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].

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].