今年广州车展上智能辅助驾驶技术的发展趋势十分明显：一边"向上"，朝着高阶水平进化，在更安全的同时适配更多场景；一边"向下"，即不断"下放"到更多 车型。 除小鹏等极少数车企采取全栈自研智能驾驶技术外，大多数车企选择接入以"地大华魔(地平线、大疆、华为、Momenta)"为核心的第三方供应商的方案。广 州车展地平线HSD（Horizon SuperDrive）城区辅助驾驶系统公布的进展尤其引人关注。今年4月，地平线推出基于自家征程6系列芯片打造的城区辅助驾驶 方案HSD，半年后HSD就已被搭载在多款量产车型上：首发车型奇瑞星途ET5将于11月28日正式上市，奇瑞全新合作车型风云T9L与iCAR V27亮相广州车 展，HSD赋能的深蓝汽车合作车型深蓝L06已上市发售。 第三方智驾方案落地一款新车，需供应商在定义阶段就与主机厂共创。地平线HSD能在半年时间内就登陆4款量产车，堪称神速。在HSD规模化量产媒体沟 通会上，地平线还透露，HSD已获得国内外一共10家车企品牌，超20款车型的定点合作，未来3-5年HSD计划达成千万量产目标。 地平线HSD的落地进程比外界预期的都要快，一夜之间，中国车企拥有了媲美FSD的智驾 ...

作为全国顶尖车展之一，今年广州车展主题被设定为"新科技·新生活"。官方数据显示，这届车展一共展示了1085台展车，新能源车629台占比高达58%，这 表明中国汽车产业"三电化"已全面完成。与此同时，据雷科技·电车通车展报道团小伙伴们观察，包括小米、小鹏、蔚来、赛力斯、比亚迪、鸿蒙智行在内 的车企，均在车展重点强调"AI汽车"、"AI化"、"智能化"等概念，发力智能辅助驾驶更是成了头部车企们的共识。 "不造车的特斯拉"，地平线HSD成高阶智驾的新解法 汽车正在不断朝着AI汽车机器人的终极形态进化。国产汽车在"三电化"层面已全面引领世界， 然而在AI汽车的终极战场，也是最重要的价值锚点"智能驾 驶"上，国产车一直差口一气。今年10月，特斯拉在美国市场面向部分汽车OTA推送了FSD v14.1版本，在架构、功能和交互上均有大幅提升，成为近一年内 最具代表性的智驾版本之一，国产车智驾水平与特斯拉FSD的距离被进一步拉开。 第三方智驾方案落地一款新车，需供应商在定义阶段就与主机厂共创。地平线HSD能在半年时间内就登陆4款量产车，堪称神速。在HSD规模化量产媒体沟 通会上，地平线还透露，HSD已获得国内外一共10家车企品 ...

行情速递 ① 主 板 领 涨 ， 省 广 集 团 (+10.06%)/ 特 发 信 息 (+10.05%)/ 名 臣 健 康 (+10.03%)/ 石 基 信 息 (+10.00%)/数据港(+10.00%)/ ②创业板领涨，久之洋(+20.00%)/中富电路(+17.75%)/蓝色光标(+15.72%)/ ③科创板领涨，金橙子(+20.01%)/光云科技(+20.00%)/品高股份(+19.99%)/ ④活跃子行业，SW营销代理 (+8.32%)/SW横向通用软件(+4.79%)/ 国内新闻 ①艾邦半导体网，国内液冷散热厂商鼎通科技官微宣布称其224G光模块液冷 散热产品进入英伟达供应链/即将批量供应/ ③半导体芯闻，禾赛科技发布基于 RISC-V 架构的激光雷达专用高性能智能 主控芯片费米 C500/其单芯片集成 MCU、FPGA、ADC 于一体/是全球首 款片上融合功能安全与网络安全双重认证的激光雷达专用主控芯片/从硬件层 满足车载场景对可靠性与信息安全的严苛要求/ ②半导体投资联盟，地平线发文称/HSD已获得国内外10家车企品牌、超20 款车型的定点合作/随着规模化装车的全面开启/地平线HSD将以更高 ...

地平线HSD采用一段式端到端架构，并融入强化学习能力，实现从"光子输入到轨迹输出"的系统超低时 延，大幅提升辅助驾驶的安全、效率、舒适。 目前，搭载HSD的奇瑞星途ET5启动预售，风云T9L、iCAR V27亮相广州车展，以"量产即爆款"之势赢 得市场开门红，展现出强劲的市场竞争力。同时，HSD系统已与超10家主流车企达成深度合作，预计将 陆续搭载于20余款新车型。在征程系列芯片累计出货突破千万套的基础上，地平线已明确下一阶段战略 目标：未来3–5年内，HSD达成千万量产，让高阶辅助驾驶惠及千家万户。 荣膺行业殊荣，夯实智能驾驶产业基石 近日，地平线在行业评选中捷报频传，旗下产品与公司实力双双获得权威认可。其中，HSD(Horizon SuperDrive™)接连斩获网易年度新车总评榜"年度高阶智驾普惠奖"与每日经济新闻猎车榜"年度标杆级 辅助驾驶方案"；地平线公司则获评21世纪经济报道"年度智驾供应商"及盖世汽车金辑奖"中国汽车新供 应链百强"称号。 这一系列荣誉不仅印证了地平线在智能驾驶领域的领先地位，更凸显出其独特的产业价值：HSD以前沿 技术推动高阶智驾走向普及，而地平线则作为智能驾驶产业的"最大公约 ...

