Scenario generation is one of the essential steps in scenario-based testing and, therefore, a significant part of the verification and validation of driver assistance functions and autonomous driving systems. However, the term scenario generation is used for many different methods, e.g., extraction of scenarios from naturalistic driving data or variation of scenario parameters. This survey aims to give a systematic overview of different approaches, establish different categories of scenario acquisition and generation, and show that each group of methods has typical input and output types. It shows that although the term is often used throughout literature, the evaluated methods use different inputs and the resulting scenarios differ in abstraction level and from a systematical point of view. Additionally, recent research and literature examples are given to underline this categorization.
翻译:情景生成是基于情景的测试的一个重要步骤,因此是驱动辅助功能和自动驾驶系统验证和确认的一个重要部分。然而,情景生成一词用于许多不同的方法,例如从自然驾驶数据中提取情景或变化情景参数。本综述旨在系统地介绍不同方法,建立情景获取和生成的不同类别,并表明每组方法具有典型的输入和输出类型。它表明,尽管这个术语经常出现在文献中,但评估的方法使用不同的输入,由系统的观点来看,生成的情景在抽象层面和实际条件中都有所不同。此外,列举了最新的研究和文献例子来强调这种分类。