如果要用一句话总结2025年的汽车智能化，那大概是： 技术更聪明了，价格腰斩了，宣传更克制了，智能驾驶从城市走向更多元场景。 年初的时候，谁也没想到，这一年会成为汽车智能化的分水岭。开年两个月，比亚迪就把智驾塞进7万块小车，喊出"智驾平权"。几乎同时，DeepSeek、 华为盘古等大模型纷纷上车，座舱从语音控制升级为主动理解。 但技术狂奔很快遭遇现实拷问，小米SU7事故将整个行业拉回现实，安全成为更重要的关键词。 于是，2025年智驾圈就这样在狂奔与刹车之间呈现出前所未有的广度。 DeepSeek等AI大模型上车热潮 2025年，DeepSeek、华为盘古、阿里通义等通用大模型密集登车，车企纷纷推出具备语义理解、多轮对话、场景预判能力的新一代智能座舱。座舱交互 从指令响应迈向主动服务，用户一句模糊的"我有点累"，就能触发座椅按摩、氛围灯调节和导航就近推荐休息区。但热潮之下也暴露短板：部分车型的大 模型依赖云端算力，在弱网或离线状态下功能大幅缩水。大模型上车，真正考验的不是参数规模，而是端云协同的稳定性与本地化推理能力。 小米SU7事故，三条生命，换来史上最严L2+智驾新规 2025年4月，一辆开启NOA的小米 ...

AI给智驾的赋能触及瓶颈了？ "明星高管"苏菁再次"大胆开麦"引发圈内热议。 "大家最近都很嗨，一段式（端到端）搞定了，各种乱七八糟的概念都跑出来了，智驾是不是会进入一 个大发展时代？"近日，在2025地平线技术生态大会，地平线副总裁兼首席架构师苏箐表示："我 要'浇'点冷水。" 他认为，这一代深度学习技术可能碰到天花板了，所以很大概率在未来三年内，智驾的发展是在现有的 系统上做极致优化，而不是理论内核重构，所以"大家别太嗨，又进入苦日子的阶段了"。 公开资料显示，苏箐曾担任华为车BU智能驾驶产品部部长，负责华为自动驾驶系统方案。在华为车BU 时，苏菁就因为"敢说"在智驾圈广为人知，曾发表"基础是计算机，车是计算机控制的外设"的观点，并 锐评特斯拉智驾事故"讲难听点就是'杀人'"。 在此次地平线技术生态大会上，苏菁回顾了过去几年其在智驾行业的历程，这也映射了整个智驾行业近 年来的发展。2022年他准备加入地平线时，心态是"不想再做自动驾驶了"，原因一是太痛苦，二是看不 到希望，"那个时代的自动驾驶看似不错，但与真正人类司机相比差距极大。" 当时的智驾技术范式主要是规则驱动。分水岭出现在2024年初特斯拉FSD ...

在苏箐看来，这一阶段的核心命题，是将现有技术的潜力发挥到极致，比如地平线将持续提升芯片算力 与模型容量，以统一范式推进L2到L4的融合，让城市L2从20万级车型下探至10万级市场，让准L4系统 以平民化价格走进大众。同时，强化工程与组织能力，应对海量长尾场景的打磨，这才是穿越周期的关 键。 "自动驾驶的终极目标，是造出能替代人类司机的机器。这场长跑，在范式革命之后，考验的是行业沉 下心来做'精活'的耐力。在未来几年内，能够把L4级别的车，以平民化的价格送到用户手上。这才是我 们所有人辛苦了这20年做这一行的意义所在。" （文章来源：中国经营报） "未来三年，自动驾驶行业将告别范式迭代的狂飙，进入极致优化的'苦日子'。" 12月9日，在"2025地平线技术生态大会"上，作为深耕自动驾驶20年的老兵，一向"反共识"的地平线副 总裁&首席架构师苏箐分享了对自动驾驶未来趋势的判断。 值得一提的是，对于当下，苏箐则给出了冷静的判断："行业需要清醒。当前深度学习已显露天花板迹 象，AGI基础理论暂无突破信号，下一轮内核重构至少还需5—20年的技术沉淀。未来三年，自动驾驶 行业将告别范式迭代的狂飙，进入极致优化的'苦日子' ...