规模化量产是检验企业综合实力与市场认可度的核心标准。自2025年4月发布以来，地平线HSD迅速成为主流车企布局城区辅助驾驶的共识之选。全球首搭 车型星途ET5以"超人反应，类人思考，拟人控车"的全场景辅助驾驶体验赢得市场关注，目前已全面开启预售，将于11月28日正式上市。地平线深度赋能的 另一款车型深蓝L06，全系标配激光雷达和征程6，首发搭载地平线、深蓝与长安三方共创的DEEPAL AD Max系统，已于11月18日正式上市。在广州车展期 间，星途ET5、深蓝L06、风云T9L、iCAR V27四款车型还联袂亮相"地平线智驾科技畅行俱乐部-广州站"活动，直观展现"城区辅助驾驶人人可享"的发展图 景。 地平线称，在征程家族达成千万量产后，公司进一步提出未来3-5年实现HSD千万量产的目标，通过持续释放的规模化效应，加速高阶辅助驾驶的普惠进 程。 11月21日开幕的广州车展上，搭载地平线HSD城区辅助驾驶系统及征程®6P的全新合作车型风云T9L与iCAR V27正式亮相，标志着地平线HSD城区辅助驾驶 系统全面进入规模化量产新阶段。此前，星途ET5已成为全球首搭地平线HSD及征程6P的车型。 作为智能驾驶领域的 ...

Core Insights - The article highlights significant developments in the autonomous driving industry, particularly the performance of Horizon HSD and the advancements in Xiaopeng's VLA2.0, indicating a shift towards end-to-end production models [1][3]. Group 1: Industry Developments - Horizon HSD's performance has exceeded expectations, marking a return to the industry's focus on one-stage end-to-end production, which has a high potential ceiling [1]. - Xiaopeng's VLA2.0, which integrates visual and language inputs, reinforces the notion that value-added (VA) capabilities are central to autonomous driving technology [1]. Group 2: Educational Initiatives - The article discusses a new course titled "Practical Class for End-to-End Production," aimed at sharing production experiences in autonomous driving, focusing on various methodologies including one-stage and two-stage frameworks, reinforcement learning, and trajectory optimization [3][8]. - The course is limited to 40 participants, emphasizing a targeted approach to skill development in the industry [3][5]. Group 3: Course Structure - The course consists of eight chapters covering topics such as end-to-end task overview, two-stage and one-stage algorithm frameworks, navigation information applications, reinforcement learning algorithms, trajectory output optimization, fallback solutions, and production experience sharing [8][9][10][11][12][13][14][15]. - Each chapter is designed to build upon the previous one, providing a comprehensive understanding of the end-to-end production process in autonomous driving [16]. Group 4: Target Audience and Requirements - The course is aimed at advanced learners with a background in autonomous driving algorithms, reinforcement learning, and programming skills, although it is also accessible to those with less experience [16][17]. - Participants are required to have a GPU with recommended specifications and a foundational understanding of relevant mathematical concepts [17].

Core Viewpoints - The article presents eight key viewpoints regarding the performance and evaluation of autonomous driving technologies, particularly focusing on the comparison between Horizon's HSD and Li Auto's VLA systems [3]. Group 1: Performance Evaluation - The experience with Horizon's HSD during a 1.5-hour test drive was notably better than the current production version of Li Auto's L7 VLA, although future production versions may not match the engineering version's performance [3][5]. - The evaluation of HSD's performance is limited due to the lack of comprehensive safety assessments and the variability of experiences across different locations [3][7]. - The HSD system demonstrated good vertical control, but its performance can vary significantly based on the city and driving conditions [6][7]. Group 2: Technical Comparisons - Horizon employs a VA-style end-to-end approach, while Li Auto utilizes a VLA-style end-to-end system, with the naming being a mere distinction [9][10]. - The VA-style end-to-end system is perceived to have advantages in user experience due to current limitations in computing power and bandwidth faced by the VLA approach [6][12]. - Li Auto's decision to pursue VLA for mass production is seen as a bold move, but it comes with challenges related to resource allocation and the need for higher computational requirements [11][12]. Group 3: Industry Outlook - There is a prevailing belief that many autonomous driving operators will eventually converge in capabilities, with only a few manufacturers able to survive without in-house development of autonomous driving technologies [3][11]. - The article suggests that manufacturers lacking self-research capabilities in autonomous driving may struggle to adapt to the evolving smart vehicle industry [3][11]. - The future landscape of autonomous driving will likely see a concentration of capabilities, with differentiation becoming increasingly important as the industry matures [3][11].

