文远知行(WRD.US)盘前涨超3%，报9美元。消息面上，文远知行宣布，截至2026年1月12日，文远知行 全球Robotaxi(自动驾驶出租车)车队规模有1023辆车。目前，文远知行Robotaxi驶入全球10多座核心城 市，在广州、北京和阿布扎比实现了纯无人Robotaxi商业化运营，阿布扎比车队即将实现单车盈亏平 衡。(格隆汇) ...

但另有网友透露，事故场景是电动自行车在湿滑路面失控滑倒，车上两人跌落地面无法动弹，自动驾驶车辆路过时未能及时侦测到躺在地上的人员，从 而导致了拖行事故。此外，有目击者曾在网上表示，类似情况并非首次出现，称曾在洒水车作业后的光滑路面看到行人滑倒后未被哈啰无人驾驶车辆侦测到 而发生碰撞。在"罗生门"下，真相模糊难辨，但都指向了一个不争的事实：自动驾驶技术的发展仍然任重道远。 去年6月底，哈啰官宣入局Robotaxi，并在不久后获得湖南株洲和江苏溧阳的运营资质，投入约80辆运营车辆。但据内部人士透露，哈啰在上述两地运 营的大部分Robotaxi，并非哈啰计划中与启辰合作的量产车HR1，而是行业内极为成熟的百度Apollo RT6。据悉，百度Apollo正在为哈啰提供车辆、运维及 百度地图的入口导流。正是因为采用了百度已经验证成熟的方案，哈啰才得以跳过漫长的技术积累期，在短短几个月内实现运营。 技术"罗生门" 专家介绍，纯视觉、激光雷达、毫米波雷达等不同感知方案各有优劣。例如，纯视觉方案依赖光线，在恶劣天气、强光或夜间的效果欠佳，测距精度也 相对较低。而激光雷达在浓雾、暴雨、大雪、严重沙尘等恶劣环境下，会使激光束显著 ...

来源 | 机器之心 原文链接： 端到端智驾新SOTA | KnowVal：懂法律道德、有价值观的智能驾驶系统 点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 >>自动驾驶前沿信息获取 → 自动驾驶之心知识星球 本文只做学术分享，如有侵权，联系删文 一个智能驾驶系统，在迈向高阶自动驾驶的过程中，应当具备何种能力？除了基础的感知、预测、规划、决策能力，如何对三维空间进行更深入的理解？如 何具备包含法律法规、道德原则、防御性驾驶原则等知识？如何进行基本的视觉 - 语言推理？如何让智能系统具备世界观和价值观？ 来自北京大学王选计算机研究所王勇涛团队的最新工作 KnowVal 给出了一种有效可行的方案。 通过自动驾驶领域专用感知和开放式三维感知，能够抽取常见实例与长尾实例的 3D 目标检测结果与实例特征，以及面向开放世界的全场景占据栅格预测与 体素特征，抽取特征保证了整个系统的特征传递与可导；同时，通过利用轻型 VLM 实现的抽象元素理解，能够对上一时间帧知识检索分支要求的信息进行 补充，针对「是否是隧道、桥梁场景？是否是夜间场景？」等抽象概念进行自然语言描述。 论 ...

北京商报讯(记者魏蔚)1月16日，文远知行宣布，截至2026年1月12日，文远知行全球Robotaxi(自动驾驶 出租车)车队规模有1023辆车。目前，文远知行Robotaxi驶入全球10多座核心城市，在广州、北京和阿布 扎比实现了纯无人Robotaxi商业化运营，阿布扎比车队即将实现单车盈亏平衡。 ...

Group 1 - The core point of the article is that Wenyan Zhixing has officially entered the "thousand-vehicle era" with its global Robotaxi fleet, marking a significant milestone in the scale deployment of autonomous driving and advancing the commercialization of the global autonomous driving industry [1][3] - The new generation Robotaxi GXR, which is the world's first Robotaxi equipped with the NVIDIA DRIVE Thor X chip, provides 2000 TOPS AI computing power and meets L4 autonomous driving requirements, leading to a 50% reduction in autonomous driving kit costs and an 84% decrease in total lifecycle costs [1][3] - Wenyan Zhixing's Robotaxi has established a global operational network covering over 10 major cities across Asia, the Middle East, and Europe, with successful commercial operations in Guangzhou and Beijing [3] Group 2 - The company has achieved a fourfold increase in fleet size in Abu Dhabi since launching pure unmanned commercial operations in December 2024, nearing breakeven on a per-vehicle basis, and plans to expand to Singapore by 2026 [3] - To enhance user experience, Wenyan Zhixing launched the "Wenyan Travel" WeChat mini-program, allowing users to easily call for Robotaxi services without downloading an app, thereby increasing service accessibility [4] - The company aims to deploy hundreds of thousands of Robotaxis globally by 2030, contributing to the intelligent and low-carbon transformation of transportation systems, and its thousand-vehicle deployment serves as a benchmark for the industry [4]

Core Viewpoint - Pony.ai-W (02026) has entered a new phase of strategic cooperation with BAIC New Energy, focusing on the commercialization and global expansion of L4-level Robotaxi technology [1] Group 1: Strategic Cooperation - Pony.ai and BAIC New Energy have officially announced a comprehensive deepening of their strategic cooperation, marking the beginning of Cooperation 2.0 [1] - The partnership aims to expand the breadth and depth of collaboration based on the successful experience of L4-level Robotaxi mass production and operation [1] Group 2: Product Development - The collaboration will transition from a "single model" approach to a "full spectrum" strategy, leveraging the mass production experience of the Arcfox Alpha T5 Robotaxi [1] - The goal is to develop a richer product matrix of Robotaxi vehicles, focusing on L4-level autonomous driving models [1] Group 3: Market Expansion - The partnership will extend the validated product experiences and technical solutions to the passenger vehicle market, targeting high-end intelligent driving models [1] - The integration of strategic resources is emphasized to enhance the overall effectiveness of the collaboration [1]

