用生成式AI加速汽车软件开发全流程，从需求到代码
Survey of GenAI for Automotive Software Development: From Requirements to Executable Code
- 结合大模型、检索增强生成等技术，覆盖需求到编码全流程
- 提出通用的生成式AI辅助汽车软件开发工作流
- 调研行业伙伴使用情况，验证工具落地可行性
生成式人工智能（GenAI）旨在通过减少人工干预和处理复杂流程所需的努力，革新众多工业领域。汽车软件开发因其需求繁多、标准化严格，被视为GenAI的重要应用方向。本文系统探讨了GenAI在汽车软件开发各阶段的应用，重点涵盖需求管理、合规性与代码生成。所涉前沿技术包括大语言模型（LLMs）、检索增强生成（RAG）、视觉语言模型（VLMs），以及代码生成中的提示工程方法。基于文献综述，我们提炼出一套通用的GenAI辅助汽车软件开发工作流。最后，还总结了针对行业合作伙伴开展的问卷调查结果，揭示其日常工作中实际使用的GenAI工具类型。
原文摘要 · Abstract (English)
Adoption of state-of-art Generative Artificial Intelligence (GenAI) aims to revolutionize many industrial areas by reducing the amount of human intervention needed and effort for handling complex underlying processes. Automotive software development is considered to be a significant area for GenAI adoption, taking into account lengthy and expensive procedures, resulting from the amount of requirements and strict standardization. In this paper, we explore the adoption of GenAI for various steps of automotive software development, mainly focusing on requirements handling, compliance aspects and code generation. Three GenAI-related technologies are covered within the state-of-art: Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Vision Language Models (VLMs), as well as overview of adopted prompting techniques in case of code generation. Additionally, we also derive a generalized GenAI-aided automotive software development workflow based on our findings from this literature review. Finally, we include a summary of a survey outcome, which was conducted among our automotive industry partners regarding the type of GenAI tools used for their daily work activities.
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