Macro and Strategy - The report discusses the ongoing expansion and diversification of public REITs in China, highlighting the inclusion of various asset types and industries, with a projected market size increase of 2.3 to 3.8 trillion yuan, indicating a potential 10-16 times expansion compared to the current scale [7][8][10] - The average dividend yield of public REITs from 2022 to 2025 is 5.73%, which is higher than the average yield of the CSI Dividend Index at 5.52%, showcasing their attractiveness as a stable income asset [8][9] - Public REITs are characterized by a dual return structure comprising dividend income and asset appreciation, with a significant portion of returns coming from dividends over longer investment horizons [9][10] Industry and Company - The Chinese duty-free industry is entering a new cycle, with Hainan's duty-free sales experiencing a compound annual growth rate (CAGR) of 39% from 2011 to 2019, but facing a decline of 37% from peak sales due to various market pressures [17][18] - Recent data indicates a recovery in Hainan's duty-free sales, with year-on-year growth of 3%, 13%, and 27% from September to November 2025, suggesting a positive trend in high-end consumption [18][19] - The report emphasizes the importance of policy support and market dynamics in shaping the future of the duty-free sector, with expectations for continued growth driven by improved consumer confidence and strategic policy enhancements [19][20][21] Automotive Industry - The report highlights the rapid advancements in smart driving technology, with companies like Tesla and Huawei leading the way in achieving Level 4 automation through innovative algorithms and architectures [24][25] - The penetration rate of smart driving technologies is expected to see significant growth, with projections indicating an increase from 11.3% to 26.3% for highway navigation assistance (NOA) by 2025 [25] - The global market for robotaxi services is projected to reach nearly 10 trillion yuan, with companies like Waymo and Apollo at the forefront of commercialization efforts [25][26] Non-Banking Sector - The report outlines the importance of the second pillar of the pension system in China, focusing on the development of enterprise and occupational pensions to address the challenges of an aging population [26][27] - The occupational pension system has achieved full coverage, while enterprise pensions are expanding from state-owned to private enterprises, indicating a shift towards a more diversified pension landscape [27][28] - The investment strategy for pension funds is evolving towards a "barbell" approach, balancing stable income-generating assets with growth-oriented investments in technology and manufacturing sectors [28]

Macro and Strategy - The report discusses the ongoing expansion and diversification of public REITs in China, highlighting the inclusion of various asset types and industries, with a projected market size of 2.3 to 3.8 trillion yuan, indicating a potential 10-16 times expansion from current levels [7][8][10] - The average dividend yield of public REITs from 2022 to 2025 is 5.73%, surpassing the average yield of the CSI Dividend Index at 5.52%, showcasing their attractiveness as a stable income asset [8][9] - Public REITs are characterized by a dual return structure comprising dividend income and asset appreciation, with a notable annualized return of 23.66% over the past year [9][10] Industry and Company - The Chinese duty-free industry is entering a new cycle, with Hainan's duty-free sales showing signs of recovery, driven by policy support and improving consumer confidence, with sales growth of 3%, 13%, and 27% from September to November 2025 [17][18] - The report emphasizes the importance of policy optimization in the duty-free sector, with recent expansions in both offshore and onshore duty-free policies, enhancing consumer access and convenience [18][19] - The report identifies key players in the duty-free market, such as China Duty Free Group, which holds a 78% market share, and highlights the strategic importance of airport channels for future growth [20][21] Automotive Industry - The report outlines the advancements in smart driving technology, with companies like Tesla and Huawei leading the way in achieving Level 4 automation through end-to-end algorithms [24][25] - The penetration rate of smart driving is expected to see significant growth, with projections indicating an increase from 11.3% to 26.3% for highway NOA and from 6.1% to 10.9% for urban NOA by 2025 [25] - The global market for Robotaxi is projected to reach nearly 10 trillion yuan, with companies like Waymo and Apollo at the forefront of commercialization efforts [25][26] Non-Banking Industry - The report highlights the importance of the second pillar of the pension system in China, focusing on enterprise and occupational pensions, which are expected to grow at an annualized rate of 8%, outpacing nominal GDP growth [26][27] - The investment behavior of pension funds is shifting towards a "barbell" strategy, balancing stable cash flow assets with high-growth sectors, indicating a significant increase in equity allocations [27][28]