小马智行-W(02026)涨近3%，截至发稿，涨2.4%，报128.1港元，成交额1640.85万港元。 其中，在产品共创层面，合作将实现从"单一车型"到"全景谱系"的跨越，以极狐阿尔法T5 Robotaxi量产 经验为基础，正向研发L4级自动驾驶车型，打造更丰富Robotaxi产品矩阵；并将已合作验证的产品经验 和技术方案，以"前装可量产"为标准，延伸至乘用车市场的高阶智能驾驶车型，实现战略资源的高度整 合。 消息面上，据小马智行官微消息，近日，小马智行与北汽新能源宣布，双方正式达成"五位一体"的全面 深化战略合作，开启合作2.0阶段。双方将基于L4级Robotaxi规模化量产和运营的成功经验，全面扩大 合作广度与深度，聚焦自动驾驶的量产化、商业化与全球化。小马智行与北汽新能源共同将L4级 Robotaxi领域已验证的成功模式，拓展至产品、技术、市场等多维度。 ...

" 在实力与困境的拉扯中，流血上市已成为最可能的路径。 " 作者丨张进 编辑丨李雨晨 2025年，大批科技公司扎堆赴港IPO，其中自动驾驶 L4 赛道尤为拥挤。 11月，"Robotaxi 双子星"文远知行和小马智行同期登陆港股市场，12月初，由"大疆教父"李泽湘创办的 希迪智驾在香港联合交易所主板挂牌上市，成为港股"商用车智驾第一股"。紧接着，无人驾驶卡车公司主 线科技、易控智驾也向联交所提交了上市申请。 IPO 的风终于吹到了无人驾驶卡车（Robotruck）赛道，但资本市场的反响并不乐观。作为商用车第一 股，希迪智驾上市即破发，这无疑给排队中的其他 Robotruck 公司带来了压力。大家同属于自动驾驶"无 人驾驶卡车"细分赛道，希迪智驾、易控智驾专注于矿山等封闭场景，主线科技则深耕港口、机场、干线 等封闭场景。 资本市场用脚投票。希迪智驾上市即破发的情况，反映出资本市场对Robotruck行业从技术验证迈向商业 盈利"道阻且长"的一种悲观预期。而其中提交了上市申请的主线科技，"扎眼"的招股书透露出紧迫的财务 状态，寻求资本输血已经迫在眉睫。 01 主线科技的分家往事 L4行业出现过几次创始团队"分家" ...

其中，在产品共创层面，合作将实现从"单一车型"到"全景谱系"的跨越，以极狐阿尔法T5 Robotaxi量产 经验为基础，正向研发L4级自动驾驶车型，打造更丰富Robotaxi产品矩阵；并将已合作验证的产品经验 和技术方案，以"前装可量产"为标准，延伸至乘用车市场的高阶智能驾驶车型，实现战略资源的高度整 合。 消息面上，据小马智行官微消息，近日，小马智行与北汽新能源宣布，双方正式达成"五位一体"的全面 深化战略合作，开启合作2.0阶段。双方将基于L4级Robotaxi规模化量产和运营的成功经验，全面扩大 合作广度与深度，聚焦自动驾驶的量产化、商业化与全球化。小马智行与北汽新能源共同将L4级 Robotaxi领域已验证的成功模式，拓展至产品、技术、市场等多维度。 智通财经APP获悉，小马智行-W(02026)涨近3%，截至发稿，涨2.4%，报128.1港元，成交额1640.85万 港元。 ...

Core Viewpoint - The article discusses the technological anxiety in the intelligent driving sector, particularly among midstream manufacturers, highlighting a slowdown in cutting-edge technology development and a trend towards standardized mass production solutions [1][2]. Group 1: Industry Trends - The mass production of cutting-edge technologies is expected to begin in 2026, with current advancements in intelligent driving technology stagnating [2]. - The overall market for passenger vehicles priced above 200,000 is around 7 million units, but leading new forces have not achieved even one-third of this volume [2]. - The maturity of end-to-end technology is seen as a prerequisite for larger-scale mass production, especially with the advancement of L3 regulations this year [2]. Group 2: Educational Initiatives - A course titled "Practical Class for End-to-End Mass Production" has been launched, focusing on the necessary technical capabilities for mass production in intelligent driving [2]. - The course emphasizes practical applications and is limited to a small number of participants, with only 8 spots remaining [2]. Group 3: Course Content Overview - The course covers various aspects of end-to-end algorithms, including: - Overview of end-to-end tasks, merging perception tasks, and designing learning-based control algorithms [7]. - Two-stage end-to-end algorithm frameworks, including modeling and information transfer between perception and planning [8]. - One-stage end-to-end algorithms that allow for lossless information transfer, enhancing performance [9]. - The application of navigation information in autonomous driving, including map formats and encoding methods [10]. - Introduction to reinforcement learning algorithms to complement imitation learning in driving behavior [11]. - Optimization of trajectory outputs through practical projects involving imitation and reinforcement learning [12]. - Post-processing logic for trajectory smoothing to ensure stability and reliability in mass production [13]. - Sharing of mass production experiences from multiple perspectives, including data, models, and rules [14]. Group 4: Target Audience - The course is aimed at advanced learners with a foundational understanding of autonomous driving algorithms, reinforcement learning, and programming skills [15]. - Participants are expected to have access to a GPU with a recommended capability of 4090 or higher and familiarity with various algorithm frameworks [18].