智驾软硬件持续迭代，robotaxi未来已来

Summary of Key Points from the Conference Call Industry Overview - The conference call discusses the autonomous driving (AD) industry, focusing on various companies and their technological advancements in the sector. Key Companies and Market Share - Momenta holds a leading position in the third-party autonomous driving market with a market share of 55%, while Huawei has a 25% share [1][3]. - DJI excels in low-computing power chip solutions but is shifting towards mid-to-high computing power solutions due to market demand [1][5]. - Horizon Robotics has developed self-researched hardware-software integrated solutions, currently in mass production with Chery's models, but faces challenges in NPU computing power and algorithm upgrades [1][6]. Technological Routes and Developments - The AD industry is divided into three main technological routes: 1. End-to-End Algorithms: Gaining traction since Tesla's AI Day in 2021, with companies like Momenta and Tesla implementing these algorithms in production vehicles [2]. 2. Vision Language Action (VLA) Models: Used by companies like Li Auto and XPeng, requiring high computing power (minimum 500 TOPS) and significant resources for training [2]. 3. World Models: Developed by companies like Huawei and Momenta, capable of understanding and predicting environmental changes [2]. Performance and Capabilities of Key Players - Momenta offers two product lines: a cost-effective single Orin X solution and a high-end dual Orin X solution, showcasing strong engineering capabilities [3]. - DJI has strong engineering capabilities but relatively weaker algorithm capabilities, allowing it to effectively implement complex algorithms in practical scenarios [3]. - Horizon Robotics is in the second tier of the industry, with its HSD and G6P series solutions providing decent user experience but needing more vehicle validation [6]. Market Trends and Shifts - The market is shifting from low-computing power chips to mid-to-high computing power solutions, prompting companies like DJI to develop new chip solutions [4][5]. - The demand for fusion perception routes combining Lidar and other sensors is expected to grow due to regulatory requirements and the need for handling complex scenarios [12]. Challenges and Future Outlook - The differences in autonomous driving capabilities among companies are primarily determined by data, computing power, and algorithms [8][9]. - Long-term, the accumulation of data will be crucial for competitive advantage, with a critical mass of road testing data needed to trigger significant improvements [10]. - The Robot Taxi market is seen as a positive growth area, with profitability dependent on vehicle efficiency, cost management, and competitive pricing [18][19]. Conclusion - Companies transitioning from L2+ to L4 levels of autonomous driving have a natural advantage due to lower resource investment and existing experience in mass production [20].