曾经依赖高精地图的智能驾驶系统，如今正在全面『去地图化』。无图智驾让车辆像人一样，靠纯感知实时决策。本文将深度解析无图智驾的技术原理、 主流方案对比、法规责任划分与市场未来预测，带你看清自动驾驶从辅助到有条件自动的本质跨越。 01 从『看地图』到『看世界』的本质变革 无图智驾的核心突破在于摆脱了对高精地图的强依赖，让车辆真正依靠传感器实时感知环境并做出决策。传统依赖高精地图的智能驾驶系统如同『看地图 走路』，需要预先绘制好详细的路线图，一旦道路发生变化或地图更新不及时，系统就可能失效。而无图智驾则像『人眼看路』，通过摄像头、激光雷 达、毫米波雷达等传感器实时捕捉周围信息，结合端到端AI模型直接生成驾驶指令。 这种技术路线的转变源于高精地图的三大局限性：覆盖慢、成本高、更新滞后。 比如，当一条道路施工或标线修改，高精地图需要经过采集、绘制、审核、推送等多个环节，周期通常以月为单位。而无图方案完全靠实时感知，道路怎 么变，车辆就怎么识别，无需等待地图包OTA。对车主来说，不用再记『哪些路段能用、哪些路段不能用』，上车设好目的地，该用就用，这才是智能科 技该有的样子。 从技术架构来看，无图智驾系统通常采用多传感器融 ...

不得不说，2026春节档的《飞驰人生3》确实燃。 全新的沐尘100赛道，车手的血性与执念——每一帧都像在观众心上踩油门。（以下内容含轻微剧透，介意的朋友可以先收藏，看完电影再来对线。） est (Call School) 1 1 2 1 range and a te 19 2017 . Nation the company of the ca 6 7 2 in the production t 1 e e a ph e the down 80 888 - 1988 are state es UNIVERSETTI NEW YOUR 图源：微博@电影飞驰人生3 不过作为一个汽车行业的观察者，电车通更在意影片中的一条暗线：人类车手 vs AI赛车系统。 这可能是整部电影最具现实意义的其中一部分。 电影中，「天梯」车队所采用的ss8芯片以及AI赛车系统，堪称「赛道外挂」。 它能在大雾弥漫、能见度几乎为零的险境中，精准感知每一寸弯道；无需领航员，车辆自己就能感知环境、预判路况。不仅如此，系统还能实时调校动力输 出与底盘参数。 正如片中角色「百强」所说，「比赛结果，可以在会议室里谈嘛！」 这句话不仅暴露了竞技异化为权力 ...

Investment Highlights - The main contradiction in C-end automotive intelligence has shifted from coverage to experience optimization in 2026. Major intelligent driving manufacturers and solution providers have achieved urban NOA (Navigation on Autopilot) experiences in complex scenarios such as roundabouts and U-turns, and have improved advanced functions like parking and ETC passage. The primary optimization direction moving forward will be the handling capability of Corner Cases to enhance the driving experience for passengers and safety operators [2][7]. Road Testing Overview - This report conducted both large-sample concentrated road tests and small-sample in-depth road tests. It qualitatively and quantitatively evaluated the intelligent driving experiences of six manufacturers/solution providers: Horizon, Li Auto, Qianli Zhijia, Qingzhou Zhihang, WeRide, and Xpeng, based on dimensions such as scenario implementation, takeover frequency, and comfort. Due to subjective scales, actual road conditions, and the trust level of safety operators in intelligent driving, the report does not rank the intelligent capabilities of specific manufacturers/solution providers [3][7]. Performance Improvement - Compared to 2025, all major manufacturers have improved their intelligent driving capabilities in Q1 2026, while third-party suppliers have also demonstrated excellent implementation results. The self-research camp of manufacturers is expected to continue iterating. Li Auto and Xpeng have developed mature self-research solutions that cover full-scene NOA on public roads and some internal roads, showing improvements in static and dynamic lateral perception, scenario understanding, and Corner Case handling. Li Auto's OTA 8.2 iteration has made AD Max smoother, reducing driving jolts and stabilizing responses. Xpeng's XOS 5.8.5 version can achieve three-point U-turns and autonomously learn from parking to parking, with VLA 2.0 expected to launch after the Spring Festival, enhancing reasoning efficiency and response speed [4][7]. Third-Party Supplier Performance - Third-party intelligent driving suppliers have shown impressive results. Their solutions have been launched to cover all external public roads seamlessly, with roundabouts and U-turns executed without interruptions. Horizon's HSD demonstrated smooth performance, achieving a full hour of deep road testing with zero takeovers (with one intervention for acceleration). Qianli Zhijia's G-ASD solution on the Zeekr model significantly reduced takeover rates. Qingzhou Zhihang utilized a single J6M chip (with 128 TOPS computing power) to achieve mass production of urban NOA, which is the lowest computing power among urban NOA models. WeRide's solution won the championship at the China Intelligent Driving Competition in Taizhou, showcasing excellent lane selection logic with no safety takeovers [4][7].

