拆解华为乾崑智驾ADS 4：世界模型乱战，尖子生如何闯关？

Core Viewpoint - The article discusses the evolution of autonomous driving technology, emphasizing the shift from traditional end-to-end models to world models that enable vehicles to understand and predict their environment more effectively [2][4][8]. Group 1: World Model Development - The world model allows vehicles to possess predictive capabilities, moving beyond mere reactive responses to real-time stimuli [2][3]. - Huawei's ADS 4 system, launched in April 2023, represents a significant advancement in high-level driving assistance, relying on the self-developed WEWA architecture [3][4]. - By 2025, several tech companies, including Xiaopeng and SenseTime, are expected to adopt world models as a crucial step towards achieving fully autonomous driving [4][8]. Group 2: Challenges in Autonomous Driving - The industry has recognized that traditional end-to-end models, which rely heavily on human driving data, often lead to suboptimal decision-making and do not truly understand physical laws [6][7]. - Research indicates that low-precision training can limit the effectiveness of models, highlighting the need for improved generalization capabilities in real-world scenarios [7]. Group 3: Competitive Landscape - Huawei's market share in the domestic pre-installed auxiliary driving domain is reported at 79.0%, maintaining its position as a leading supplier [9]. - The company differentiates itself by focusing on a more fundamental approach to driving, emphasizing spatial reasoning over merely following trends [9][10]. Group 4: Technological Innovations - Huawei's world model architecture integrates a cloud-based world engine and a vehicle-side behavior model, enhancing real-time reasoning and decision-making capabilities [12][14]. - The company has developed a unique approach to generating training scenarios, focusing on extreme cases that are often difficult to capture in real-world data [13][14]. Group 5: Implementation and Future Prospects - Huawei's intelligent driving system has been deployed in over 1 million vehicles across various manufacturers, facilitating rapid feedback and continuous improvement of the system [15]. - The integration of a large-scale real vehicle fleet supports the evolution of the driving system, paving the way for higher levels of autonomous driving capabilities [15].