

Core Viewpoint - The article discusses the challenges and pressures faced by a leading automotive company's self-driving research team as they approach critical deadlines for developing advanced autonomous driving technologies, highlighting the competitive landscape and the importance of effective management in achieving technological advancements [6][8][14]. Group 1: Development Goals and Challenges - The self-driving research team of a leading automotive company has set ambitious internal goals to develop a no-map urban Navigation on Autopilot (NOA) by September 30 and an end-to-end system by December 30 [6]. - The company is currently lagging behind new entrants and leading autonomous driving firms by at least a year in terms of research and development progress [8]. - The pressure is high for the smart driving leaders, as failure to meet these deadlines could lead to accountability issues and organizational turmoil [7][8]. Group 2: Investment and Talent Acquisition - The company has significantly increased its investment in autonomous driving technology, surpassing that of some new entrants, and is willing to offer competitive salaries to attract top talent [9]. - Unlike some new entrants that offer compensation packages tied to stock performance, this leading company provides more cash to avoid fluctuations in employee compensation due to stock price volatility [9]. Group 3: Technical and Management Issues - Despite substantial investments, the company faces challenges in the end-to-end development process, particularly in data management, which is crucial for training models effectively [10]. - Traditional automotive companies often struggle with a lack of algorithmic expertise among their leadership, which affects their ability to manage and innovate in autonomous driving technology [13]. - The management approach in traditional firms tends to focus on coding output rather than the underlying algorithmic thought processes, which contributes to lower technical output compared to new entrants [14]. Group 4: Future Outlook and User Experience - The company plans to widely implement high-level urban NOA in numerous models next year, contingent on the success of its self-developed end-to-end system [15]. - The upcoming year is expected to be pivotal for end-to-end systems, as both new entrants and leading firms are achieving performance levels that meet consumer expectations [15]. - The emphasis will shift towards ensuring that the technology not only functions but also provides a satisfactory user experience, as performance differences among various end-to-end systems can significantly impact consumer perception [16].

Core Insights - The article discusses the monthly OTA (Over-The-Air) monitoring report released by the China Automobile Circulation Association and Guangzhou Weierbo Information Technology Co., Ltd, focusing on the trends and updates in the automotive industry regarding OTA upgrades [1]. Industry Overview - In June 2025, the industry updated a total of 463 features, a decrease from 498 in the previous month. The "assisted driving" module regained the top position in upgrade share, with urban NOA (Navigation on Autopilot) features accounting for approximately 30% of the upgrades [4]. - New force brands updated a total of 133 features in June 2025, down from 200 in the previous month. The competition in the intelligent driving sector reignited among various new force brands, while upgrades in voice assistants, navigation, and ecosystem applications were minimal [6]. - Domestic brands updated 269 features in June 2025, with 13 brands pushing OTA upgrades. The focus remained on enhancing intelligent cockpit experiences and ecosystem refinement, while the competition in assisted driving gradually warmed up [8]. - Joint venture and luxury brands updated 61 features in June 2025, a significant increase from 9 in the previous month. Notably, Nissan and Toyota launched their first OTA upgrades for locally developed new energy models [10]. OTA Iteration Speed - The report indicates a notable increase in the speed of OTA iterations across various brands, reflecting a growing emphasis on enhancing vehicle functionalities and user experiences [12]. OTA Operational Activities - Nissan held a significant OTA upgrade event for the N7 model on June 30, 2025, promoting the new features through various channels, including a live-streamed launch event [20][26]. - Post-OTA push, Nissan initiated long-term operational activities to encourage user engagement, including video contests and experience-sharing topics, focusing on automotive media platforms [27][31]. Upcoming OTA Upgrades - Several brands have scheduled OTA upgrades for various models in the upcoming months, including features like full-scene navigation and advanced driver assistance systems [30][32]. User Feedback - User feedback highlighted both satisfaction and areas for improvement regarding the new features, with specific mentions of the intelligent driving indicator and the overall experience of the upgraded functionalities [34][36][39][49].

Group 1 - The development of urban NOA (Navigation on Autopilot) is expected to reach a penetration rate of 15%, while highway NOA is projected to exceed 60% [4][5] - The vehicle camera market is experiencing simultaneous growth in both quantity and price, with accelerated domestic substitution [5][6] - Domestic manufacturers are emerging and restructuring the market landscape due to intensified competition within the industry [6] Group 2 - High temperatures are driving a new peak in electricity load, enhancing the value of flexible resources like thermal power [9] - The second quarter performance of thermal and hydropower sectors is anticipated to exceed expectations [10] - The energy structure transformation, coupled with deepening electricity reforms, is presenting clear opportunities for transition [11]

Core Insights - Intelligent assisted driving has become a focal point in the automotive industry, with a significant push towards "equal rights" in technology access and safety standards [1][3][5] - The recent "Xiaomi incident" has raised safety concerns, prompting the introduction of mandatory national standards for L2 level assisted driving systems [1][5] - The rapid increase in the penetration rate of urban NOA (Navigation on Autopilot) reflects a shift in market dynamics, with prices for such technologies decreasing significantly [2][3] Industry Trends - The penetration rate of urban NOA in vehicles priced between 200,000 to 250,000 yuan rose from 2.1% in January 2024 to 24.7% by October 2024, driven by decreasing prices [2] - As of December 2023, vehicles equipped with urban NOA are increasingly found in the 200,000 to 300,000 yuan price range, while high-speed NOA is penetrating the 150,000 to 200,000 yuan segment [2] - The industry anticipates that 2025 will be a pivotal year for urban NOA, with expectations for it to enter the mainstream market segment priced between 150,000 to 200,000 yuan [2] Safety and Technology Concerns - There is a growing consensus that achieving "equal rights" in intelligent driving must prioritize safety, with significant disparities in safety capabilities among vehicles in the same price range [3][5] - The current configuration differences in vehicles at the same price point can lead to substantial safety performance variations, with some models having up to six times the computing power and eight more sensors than others [5] - The push for widespread adoption of advanced driving technologies must not compromise safety, as highlighted by industry experts [4][5] Market Dynamics - The competition in the intelligent driving chip sector is intensifying, with established players like NVIDIA dominating the market, making it challenging for new entrants [8][9] - The industry is witnessing a shift where intelligent driving chip manufacturers and solution providers are becoming central players, potentially overshadowing traditional Tier 1 suppliers [7][8] - The trend towards "equal rights" in intelligent driving is expected to lead to standardization, which will benefit chip manufacturers by increasing shipment volumes and enhancing cost competitiveness [8][9] Future Outlook - Industry leaders predict that within 2 to 3 years, intelligent assisted driving features will become standard in vehicles priced above 100,000 yuan, with aspirations to extend this to lower-priced models [7] - The automotive industry is expected to see a consolidation of suppliers, with a few strong players emerging as leaders while maintaining a diverse market landscape [9] - The challenge for automakers will be to differentiate their brands in a market increasingly focused on standardized intelligent driving technologies [9]