Core Viewpoint - The company, Haomo Zhixing, is facing significant operational challenges leading to layoffs and a halt in operations, attributed to internal management issues and fierce industry competition [1][10]. Group 1: Company Background and Financials - Haomo Zhixing was founded in November 2019 and achieved a valuation exceeding $1 billion by the end of 2021 after raising nearly 1 billion yuan in Series A funding [2]. - The company has raised over 2 billion yuan in total funding, supported by major investors including Meituan and Hillhouse Capital [2]. - Despite ambitious goals, such as equipping over 1 million vehicles with its driving assistance system within three years, the actual deployment has fallen short, with only 100,000 units expected by the end of 2024 [5]. Group 2: Product and Technology - The company aimed to develop products across passenger vehicles, logistics vehicles, and smart hardware, with its main product being the HPilot system, which covers L2 to L4 technology [3]. - The HPilot 3.0 system features advanced capabilities such as automatic lane changing and complex road navigation, utilizing a combination of visual and lidar technology [3]. Group 3: Market Position and Competition - Haomo Zhixing's customer base has been limited, primarily relying on a single major client, which has hindered its market position compared to competitors who have diversified client portfolios [8]. - The company has struggled to compete on pricing and technology, with its HP570 solution priced at 8,000 yuan, which is higher than similar offerings from competitors [8]. Group 4: Operational Challenges - The company has faced significant delays in project deliveries, impacting its credibility and operational efficiency, with multiple projects experiencing postponed timelines [7]. - Internal management issues and a lack of focus on commercialization have been cited as critical factors contributing to the company's decline [10]. Group 5: Industry Context - The overall investment climate for autonomous driving companies has cooled, with a significant drop in financing events and amounts from 2022 to 2023, indicating a cautious approach from investors [9]. - The failure of Haomo Zhixing is part of a broader trend in the industry, with several other autonomous driving companies also facing bankruptcy or restructuring [10].

Core Insights - The company, Haomo Zhixing, is facing significant operational challenges leading to a sudden halt in operations starting November 24, 2023, following a series of layoffs and management departures [1][2][12] - The decline of Haomo Zhixing is attributed to multiple factors, including internal management issues and fierce competition in the autonomous driving industry [1][13] Group 1: Company Background and Financials - Haomo Zhixing was founded in November 2019 and achieved a valuation exceeding $1 billion by the end of 2021 after raising nearly 1 billion yuan in Series A funding [2][4] - The company has raised over 2 billion yuan in total funding, supported by major investors from the internet and automotive sectors [4][12] - The initial goal was to equip over 1 million passenger vehicles with its HPilot system within three years, aiming for an 8%-10% market share [7][12] Group 2: Product Development and Market Position - Haomo Zhixing's main products include the HPilot system, which covers levels L2 to L4 of autonomous driving technology, and the small logistics delivery vehicle series [5][11] - Despite ambitious targets, the actual deployment of HPilot was only 100,000 units by the end of 2024, far below the initial goal [7][10] - The company has struggled with project delays and low delivery efficiency, impacting its ability to meet market demands [10][11] Group 3: Competitive Landscape - The autonomous driving sector is highly competitive, with companies like Tesla and others transitioning to end-to-end solutions, leaving Haomo Zhixing lagging behind [9][10] - Haomo Zhixing's pricing strategy has been criticized, as its offerings are perceived as more expensive compared to competitors, which has hindered customer acquisition [11][12] - The company has been unable to expand its customer base beyond a few key clients, limiting its revenue potential [10][12] Group 4: Industry Trends and Challenges - The autonomous driving industry has seen a significant reduction in financing, with a drop in the number of funding events and total investment amounts from 2022 to 2023 [12] - Many autonomous driving companies have faced bankruptcy or restructuring, indicating a challenging environment for startups like Haomo Zhixing [13] - The overall market sentiment has shifted towards investing in companies with strong technological barriers and commercialization capabilities, further complicating Haomo Zhixing's situation [12][13]

Core Insights - The automotive and intelligent driving industry is experiencing rapid technological iterations, leading to new terminologies and concepts that challenge user understanding and acceptance [1] - The transition from rule-based systems to end-to-end and world model architectures is reshaping the landscape of autonomous driving, with significant implications for company strategies and personnel [2][4][10] Industry Trends - The shift towards end-to-end systems, exemplified by Tesla's FSD V12, has prompted other companies like Huawei, Xpeng, and NIO to explore similar approaches, indicating a trend towards more integrated solutions [2][4] - The industry recognizes the upcoming critical period for the implementation of advanced driver assistance technologies, particularly from Q4 2023 to mid-2024, as companies race to adopt and refine these technologies [1] Technical Developments - Current autonomous driving systems, whether rule-based or end-to-end, primarily rely on mimicking human driving through extensive data collection and learning, which presents challenges in efficiency and adaptability [4][5] - The introduction of VLA (vision-language-action) models aims to enhance understanding of the physical world, moving beyond mere imitation to a more human-like comprehension of driving scenarios [7][11] Company Strategies - Companies like Xpeng and Li Auto are pivoting towards VLA models, with Xpeng's second-generation VLA eliminating the language translation step to improve efficiency and data utilization [8][11] - The restructuring of R&D departments within companies such as Li Auto and NIO reflects a strategic shift towards prioritizing VLA and world model approaches, indicating a broader industry trend towards adapting organizational structures to new technological demands [15][17] Competitive Landscape - The competition between self-developed autonomous driving technologies and third-party solutions is intensifying, with companies increasingly opting for partnerships with specialized suppliers to enhance their capabilities [18][21] - The financial burden of self-development is prompting companies to reconsider their strategies, as seen in Xpeng's significant investment in computing resources and the need for profitability in Q4 2023 [19][22]

