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].

WeRide (WRD.O/0800.HK) Conference Call Summary Company Overview - **Company**: WeRide - **Ticker**: 0800.HK (H-share), WRD.O (ADR) - **Founded**: 2017 - **Industry**: Autonomous Driving - **Global Presence**: Operations in over 30 cities across 11 countries, with permits in seven markets including China, Saudi Arabia, UAE, Singapore, France, Belgium, and the US [16][21] Key Points Coverage Initiation - **Rating**: Initiated coverage on WeRide-H with a Buy/High Risk rating - **Target Price**: HKD39.6 for H-share and US$15.3 for ADR, adjusted from US$18.2 due to share dilution from H-share listing [1][4] Market Forecast - **Robotaxi Market Growth**: - Fleet size expected to grow from 3.8k units in 2025 to 538k units in 2030 and 2.3 million units in 2035 - CAGR of 169% from 2025 to 2030 and 34% from 2030 to 2035 - Total addressable market for robotaxis in China projected to reach US$15 billion in 2030 and US$68 billion in 2035, with a CAGR of 229% from 2025 to 2030 [2] Cost Reduction - **Vehicle Cost**: Anticipated decline in full vehicle cost per Robotaxi to US$32.4k in 2030 and US$28.2k in 2035, with a CAGR of -6% from 2025 to 2030 and -3% from 2030 to 2035 [2] Major Milestones - **Expansion**: Launched Robotaxi and Robobus pilots in Ras Al Khaimah, UAE, marking the third emirate of operation [3][10] Financial Projections - **EPS Forecast**: Updated EPS forecast for 2025-27E to Rmb -4.44/-3.89/-2.82, down from Rmb -5.34/-4.68/-3.39 due to share dilution [4] - **Free Cash Flow**: Expected outflow of Rmb1.58 billion in 2025, Rmb1.16 billion in 2026, and Rmb1.14 billion in 2027, with potential refinancing needed in 2027 [9] Valuation Metrics - **Valuation Methodology**: DCF valuation with a WACC of 17.1% and a terminal growth rate of 2% - **Target Price Implications**: Implies 13x 2027E PS and 1.3x 2030E PS/9.0x 2030E PE, with current trading around 8x 2027E PS and 0.8x 2030E PS/5.6x 2030E PE [4][18] Investment Strategy - **High-margin Overseas Business**: Significant milestones achieved overseas, with partnerships with Uber and Grab to accelerate deployment of L4 robotaxis [17][22] - **Cost Advantages**: Latest robotaxi model GXR priced at USD 40k with advanced computing power of 2,000 TOPS, expected fleet size of 1k units by end-2025 [17][22] Risks - **High Risk Rating**: Due to loss-making status and uncertainties in robotaxi development - **Key Risks**: Include technological challenges, business model uncertainty, safety concerns, competition, regulatory risks, cash shortages, and limited operating history [19][24] Conclusion - WeRide is positioned as a leader in the autonomous driving sector with significant growth potential in the robotaxi market, supported by strategic partnerships and cost advantages. However, the company faces substantial risks that could impact its future performance.

Core Viewpoint - Baidu Group's stock has seen an increase of over 4%, currently trading at 130.4 HKD, with a transaction volume of 245 million HKD, following the announcement of significant developments in the autonomous vehicle sector by its partner,萝卜快跑 [1] Group 1: Company Developments - 萝卜快跑 has received the first batch of fully autonomous commercial operation licenses from the Abu Dhabi Integrated Transport Centre (ITC), marking a key advancement in its global strategy [1] - Since entering the Abu Dhabi market in March, 萝卜快跑 has formed a strategic partnership with AutoGo to deploy sixth-generation autonomous vehicles in specific areas, aiming for full autonomous operation by 2026 [1] - The collaboration aims to create the largest fleet of autonomous vehicles in Abu Dhabi, enhancing urban traffic efficiency and reducing carbon emissions, contributing to the city's smart city goals [1] Group 2: Operational Metrics - As of October 31, 萝卜快跑 has surpassed 250,000 weekly orders, all of which are fully autonomous [1] - The total number of global orders serviced by 萝卜快跑 has exceeded 17 million [1]

Core Viewpoint - The article discusses the transition from autonomous driving to embodied intelligence, highlighting the differences in challenges and solutions between the two fields. It emphasizes the importance of documenting past experiences in autonomous driving, despite the focus shifting to embodied intelligence. Research Areas Summary - The main research areas include 3D fusion perception, trajectory prediction, end-to-end motion planning, sensor simulation, traffic flow simulation, and foundational models for intelligent driving. These areas are interconnected and aim to build a comprehensive autonomous driving algorithm system [2][5]. 1. Sparse4D Series: Multi-Sensor Fusion Perception Framework - The Sparse4D series aims to improve perception performance by utilizing sparse queries and projection sampling from multi-view images, avoiding the computational costs associated with BEV (Bird's Eye View) methods. Sparse4D v1 introduced deformable aggregation for sparse fusion, while v2 improved temporal fusion complexity from O(T) to O(1) [6][9]. Sparse4D v3 further enhanced detection and tracking capabilities, achieving top rankings in camera-only detection and tracking leaderboards [11][13]. 2. SparseDrive: End-to-End Planning Attempt - SparseDrive integrates online mapping and motion planning, achieving five tasks: detection, tracking, mapping, prediction, and planning. It raises concerns about the simplicity of its planning decoder and the need for closed-loop performance evaluation [13][15]. 3. EDA & UniMM: Trajectory Prediction and Traffic Flow Simulation - EDA (Evolving and Distinct Anchors) addresses the core issue of anchor and sample allocation in trajectory prediction, enhancing model convergence. UniMM unifies existing traffic simulation models and proposes a general algorithm framework, addressing key performance factors [16][20]. 4. DriveCamSim: Sensor Simulation - DriveCamSim focuses on creating a highly controllable sensor simulation system to evaluate autonomous driving models efficiently. It emphasizes the need for a simulation system that can accurately reflect model performance without relying solely on real-world testing [22][24]. 5. LATR: Foundational Model for Intelligent Driving - LATR aims to build a robust foundational model for intelligent driving using large datasets and parameters. It employs a masking strategy for unsupervised training and integrates multiple tasks into a unified framework, demonstrating effective performance [26][27]. Conclusion and Outlook - The seven modules collectively form the core link of the autonomous driving system, indicating a correct technological path. The article suggests that the future focus should be on efficient evaluation systems and the potential of reinforcement learning to enhance model performance [30][31].

