Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The report highlights the evolution of advanced driver assistance systems (ADAS) in China, focusing on the expansion of operational design domains (ODD), technological equity, safety concerns, and supportive policies [4][21][23] - It emphasizes the need for algorithm, data, and computing power upgrades to address safety shortcomings in high-level ADAS technologies [23][66] - The report discusses the transition from modular to end-to-end architectures in vehicle algorithms, aiming for human-like driving capabilities [66][68] Summary by Sections 1. Market Background - The expansion of high-level ADAS ODD is noted, with a focus on technological inclusivity and addressing accident anxiety through safety redundancies [4][21] - Policy support is highlighted as crucial for rational promotion of ADAS technologies [4][21] 2. Technology Insights - The report decodes the underlying logic of data, algorithms, and computing power in high-level ADAS [4][28] - It discusses the computing power landscape, noting the shift towards higher TOPS (trillions of operations per second) capabilities in vehicle and cloud computing [42][44] - Data challenges, including collection and positioning technologies, are identified as critical areas for development [4][28] 3. Competitive Analysis - The competitive landscape is analyzed, detailing the tiered structure of companies and their development strategies [29][30] - The report outlines various collaboration models among automotive manufacturers and technology providers, emphasizing the balance between self-research and external sourcing [83] 4. Trend Insights - The report notes the commercialization progress of passenger vehicle L3 systems, indicating a growing market for advanced ADAS [31][32] - It highlights the importance of continuous upgrades and iterations in ADAS functionalities to meet evolving consumer expectations and safety standards [82][83]

Core Viewpoint - The article discusses Li Auto's strategic focus on artificial intelligence (AI) and its evolution from a vehicle-centric AI assistant to a multi-platform intelligent application, emphasizing the importance of AI in future competitiveness [4][5][6]. Group 1: Strategic Meetings and AI Prioritization - Li Auto holds biannual closed-door strategy meetings to discuss future directions, with significant participation from top executives and industry leaders [3]. - Following a strategic meeting, Li Auto adjusted its AI-related business priorities, emphasizing the strategic importance of intelligent driving over other AI applications [4][5]. - The company aims to become a global leader in AI by 2030, with a clear focus on enhancing its AI capabilities and applications [5][6]. Group 2: Development of AI Capabilities - Li Auto has transitioned its AI assistant, "Li Xiang," from a vehicle-only application to a multi-platform tool, including mobile and web applications [7]. - The company has invested in self-developed algorithms, achieving a full switch to in-house technology for its AI functionalities by March 2023 [7][8]. - The introduction of the multi-modal cognitive model, Mind GPT 1.0, marks a significant advancement in Li Auto's AI capabilities [7]. Group 3: Intelligent Driving and Technological Advancements - Li Auto's intelligent driving system, AD Max, was launched to address product shortcomings and enhance competitive positioning in the market [10][11]. - The company has initiated a large-scale recruitment drive for its intelligent driving team, reflecting its commitment to advancing this technology [10]. - The shift towards an "end-to-end" model for intelligent driving aims to streamline processes and improve system performance through better data utilization [10][11]. Group 4: Organizational Changes and AI Integration - Li Auto established an AI Technical Committee to integrate AI capabilities across various business lines, enhancing collaboration and execution [15][16]. - The committee includes leaders from key departments, ensuring that AI is a core focus in strategic decision-making [16][17]. - The company aims to develop a foundational model that serves as a core capability for all AI projects, positioning itself as a leader in the automotive AI landscape [17].

Core Viewpoint - The article discusses Li Auto's strategic shift towards AI and intelligent driving, emphasizing the importance of AI in the company's long-term competitiveness and product development [3][10][12]. Group 1: AI Strategy and Development - Li Auto held a strategic meeting in October 2022, where the priority of AI-related business was adjusted, emphasizing the strategic importance of intelligent driving [3][5]. - The company aims to become a global leader in AI by 2030, with significant investments in AI talent and technology [5][10]. - Li Auto's AI assistant, "Li Xiang," has evolved from a car-mounted system to a multi-platform application, indicating a broader vision for AI applications beyond the vehicle [7][8]. Group 2: Intelligent Driving Focus - Intelligent driving was designated as the company's primary strategy in 2023, with plans to heavily invest in this area to compete with major players like Huawei [10][12]. - The company has expanded its intelligent driving team significantly, with over 50 new positions created in late 2023, reflecting a strong commitment to this technology [10][11]. - Li Auto is transitioning its intelligent driving technology from a modular approach to an "end-to-end" model, which is expected to enhance performance and user experience [11][12]. Group 3: Organizational Changes and AI Integration - An AI Technical Committee was established to integrate AI capabilities across various business lines, indicating a strategic focus on AI as a core business direction [14][15]. - The committee includes leaders from product development and research departments, ensuring that AI applications are aligned with the company's overall strategy [15][16]. - Li Auto's foundational model for AI is seen as a critical component for future developments, with aspirations to rank among the top three in the industry [17][18].

