Core Viewpoint - The article discusses the advancements and potential of Horizon Robotics' HSD (Highway Smart Driving) system, emphasizing its transition from testing to near mass production, and its implications for the smart automotive industry in China [1][4][36]. Group 1: Technological Advancements - Horizon Robotics has launched its self-developed computing hardware, the J6P, and the UniAD software, marking significant milestones in autonomous driving technology [2][4]. - The HSD system features a one-stage end-to-end architecture, which improves the driving experience by integrating various functionalities without relying on traditional rule-based systems [19][36]. - Key innovations include dense modal information processing, joint optimization of lateral and longitudinal control, and a robust safety verification module to ensure safe vehicle operation [20][21][24]. Group 2: Performance and User Experience - The latest version of HSD demonstrates improved speed control and smoother driving experiences, particularly in complex scenarios like traffic lights and merging [6][10]. - The system's ability to navigate through obstacles and make real-time decisions showcases its advanced cognitive capabilities, allowing it to handle various driving conditions effectively [11][36]. - Despite its advancements, some issues were noted, such as misidentifying stationary vehicles, indicating areas for further refinement [13][36]. Group 3: Industry Implications - Horizon Robotics aims to establish a comprehensive solution for the automotive industry, moving away from isolated implementations for specific manufacturers [41]. - The company's strategy focuses on a gradual approach to autonomous driving, with a clear timeline for achieving hands-off and eyes-off driving capabilities [37][39]. - The competitive landscape suggests that companies failing to keep pace with these advancements may risk obsolescence in the rapidly evolving smart automotive sector [37][39].

Core Insights - The automotive industry is experiencing a shift from traditional E/E architecture to a centralized architecture, enabling companies to take control of software development and redefine vehicle core functionalities [1] - The trend towards self-developed chips is driven by the desire to capture profits from the high-margin ends of the "smile curve" (chips and algorithms) [1] - The "smart driving equality" movement initiated by BYD presents both opportunities for automakers and a historic chance for smart driving suppliers [2] Industry Dynamics - In the context of intensified competition and the saturation of smart driving solutions, automakers prioritize getting their products to market rather than focusing solely on self-development [2][3] - The window for automakers to capitalize on this trend is limited to approximately two years [3] Competitive Landscape - NVIDIA currently dominates the smart driving market with a 45.4% share, primarily due to its Orin-X chip, which is highly regarded for its AI acceleration capabilities [4] - New entrants in the market, such as Horizon and Black Sesame, have made significant advancements in chip capabilities, allowing them to compete with NVIDIA's offerings [5][8] - The validation timeline for domestic chips is only 2-3 years behind NVIDIA, indicating a narrowing gap in competition [6][8] Chip Development and Cost Analysis - The development of chips is a long-term endeavor, with significant time required for accumulation and iteration [10] - Companies need to achieve a minimum production scale and possess strong iteration capabilities to make self-developed chips economically viable [11] - Cost analysis shows that the manufacturing costs of chips vary significantly based on technology nodes, with the total cost for advanced chips reaching up to 3915 yuan [12] Data and Talent Acquisition - Automakers have a substantial advantage in data acquisition for training smart driving systems, with companies like Tesla and Huawei leading in vehicle deployment [15] - The scale of talent and internal collaboration is crucial for the development of advanced smart driving technologies, with major players employing large teams dedicated to this field [16] Conclusion - BYD, while relying on external suppliers for chips and algorithms, is actively working on self-developed smart driving solutions, indicating a trend among leading automakers to balance self-development with external sourcing [17]

Core Insights - The optimistic forecast for the penetration rate of intelligent driving (NOA) suggests an annual growth of 5%, reaching 55% for highways and 25% for urban areas by 2030 [1] - The increase in penetration rates is attributed to competitive pricing strategies among automakers, which have driven down the costs of intelligent driving systems [1] - The domestic production of key components, such as lidar and chips, has significantly contributed to cost reductions in intelligent driving hardware [1] Summary by Categories Intelligent Driving Chip Market - Intelligent driving chips are categorized by computing power: low (<30 TOPS), medium (30-150 TOPS), and high (>150 TOPS) [2] - The domestic replacement rate for low-power chips is high, with products like Horizon J2 and J3 gaining traction due to their cost-effectiveness and local service capabilities [3][4] - Horizon J2/J3 chips are priced at $50 each, significantly lower than Mobileye's EyeQ4, which enhances their market appeal [5] Medium-Power Chips - Medium-power chips support more complex driving algorithms, with products like NVIDIA Xavier and Horizon J5 leading the market [6] - Horizon J5 has achieved a market share of 5.1% with a projected shipment of 26.9 million units by 2024 [6][7] - The Horizon J6 series targets both urban and highway NOA applications, with J6M and J6E designed for different driving environments [7] High-Power Chips - High-power chips are essential for complex urban driving scenarios, with products like NVIDIA Orin-X and Tesla HW series dominating the market [9][10] - NVIDIA's Orin-X holds a 39.8% market share, while Tesla's FSD accounts for 25.1% [11] - The Horizon J6P, with a computing power of 560 TOPS, is positioned as a strong competitor to NVIDIA's offerings [11][12] Emerging Technologies - The NIO-developed Shenji NX9031 chip, with a performance equivalent to four flagship chips at 1000 TOPS, represents a significant advancement in domestic chip technology [13] - The A2000 series from Black Sesame targets various levels of autonomous driving needs, with performance metrics that could rival NVIDIA's Thor chip [12]