Investment Rating - The industry investment rating is "Overweight," indicating an expected outperformance of the industry index relative to the benchmark by more than 5% over the next six months [71]. Core Insights - The main contradiction in C-end automotive intelligence has shifted from coverage to experience optimization, with major intelligent driving manufacturers achieving urban NOA experiences in complex scenarios such as roundabouts and U-turns, and enhancing advanced features like parking and ETC passage. Future optimization will focus on handling corner cases to improve the driving experience for passengers and safety personnel [2][66]. - Compared to 2025, all major manufacturers have improved their intelligent driving capabilities in Q1 2026, with third-party suppliers also showing excellent implementation results [2][66]. - The report evaluates the intelligent driving experiences of six manufacturers, including Horizon, Ideal, Qianli Zhijia, Lightyear, WeRide, and Xiaopeng, through both large-sample and small-sample road tests, focusing on scene implementation, takeover frequency, and comfort [2][66]. Summary by Sections Road Test Overview - The report includes two types of road tests: large-sample centralized road tests and small-sample deep road tests, each with distinct advantages and limitations [6][7]. - The large-sample test involved over 30 participants and standardized routes, while the small-sample test used consistent evaluators and longer durations for a more in-depth experience [7][8]. Intelligent Driving Models Tested - The models tested in February 2026 included: - Xingtou ET5 - Ideal i6 - Geely 9X - Ideal L6 Pro - Xingtou Star Era ES - Xiaopeng X9 [8][10]. Performance Metrics - Key performance metrics evaluated include overall evaluation, takeover frequency, stability performance, and efficiency in various driving scenarios such as roundabouts and U-turns [23][41]. - The report provides detailed performance scores for each model, indicating their ability to handle complex driving situations and overall driving smoothness [41][46][50][56][61][62]. Manufacturer Insights - Horizon's HSD achieved an average score of 4.55 with a total takeover frequency of 0.16, demonstrating excellent handling of road test scenarios [41]. - Ideal's AD Max scored 3.51 with an average takeover frequency of 1.86, showcasing strong performance in stability and handling [46]. - Qianli's G-ASD scored 3.05 with a takeover frequency of 2.60, indicating good performance in complex scenarios [50]. - Lightyear's AD Pro scored 2.89 with a takeover frequency of 2.75, performing well in roundabout scenarios [56]. - WeRide's E2E scored 3.84 with a low takeover frequency of 0.70, indicating strong performance in efficiency [61]. - Xiaopeng's XNGP scored 3.64 with a takeover frequency of 1.20, showing good stability and efficiency [62].

高阶辅助驾驶收费并非新鲜事，但当特斯拉CEO马斯克亲自下场官宣时，依然在全球车圈投下了一颗重磅炸弹。 1月14日，马斯克在社交平台发布信息称：2026年2月14日起，特斯拉全自动驾驶（FSD）将彻底废除一次性买断方案，全面转向订阅制，博主@Sawyer Merritt在评论区下方留言，该服务的月费为99美元，年费为999美元。 截图：X@Elon Musk 消息一出，海内外网友纷纷开启「嘲讽模式」。不少网友揶揄道：「今天取消买断，明天是不是方向盘和刹车也要按次收费？」也有人表达了对未来涨价的 担忧：「现在99美元，明年会不会变199？订阅制就是温水煮青蛙。」 当然，也有理性的声音认为，相比一次性掏出8000美元买断的巨款，每月99美元的门槛确实更低，对于偶尔需要的用户更友好。 实际上，汽车圈的订阅模式并不少见，此前奔驰和宝马就因为付费订阅服务项目站到了舆论中心，后轮转向、座椅加热、方向盘加热等配置均需要车主订 阅。 但作为行业龙头，特斯拉此举究竟意在何为？难道不担心此举会带来负面影响吗？而且，面对特斯拉的激进变革，长期以买断制为智驾主流收费模式的国产 品牌，是会坚守阵地，还是迫于压力，悄悄跟进这一「收割模式」 ...