Core Insights - The automotive and smart driving industry is experiencing rapid technological iterations, leading to new terminologies and concepts that challenge user understanding and acceptance [1] - The transition from rule-based systems to end-to-end and world model architectures is reshaping the industry, with significant implications for company strategies and personnel [2][6] Group 1: Technological Evolution - The shift from rule-based to end-to-end systems has highlighted the limitations of modular approaches, particularly in terms of latency and information loss [2] - Tesla's introduction of the end-to-end FSD V12 has sparked interest among other companies like Huawei, Xpeng, and NIO, who are also developing similar solutions [2][5] - The industry is moving towards VLA (vision-language-action) models, which aim to better understand the physical world and improve driving actions [8][12] Group 2: Challenges in Implementation - Current systems, whether rule-based or end-to-end, rely heavily on passive learning from vast amounts of driving data, which limits their ability to adapt to new scenarios [5][6] - The VLA model faces challenges such as multi-modal feature alignment and the inherent limitations of language models in processing complex real-world situations [11][15] - Companies like Ideal Auto and Xpeng are exploring innovative VLA approaches to enhance their systems' capabilities and efficiency [8][12] Group 3: Organizational Adjustments - The transition to new technological routes has led to significant organizational restructuring within companies like Xpeng, Ideal Auto, and NIO, reflecting a shift in focus towards foundational models [13][14] - Xpeng's leadership changes indicate a strategic pivot from traditional VLA to innovative VLA, emphasizing the need for a robust foundational model [14] - NIO and Ideal Auto have also undergone multiple organizational adjustments to align their resources with the evolving technological landscape [15][17] Group 4: Competitive Landscape - The trend of self-research in autonomous driving technology is shifting towards partnerships with specialized suppliers, as seen with companies like Chery and Great Wall [18][19] - Suppliers are gaining an edge in flexibility and rapid iteration capabilities compared to traditional automakers, which face constraints in their development processes [21] - The competition is intensifying, with suppliers expected to play a more dominant role in the market as they advance their solutions [18][22]

Core Viewpoint - The successful IPOs of two autonomous driving companies, Pony.ai and WeRide, in Hong Kong mark a significant milestone for Guangzhou, showcasing the city's long-term investment in the autonomous driving sector and the potential for growth in this industry [4][20]. Group 1: Pony.ai - Pony.ai raised approximately HKD 67.1 billion, setting a new record for IPO fundraising by an autonomous driving company in Hong Kong [5]. - The cornerstone investors for Pony.ai include five firms, collectively investing USD 120 million (approximately HKD 932 million), which accounts for 13.9% of the total shares offered [6]. - Notable investors include Ghisallo Fund, which subscribed to 279,460 shares, representing 5.79% of the total shares offered [6]. - Prior to its IPO, Pony.ai had completed multiple funding rounds, raising over USD 1.3 billion [8]. - Major investors include Toyota, which invested USD 400 million in 2020, and Sequoia Capital, which invested a total of USD 36.5 million [9]. - After the IPO, Toyota holds a 9.94% stake, Sequoia 5.29%, and Wuyuan Capital 3.65%, with significant unrealized gains [10][12]. Group 2: WeRide - WeRide raised approximately HKD 23.9 billion in its IPO and did not have cornerstone investors but secured strategic investments from companies like Uber and Nvidia [13]. - The founders of WeRide hold over 72.1% of the voting rights, with significant stakes held by other investors such as Yutong and Qiming Venture Partners [14][15]. - Uber has made a substantial investment in WeRide, adding USD 100 million in equity earlier this year [13]. Group 3: Industry Context - The rise of autonomous driving in Guangzhou can be traced back to 2014 when city leaders recognized the potential of AI and began attracting startups in this field [18]. - The industry is divided into two paths: the "incremental" approach, exemplified by Tesla, and the "leapfrog" approach, represented by Pony.ai and WeRide, which aims for full autonomy [19]. - The "leapfrog" approach offers a clear business model and the potential for significant market share in a rapidly growing industry, with both companies positioned to capitalize on this transformation [20].