Scenario-based approaches for the validation of highly automated driving functions are based on the search for safety-critical characteristics of driving scenarios using software-in-the-loop simulations. This search requires information about the shape and probability of scenarios in real-world traffic. The scope of this work is to develop a method that identifies redefined logical driving scenarios in field data, so that this information can be derived subsequently. More precisely, a suitable approach is developed, implemented and validated using a traffic scenario as an example. The presented methodology is based on qualitative modelling of scenarios, which can be detected in abstracted field data. The abstraction is achieved by using universal elements of an ontology represented by a domain model. Already published approaches for such an abstraction are discussed and concretised with regard to the given application. By examining a first set of test data, it is shown that the developed method is a suitable approach for the identification of further driving scenarios.

翻译：用于验证高度自动化驾驶功能的基于假设情况的方法,是以使用在环形模拟软件搜索驾驶假设情景的安全关键特征为基础。这种搜索需要关于现实世界交通中情景的形状和概率的信息。这项工作的范围是开发一种方法,确定外地数据中重新定义的逻辑驱动情景,以便随后得出这种信息。更准确地说,利用交通流量假设情景来开发、实施和验证一种适当的方法。所介绍的方法基于对情景的定性建模,可以在抽象的实地数据中探测到。抽象化是通过使用域模型所代表的本体学的通用元素来实现的。已经公布的关于这种抽象化的方法已经与给定的应用相关并得到了讨论和具体化。通过审查第一套测试数据,可以表明,开发的方法是确定进一步驱动情景的合适方法。