Core Viewpoint - Tesla's decision to eliminate the one-time purchase option for its Full Self-Driving (FSD) software is driven by the need to achieve a target of 10 million active FSD subscriptions, which is part of Elon Musk's ambitious compensation plan [3][10]. Group 1: Tesla's Strategy - The shift from a one-time purchase model to a subscription model aims to convert existing customers into active subscribers, thereby generating continuous revenue and valuable data [6][10]. - The subscription model is seen as a lucrative business opportunity, with potential revenue exceeding 14,500 USD per vehicle over its lifetime compared to the one-time purchase price of 8,000 USD [10]. - Tesla's move is also a response to declining profits, as evidenced by a 37% drop in net profit year-over-year, despite a 6% increase in automotive revenue [10][11]. Group 2: Market Competition - Tesla faces increasing competition from domestic brands like BYD, which has surpassed Tesla in annual sales of electric vehicles, highlighting a shift in market dynamics [12]. - Domestic brands predominantly use a one-time purchase model for advanced driving systems, aligning with local consumer preferences for upfront payments rather than subscriptions [19][20]. - The competitive landscape is characterized by aggressive pricing strategies from domestic manufacturers, who often offer advanced driving features at significantly lower prices or even for free [16][20]. Group 3: Consumer Behavior - Chinese consumers generally prefer a one-time payment model for advanced driving features, with a significant portion unwilling to pay for subscriptions [19]. - The perception of subscription services as luxury items contrasts with the domestic approach of making advanced driving features standard, reflecting a broader trend towards "driving equality" in the market [26].

Core Insights - The article highlights the transition of China's intelligent driving industry from concept to practical application, with Chery's commitment to its intelligent driving strategy serving as a milestone [1][3]. Industry Overview - By 2025, the Chinese intelligent driving industry is expected to shift from "parameter competition" to "real-world validation," with consumer expectations evolving from "availability" to "usability" and "reliability" [3]. - The current stage of the industry is characterized by both technological breakthroughs and challenges in implementation [4]. Chery's Commitment - Chery's chairman publicly committed to equipping all models with the Falcon intelligent driving assistance system within the year, a move that sparked industry discussions due to the previous trend of high-level intelligent driving features being limited to premium models [3][6]. - As of the end of the year, Chery successfully integrated the Falcon system across all models, demonstrating its technical capabilities through real-world testing in complex driving conditions [3][6]. Challenges in Intelligent Driving - Many automakers face issues such as "feature reduction," "delayed functionality," and limitations to high-end models when delivering intelligent driving features [5]. - Current intelligent driving systems exhibit significantly higher error rates on unstructured roads compared to structured ones, with failure rates being 3-5 times higher [5]. Technical Foundation of Falcon Intelligent Driving - The Falcon system's success is attributed to a collaborative foundation of data, algorithms, and hardware, creating a "data loop - algorithm breakthrough - hardware redundancy" structure [7]. - Chery's Tianqiong Intelligent Computing Center has accumulated over 24 billion kilometers of driving assistance data, enhancing the system's adaptability across various road conditions [7][10]. Algorithm and Hardware Integration - The Falcon system utilizes the Momenta R6 reinforcement learning model, which allows for rapid decision-making in unforeseen scenarios, enhancing its performance in complex environments [10][11]. - The hardware setup includes a combination of sensors, ensuring reliable perception in challenging conditions, while the system's computational power is optimized for efficient data processing [12][14]. Long-term Strategy and Collaboration - Chery's approach to intelligent driving is rooted in a long-term commitment to technology development, having invested in intelligent technology since 2010 [17][19]. - The company employs a collaborative ecosystem model, partnering with various tech firms to enhance its capabilities while maintaining core technology independence [19]. Future Outlook - Chery aims to achieve end-to-end integration of its intelligent driving system by 2026, with ongoing updates to enhance functionality [21]. - The intelligent driving industry is moving towards a phase of "refined cultivation," focusing on real-world validation and user-centric solutions [22].

