Scenario-based approaches have been receiving a huge amount of attention in research and engineering of automated driving systems. Due to the complexity and uncertainty of the driving environment, and the complexity of the driving task itself, the number of possible driving scenarios that an ADS or ADAS may encounter is virtually infinite. Therefore it is essential to be able to reason about the identification of scenarios and in particular critical ones that may impose unacceptable risk if not considered. Critical scenarios are particularly important to support design, verification and validation efforts, and as a basis for a safety case. In this paper, we present the results of a systematic literature review in the context of autonomous driving. The main contributions are: (i) introducing a comprehensive taxonomy for critical scenario identification methods; (ii) giving an overview of the state-of-the-art research based on the taxonomy encompassing 86 papers between 2017 and 2020; and (iii) identifying open issues and directions for further research. The provided taxonomy comprises three main perspectives encompassing the problem definition (the why), the solution (the methods to derive scenarios), and the assessment of the established scenarios. In addition, we discuss open research issues considering the perspectives of coverage, practicability, and scenario space explosion.
翻译:由于驾驶环境的复杂性和不确定性,以及驾驶任务本身的复杂性,ADS或ADAS可能遇到的可能的驾驶场景数量几乎是无限的,因此,必须能够说明如何确定假设情景,特别是如果不予考虑可能构成不可接受的风险的关键情景;关键情景情景对于支持设计、核查和验证工作特别重要,是安全案例的基础。本文介绍了在自主驱动背景下系统文献审查的结果。主要贡献是:(一) 采用关键情景识别方法的全面分类;(二) 概述2017年至2020年期间基于包含86份文件的分类学的最新研究;(三) 查明开放的问题和进一步研究的方向。提供的分类包括问题定义(原因)、解决方案(预测方法)和既定情景评估等三个主要观点。此外,我们讨论了基于涵盖范围、可行性、爆炸情景和空间设想的公开研究问题。