L4产业链跟踪系列第三期-头部Robotaxi公司近况跟踪（技术方向）

Summary of Conference Call Company and Industry - The conference call primarily discusses advancements in the autonomous driving industry, specifically focusing on a company involved in Level 4 (L4) autonomous driving technology. Key Points and Arguments 1. Technological Framework: The company has a modular architecture for its autonomous driving system, which includes perception, prediction, control, and planning. This framework has evolved to incorporate advanced techniques like reinforcement learning and world models, although the core structure remains intact [1][2][3]. 2. Transition to Large Models: The industry is shifting from CNN architectures to transformer-based models. The company is gradually replacing its existing models with these new frameworks, which may take longer due to the high baseline performance of their current systems [3][4]. 3. Data Utilization: The company emphasizes the importance of both real and simulated data for model training. While real data is primarily used, there is a plan to increasingly incorporate simulated data to address data shortages, especially for control models [8][9][10]. 4. Learning Techniques: Imitation learning has been used for scenarios where rule-based approaches fail, while reinforcement learning is applied in end-to-end (E2E) models. The proportion of reinforcement learning used is not significant, indicating a cautious approach to its implementation [11][12]. 5. Operational Deployment: The company has deployed several autonomous vehicles in major cities like Beijing and Guangzhou, with plans to expand in Shenzhen and Shanghai. The current fleet consists of a few hundred vehicles [14][21]. 6. Cost Structure: The cost of vehicles includes hardware components such as multiple radars and cameras, with estimates suggesting that the total cost could be reduced to around 200,000 yuan [15][19]. 7. Computational Resources: The company is facing challenges with computational capacity, particularly with the integration of various models across different chips. There is a focus on optimizing the use of existing resources while planning for future upgrades [19][20]. 8. Profitability Goals: The company aims to achieve a break-even point by deploying a fleet of over 10,000 vehicles by 2027 or 2028. Current estimates suggest that achieving profitability may require a fleet size closer to 100,000 vehicles [26]. 9. Market Positioning: The company acknowledges competition from other players in the autonomous driving space, particularly in terms of regulatory approvals and operational capabilities. It aims to maintain a competitive edge by leveraging its faster acquisition of commercial licenses [27][28]. Other Important Content - The discussion highlights the ongoing evolution of the autonomous driving technology landscape, with a focus on the balance between technological advancement and operational scalability. The company is committed to addressing challenges in data acquisition, model training, and fleet management to enhance its market position [22][23][30].