Core Viewpoints - The article presents eight key viewpoints regarding the performance and evaluation of autonomous driving technologies, particularly focusing on the experiences with Horizon's HSD and Li Auto's VLA systems [2]. Group 1: Performance Evaluation - TOP2 found the Horizon HSD software experience during a 1.5-hour test drive in Hangzhou to be significantly better than the current production version of Li Auto's L7 VLA [2]. - There is a possibility that the production version of Horizon's software may not perform as well as the engineering version experienced during the test [2]. - The evaluation of autonomous driving systems is limited by the number of test experiences, as a few tests cannot generalize performance across different regions [3]. Group 2: Technical Architecture - Horizon employs a VA-style end-to-end system, while Li Auto uses a VLA-style end-to-end system, with the naming being a minor distinction [3][9]. - The current technological landscape suggests that VA-style systems may have advantages in user experience due to existing computational and bandwidth limitations [6]. - Li Auto's decision to adopt a VLA-style system is seen as a courageous move, as it requires significant resources and presents various challenges [14]. Group 3: Market Dynamics - The future landscape of autonomous driving operators is uncertain, with a prevailing belief that only a few companies will survive, particularly those capable of self-developing their technologies [4]. - Companies lacking self-research capabilities in autonomous driving may struggle to adapt to the evolving smart vehicle industry [4]. - The article emphasizes that autonomous driving is not merely a selling point but a differentiating capability that can lead to high market concentration due to low marginal costs [4]. Group 4: User Experience Insights - Feedback from Horizon personnel indicated that the performance of their systems in extreme weather and complex scenarios is generally average, highlighting the need for comprehensive testing [5][6]. - The experiences reported during the test drives varied significantly based on the vehicle models and their respective chip capabilities, indicating that performance can be inconsistent [7]. - The article suggests that the perception of Horizon's HSD performance may be overly positive due to selective testing locations and conditions [8].

Core Insights - The article discusses the advancements in autonomous driving technology, particularly focusing on the performance of Horizon's HSD system compared to Li Auto's VLA system, highlighting the strengths and weaknesses of both [5][6]. Group 1: Technology Comparison - Horizon's HSD technology architecture utilizes visual information for trajectory output, with laser radar positioning as a safety redundancy, while the VLA system is criticized for its high computational and bandwidth requirements [5]. - During a test drive of the Horizon HSD engineering vehicle, the experience was reported to be significantly better than the current production version of Li Auto's VLA, particularly in terms of comfort and smoothness during traffic conditions [6]. - Feedback from the Horizon team indicated that the HSD system performs well in controlled environments but has limitations in extreme weather and complex scenarios, suggesting a need for further development [7]. Group 2: Community and Collaboration - The article mentions the establishment of nearly a hundred technical discussion groups related to various aspects of autonomous driving, with a community of around 4,000 members and over 300 companies and research institutions involved [8]. - The collaboration between Horizon and vehicle manufacturers is emphasized, with a focus on integrating user interface elements that respect manufacturer preferences, which can impact the overall driving experience [7]. Group 3: Future Outlook - The article suggests that while the HSD system shows promise, it is still in development and may not yet reach full autonomous driving capabilities, estimating it to be around 60% of the level of Li Auto's V13 system [7].

Core Viewpoint - The article discusses the comparative performance of Horizon's HSD technology and Li Auto's VLA system, highlighting the strengths and weaknesses of both in terms of autonomous driving capabilities and user experience [1][2]. Group 1: Performance Comparison - Horizon's HSD engineering vehicle demonstrated superior auxiliary driving capabilities compared to Li Auto's L7 VLA as of October 2025, although there is a possibility that mass production vehicles may not perform as well as engineering prototypes [1]. - During a 1.5-hour test drive around West Lake in Hangzhou, the HSD vehicle showed high levels of comfort and smoothness, with no need for manual speed adjustments, contrasting with the frequent adjustments required in the Li Auto VLA [2]. - Feedback from multiple testers indicated that the A model of Horizon's HSD performed well, while the B model was considered average, attributed to differences in chip computing power and collaboration between the two companies [2]. Group 2: Limitations and Challenges - Horizon's team acknowledged that the HSD system performs poorly in extreme weather, non-standard scenarios, and complex situations, indicating that it is not yet fully reliable for autonomous driving [3]. - The team also noted that the transition from auxiliary driving to full autonomy can sometimes lead to subpar experiences, particularly in scenarios requiring navigation adjustments [3]. - The integration of HUD and vehicle interfaces is crucial for the overall driving experience, with some design choices being counterintuitive, which could affect user satisfaction [3]. Group 3: Community Engagement - There is an invitation for deeper discussions regarding Li Auto's operational status and long-term fundamentals, emphasizing a focus on practical business insights rather than technical discussions [4].