3 6 Ke·2025-08-11 23:08Core Insights - The article highlights the advancements in intelligent driving technology, specifically focusing on the VLA (Vision-Language-Action) model, which integrates visual perception, language understanding, and action decision-making [4][6][16] - Both Li Auto's i8 and Xpeng's P7 are utilizing VLA technology to enhance their autonomous driving capabilities, marking a shift from traditional rule-based algorithms to AI-driven systems [1][3][16] Group 1: VLA Technology Overview - VLA stands for Vision-Language-Action, which combines visual perception, language understanding, and action decision-making into a unified system [4] - The model processes data from cameras and LiDAR to recognize road conditions, traffic signs, and the positions of other vehicles and pedestrians [4][8] - VLA improves upon traditional models by creating a closed-loop system that enhances adaptability to various driving scenarios [7][10] Group 2: Practical Applications of VLA - VLA can analyze complex traffic situations, such as determining whether to stop for pedestrians or proceed through a green light, mimicking human-like decision-making [8][10] - The technology allows for smoother driving experiences, including automatic risk assessment, stable acceleration and deceleration, and efficient maneuvering in tight spaces [10] - VLA enables continuous communication with the vehicle, allowing it to execute multiple driving commands in sequence [10] Group 3: Psychological Basis of VLA - The functioning of VLA aligns with human cognitive processes, where information is perceived, understood, and acted upon in a structured manner [11][15] - The model aims to replicate human-like perception and decision-making in driving, enhancing the overall driving experience [15][16] Group 4: Future Prospects and Challenges - The introduction of VLA signifies a transition from mere functional enhancements to a more integrated cognitive approach in intelligent driving [16] - Current limitations include the computational power required to run such extensive AI models, indicating a clear area for future technological advancements [16]