拆解华为乾崑智驾ADS 4：世界模型乱战，“尖子生”如何闯关？

Core Insights - The article discusses the evolution of autonomous driving technology, emphasizing the transition from traditional models to world models that enable vehicles to predict and understand their environment rather than merely reacting to it [2][4][5]. Group 1: World Model Concept - The world model provides vehicles with the ability to anticipate and reason about their surroundings, moving beyond simple reactive capabilities [4][11]. - This model integrates vast amounts of multimodal data, including real-world driving scenarios and traffic rules, to create a dynamic and inferential digital representation of the traffic world [2][4]. - Companies like Huawei, XPeng, and SenseTime are recognizing the world model as essential for achieving true autonomous driving by 2025 [4][12]. Group 2: Technological Advancements - Huawei's ADS 4 system, launched in April 2023, marks a significant advancement in high-level driving assistance, relying on its self-developed WEWA architecture [4][12]. - The WEWA architecture consists of a cloud-based world engine (WE) for data training and scenario generation, and a vehicle-based world behavior model (WA) for real-time environmental reasoning and decision-making [4][12][21]. - The world model addresses the limitations of traditional end-to-end models, which often mimic human behavior without understanding the underlying physics of driving [6][11]. Group 3: Market Position and Competition - Huawei's market share in the domestic pre-installed advanced driving domain is reported at 79.0%, maintaining its position as a leading supplier [12][14]. - The company has successfully deployed its driving system in over 1 million vehicles across various manufacturers, enhancing its data collection and model training capabilities [24][25]. - The competitive landscape is shifting, with other companies like NIO and XPeng also exploring world models, but Huawei's approach remains distinct due to its focus on specialized behavior models rather than language-based models [18][19][22].