Group 1 - Grab is investing $60 million in remote driving service company Vay to enhance its presence in the autonomous vehicle technology sector [1] - The investment could increase to $410 million within a year if Vay meets certain milestones, pending regulatory approval, with the transaction expected to be completed in Q4 [1] - Vay's service model operates between traditional taxis and fully autonomous vehicles, where a remote operator controls the vehicle until it reaches the customer, who then takes over driving [1] Group 2 - Grab is not the only ride-hailing platform preparing for the future of autonomous driving, as its U.S. counterparts Uber and Lyft are also collaborating with technology suppliers and fleet operators for global deployment [1]

Core Viewpoint - Autonomous driving is expected to fundamentally reshape human social behavior paradigms, liberating the "third space" of human activity, which is currently constrained by commuting time and energy expenditure [2][6]. Group 1: Company Overview - Pony AI Inc. (stock code: 02026.HK) completed its dual listing on the Hong Kong Stock Exchange on November 6, 2025, with a total market capitalization of approximately HKD 53.9 billion [3]. - The company had previously gone public on NASDAQ under the stock code "PONY" on November 27, 2024, raising about USD 452 million through its IPO, marking the largest IPO in the autonomous driving sector that year [6]. Group 2: Investment Background - 卓源亚洲, one of the earliest investors in Pony AI, made investments in 2016 and 2021, with its founder 林海卓 having a background in computer science from Tsinghua University, similar to Pony AI's founders [4][5]. - The investment firm has also invested in various AI companies, including 中科时代, 清微智能, and others, focusing on integrated circuits and artificial intelligence [7]. Group 3: Market Perception - The perception of autonomous driving as a transformative technology is rooted in its potential to free up time for creative activities, as many individuals in first- and second-tier cities spend up to two hours commuting daily [6]. - The early discussions among the founders and investors highlighted the significance of algorithms like BFS and D* in the future of autonomous driving, indicating a strong technical foundation for the company's development [5].

Core Viewpoint - WeRide has officially listed on the Hong Kong Stock Exchange, becoming the first Robotaxi company to be publicly traded in both Hong Kong and the United States, marking a significant milestone in the autonomous driving industry [2][3]. Group 1: Listing Details - WeRide issued a total of 88.25 million shares at a price of HKD 27.1 per share, raising approximately HKD 2.39 billion before the greenshoe option [2]. - The CEO, Tony Han, has signed a three-year lock-up agreement, demonstrating confidence in the company's fundamentals and growth prospects [2]. Group 2: Company Achievements - WeRide is the only company globally to have its products licensed for autonomous driving in seven countries, including China, UAE, Singapore, Saudi Arabia, France, Belgium, and the USA [5]. - The company operates over 1,500 L4 autonomous vehicles, with more than 700 being Robotaxis, and has partnered with Uber to operate the largest commercial Robotaxi fleet outside of China and the USA [5]. Group 3: Technological Advancements - WeRide's autonomous driving technology spans L2 to L4 levels, providing services such as Robotaxi, Robobus, Robosweeper, and Robovan, supported by the self-developed WeRide GENESIS simulation engine [4]. - The company has achieved significant milestones in commercializing L4 autonomous vehicles, with operations in major cities like Guangzhou and Beijing, and maintaining a lead of at least 1.5 years over competitors in key markets [6]. Group 4: Future Plans - WeRide aims to deploy tens of thousands of Robotaxis by 2030, continuing to expand its global commercial operations and technological development [5][6]. - The company is committed to creating a safer, more efficient, and sustainable smart mobility ecosystem through partnerships with global leaders like NVIDIA, Bosch, and Renault-Nissan [5][7].

China's Autonomous Driving company WeRide debuts on the Hong Kong stock exchange. The company's Founder & CEO Tony Han says this listing marks a milestone and he plans to use the raised fund on recruitment, data centre, sales network, and building a global taxi fleet. He speaks with Annabelle Droulers at the stock exchange on "Bloomberg: The China Show". ...

By Kane Wu and Scott Murdoch (Reuters) -Pony Ai and WeRide stocks plunged around 10% each Thursday as the Chinese autonomous driving developers started trading in Hong Kong, with analysts pinning the blame on new-listing oversupply as well as the ​firms' overseas share performance. WeRide shares closed down 10% from their issue price while Pony Ai stock lost 9.3%, after ‌the two companies raised almost $1.2 billion in separate public share offerings. The weak performance came one day after electric vehi ...

Shares of China's WeRide were set to open down nearly 8% in its Hong Kong Stock Exchange debut on Thursday after it raised about $308 million in its listing. ...