Core Viewpoint - The article discusses the increasing collaboration between traditional car manufacturers and Huawei, highlighting the challenges and strategies in the automotive industry's shift towards smart driving technology [3][8][14]. Group 1: Industry Dynamics - In 2025, the Chinese automotive market will be highly competitive, with new players and tech companies dominating, while traditional manufacturers struggle with their self-developed technologies [11][12]. - Companies like Chery and Great Wall have faced significant setbacks in their self-research efforts, leading to a shift towards partnerships with Huawei for survival [13][14]. - The article emphasizes that collaboration with Huawei is seen as a necessity for traditional car manufacturers to keep pace with the rapid technological advancements in the industry [14][19]. Group 2: Collaboration with Huawei - Many car executives have visited Huawei's headquarters, seeking guidance and collaboration to enhance their smart driving capabilities [3][8][10]. - Huawei offers various cooperation models, including component supply, full-stack solutions, and deep involvement in product design and marketing, which allows car manufacturers to leverage Huawei's technology without fully losing their brand identity [17][21]. - The article notes that while some collaborations have yielded positive results, such as the AITO brand, others have struggled with market acceptance and internal conflicts [21][22]. Group 3: Challenges and Risks - The dependence on Huawei's technology raises concerns about brand dilution for car manufacturers, as consumers may associate the product more with Huawei than the car brand itself [19][24]. - Companies like Li Auto and Xiaopeng, which initially focused on self-research, are now integrating Huawei's technologies, reflecting the industry's shift towards collaboration despite previous competitive tensions [18][19]. - The article warns that while partnerships can provide immediate benefits, they may also lead to long-term challenges in maintaining a unique brand identity and technological independence [23][24].

Group 1 - The core viewpoint is that the Chinese electric vehicle (EV) market is undergoing a significant reshuffle, with predictions that only 5-8 brands will survive in the future, including established players like Tesla and BYD [1][2][21] - The concept of a "moat" is crucial for companies to maintain competitive advantages, which can include brand strength, technological superiority, and cost advantages [3][4][8] - The current intense competition in the EV sector is attributed to the diminishing moats, allowing new entrants to compete more effectively with established brands [4][6] Group 2 - Tesla is highlighted as the market leader with several advantages, including technological leadership in Full Self-Driving (FSD), cost control, and a strong brand image [10][11][16] - Despite Tesla's technological edge, it is noted that this advantage may not be sustainable in the long term due to increasing competition from other manufacturers [12][15] - Tesla's cost control strategy has allowed it to reduce production costs significantly, with the Model Y's production cost dropping by 30% from 2020 to 2023, enabling it to engage in price wars effectively [16][17] Group 3 - BYD is recognized for its supply chain advantages and scale, which have allowed it to achieve the lowest costs in the industry, with a market share of 33.2% in 2024 [22][29][26] - BYD's extensive control over its supply chain, from raw materials to battery production, contributes to its competitive edge [24][22] - However, BYD's heavy asset base poses risks, as maintaining such a structure requires substantial ongoing investment [30][33] Group 4 - New entrants like Huawei and Xiaomi are adopting different strategies, with Huawei focusing on a light-asset model that provides technology without heavy investment in manufacturing [36][40][42] - Xiaomi's approach leverages its existing brand trust from the smartphone market to penetrate the automotive sector, achieving remarkable sales figures [50][56][58] - The new forces in the EV market, including NIO, Xpeng, and Li Auto, are still developing their moats, with varying degrees of success in establishing competitive advantages [63][68]

Group 1 - Multiple new energy vehicle companies reported significant year-on-year growth in January 2024 deliveries, including Lantu, Li Auto, Zeekr, Xpeng, and Neta [1][2] - Lantu delivered 7,041 vehicles in January, marking a 355% increase year-on-year, and aims for an annual sales target of 100,000 units [2] - Li Auto delivered 31,165 vehicles in January, a 105.8% increase year-on-year, with a cumulative delivery of 664,529 vehicles since inception, targeting 800,000 annual deliveries in 2024 [2] Group 2 - Zeekr, Leap Motor, NIO, Neta, and Xpeng also reported substantial year-on-year delivery increases, with deliveries of 12,537, 12,277, 10,055, 10,032, and 8,250 vehicles respectively [2] - Neta announced overseas sales of 2,821 vehicles in January, with a global sales target of 300,000 units for the year [3] - Xpeng revealed that its XNGP smart driving feature has a monthly active user penetration rate exceeding 85%, with plans for suppliers to prepare for monthly sales of 20,000 to 30,000 units [3] Group 3 - AITO Wenjie emerged as a market leader with 32,973 vehicles delivered in January, a 34.76% month-on-month increase, and the new M7 model achieved a record delivery of 31,253 units [3][4] - Various new energy vehicle companies initiated promotional activities ahead of the Spring Festival, offering discounts and incentives to attract consumers [5] - Companies like Aion, Geely, and Tesla launched promotional campaigns, while Zeekr and Li Auto are enhancing their service infrastructure, including charging stations [5][6]