2024年中国汽车基础软件发展白皮书5.0

Industry Overview - The global automotive industry is undergoing a dual transformation in energy and intelligence, presenting significant opportunities for the Chinese automotive sector to transition from being large to strong [2] - The first half of this transformation focuses on energy transition, where the Chinese automotive industry has gained a competitive edge globally [2] - The second half, centered on intelligence, is becoming increasingly competitive, with software being the key driver for differentiation and innovation in vehicle applications [2] - The complexity of vehicle iteration, software development, and integration verification has significantly increased, leading to high development costs [2] - The adoption of an open software architecture, inspired by modular design principles like LEGO, could enhance development efficiency and product quality [2] Open Software Architecture - The open software architecture is designed to integrate seamlessly with AI large models, promoting a flexible and scalable framework for automotive software development [4] - Key components of the architecture include middleware, operating system foundations, toolchains, and ecosystem development [4] - The architecture aims to address challenges in multi-domain integration, data processing, and AI deployment, providing a unified development view for domain controllers [26] - The middleware layer includes standard middleware for MCUs and SoCs, vehicle basic services, and a unified communication framework for the entire vehicle [26] - The operating system layer focuses on balancing performance, safety, and third-party ecosystem compatibility, with various OS options for different vehicle domains [28] AI Large Models in Automotive Applications - AI large models are revolutionizing automotive software development by enabling data-driven approaches, particularly in autonomous driving and intelligent cockpit systems [13] - In intelligent cockpits, AI models enhance human-machine interaction through natural language processing, personalized recommendations, and driver behavior analysis [31] - In autonomous driving, AI models are used for environment perception, decision-making, and control execution, with end-to-end models offering global optimization and reduced reliance on manual rules [33] - AI models are also being deployed on the edge, reducing dependency on cloud computing and improving real-time performance [24] - Challenges for AI models in automotive applications include high computational resource demands, data processing and storage, and ensuring model stability and reliability [42] Cloud Applications - Cloud-based AI models are being used for vehicle security operations, performance prediction, fault diagnosis, and virtual testing [46] - The Vehicle Security Operation Center (VSOC) leverages AI to enhance threat detection, automated response, and data analysis, improving overall vehicle cybersecurity [47] - AI models in the cloud can predict vehicle performance, optimize energy management, and provide fault diagnosis and predictive maintenance [49] - Virtual testing and validation using AI models can simulate various driving scenarios, reducing the need for physical testing and accelerating development cycles [52] - Challenges in cloud applications include data privacy, model scalability, real-time performance requirements, and cross-platform compatibility [52] Middleware and Toolchains - The middleware layer in the open software architecture supports multi-domain integration, providing services like cross-core collaboration, power management, and health monitoring [54] - Standard middleware for MCUs and SoCs follows AUTOSAR Classic and Adaptive Platform standards, ensuring high performance, reliability, and security [56][60] - The toolchain for open software architecture includes classic tools for MCU and SoC development, as well as efficient development frameworks that support AI integration [29] - The ecosystem for open software architecture focuses on unified interfaces, communication protocols, and development standards, promoting collaboration and innovation across the industry [10]