Core Viewpoint - The article discusses the advancements in the field of autonomous driving, particularly focusing on the Diffusion model and its application in generating driving trajectories, highlighting the differences between VLM and VLA systems [1][4]. Group 1: Diffusion Model Explanation - Diffusion is a generative model that learns data distribution through a process of adding noise (Forward Process) and removing noise (Reverse Process), akin to a reverse puzzle [4]. - The model's denoising process involves training a neural network to predict and remove noise, ultimately generating target data [4]. - Diffusion not only generates the vehicle's trajectory but also predicts the trajectories of other vehicles and pedestrians, enhancing decision-making in complex traffic environments [5]. Group 2: VLM and VLA Systems - VLM consists of two systems: System 1 mimics learning to output trajectories without semantic understanding, while System 2 has semantic understanding but only provides suggestions [2]. - VLA is a single system with both fast and slow thinking capabilities, inherently possessing semantic reasoning [2]. - The output of VLA is action tokens that encode the vehicle's driving behavior and surrounding environment, which are then decoded into driving trajectories using the Diffusion model [4][5]. Group 3: TransDiffuser Architecture - TransDiffuser is an end-to-end trajectory generation model that integrates multi-modal perception information to produce high-quality, diverse trajectories [6][7]. - The architecture includes a Scene Encoder for processing multi-modal data and a Denoising Decoder that utilizes the DDPM framework for trajectory generation [7][9]. - The model employs a multi-head cross-attention mechanism to fuse scene and motion features during the denoising process [9]. Group 4: Performance and Innovations - The model achieves a Predictive Driver Model Score (PDMS) of 94.85, outperforming existing methods [11]. - Key innovations include anchor-free trajectory generation and a multi-modal representation decorrelation optimization mechanism to enhance trajectory diversity and reduce redundancy [11][12]. Group 5: Limitations and Future Directions - The authors note challenges in fine-tuning the model, particularly the perception encoder [13]. - Future directions involve integrating reinforcement learning and referencing models like OpenVLA for further advancements [13].

出品丨虎嗅汽车组 作者丨肖漫 头图丨视觉中国 尽管账上有千亿现金，但理想还没有迎来躺着数钱的时候。 理想今年的销量目标是70万辆，比去年多了20万，而理想规划的新车型仅有理想i8和理想i6两款，且都在下半年发布，其他均为改款焕新。销量的重 担，依然落在L系列上。然而，L系列的销量疲势已经出现，近4个月都未能突破月销4万辆的瓶颈，不及去年下半年的表现。 一季度承压明显，进入四月，理想逐渐出牌。先是在上海车展发布MEGA家庭版车型，并在 5 月 8 日发布了 L 系列的智能焕新版（即L系列的2025 款）。 理想的打法是"加量不加价"，除了全系升级智能辅助驾驶硬件，L7/8 是全系标配魔毯双腔空悬、新增 52.3kWh 大电池，L9 则是用上了双枪双阀魔毯空 气悬架、十八点热石按摩等配置。 理想的刀法落得很精确，增配的目的显然是保量。理想手上的牌仅剩理想i8和理想i6，接下来的战，理想要怎么打？ 理想L系列，尚能战否？ 理想的第一道难关，是要守住增程车型的基本盘。 今年以来，理想L系列车型经历了不同程度的下滑，销量扛把子L6升至回到了去年刚上市的水平，L7的单月销量也都在一万以下。 数据来源： 车主之家 理想L系 ...

Core Viewpoint - Despite having over 100 billion in cash, Li Auto has not yet reached a point of effortless profitability, facing significant challenges in achieving its sales targets for the year [1]. Group 1: Sales Performance and Targets - Li Auto's sales target for the year is set at 700,000 units, an increase of 200,000 units from the previous year, but the new models, Li i8 and Li i6, are only set to launch in the second half of the year, placing the sales burden primarily on the L series [1][2]. - The L series has shown signs of sales fatigue, failing to exceed 40,000 units per month for the past four months, which is below the performance of the second half of last year [1][3]. - The L series' market share for range-extended products is projected to decline by 2.1% in Q4 2024, indicating increasing competition [6]. Group 2: Competitive Landscape - Li Auto faces growing competition from various manufacturers, including Huawei, which has launched multiple models that directly compete with the L series [6][7]. - The introduction of over 10 new mid-to-large SUVs this year, such as the AITO M8 and Lynk & Co 900, is intensifying competition in the market [7]. - The AITO M8 has already accumulated over 70,000 pre-orders, positioning it as a strong competitor against the L8 and L9 models [7]. Group 3: Product Strategy and Innovations - Li Auto's strategy includes enhancing the L series with new features while maintaining price stability, aiming to preserve sales volume [2][8]. - The L series is undergoing significant upgrades in intelligent driving capabilities, with the introduction of the new Thor-U chip and advanced laser radar systems [8][9]. - The new VLA (Vision Language Action) model aims to differentiate Li Auto's intelligent driving technology from competitors, focusing on advanced capabilities that mimic human-like understanding and reasoning [9][11]. Group 4: Electric Vehicle Strategy - Li Auto's upcoming pure electric models, the i8 and i6, are seen as critical variables for the company's performance this year, with conservative internal sales expectations of 50,000 units for both [15][16]. - The company is exploring new growth avenues through channel transformations and expanding into overseas markets, although the complexity of international markets poses challenges [16][17]. - The domestic market remains the primary focus, but increasing competition and uncertainties in the electric vehicle segment make achieving sales targets difficult [17].