地面车辆基于AI/ML系统的验证与确认

[中文适用范围]： 本文件旨在聚焦于车载及车外部署的人工智能/机器学习（AI/ML）系统，涵盖汽车系统开发生命周期中任何环节所采用的方法与工具。具体包括但不限于：用于参数识别、基于经典控制算法或神经网络的算法校准、系统级建模与验证，以及数据流程自动化管线（如自动标注与注释、数据质量检查等）的AI/ML系统。 此外，随着生成式人工智能（GenAI）能力的持续突破，利用其生成合成数据已不再局限于此，代码编写、测试场景构建及基准测试等多类开发 artifacts 均可借助GenAI工具完成，因而必须对这类“生成式”开发步骤实施额外的验证。生成式方法面临的核心挑战在于“可信落地”（grounding），尤其是在所涉数据、场景与测试均用于AI功能与产品开发的背景下。详见后文。 [外文原描述]： This document intends to focus on AI/ML systems deployed on board and/or off board the vehicles, including the methods and tools used anywhere in the life cycle of automotive system development. This includes, for instance, AI/ML systems used in the identification of parameters, calibration of classical or neural network-based control algorithms, system level modeling and validation, data process automation pipeline such as automated labeling and annotation, data quality checks, etc. Furthermore, with the continued success of Generative AI (GenAI) capabilities, it is becoming a common practice to leverage these capabilities beyond just generating synthetic data. Multiple artifacts such as code, testing scenarios, and benchmarks could be developed using GenAI tools, necessitating the additional verification of these “generative” development steps. The fundamental challenge with generative methods is grounding, especially if data, scenes, and tests are used for the development of AI-enabled products and features.AI and ML systems have been the subject of several national and international standards and guideline documents. A brief selection of these are given in Section 2. One, ISO PAS 8800:2024, focuses on safety over the entire life cycle of AI development and deployment.This document is intended to serve the following purpose:a. The document is an information report with no mandatory requirements.b. The focus of the document is only on V&V of the development life cycle of AI-based components or systems.c. The V&V methods are general in nature. The methods discussed include, but are not restricted to, safety requirements or properties.