From Functional to Logical Scenarios: Detailing a KeywordBased Scenario Description for Execution in a Simulation Environment Scenariobased development and test processes are a promising approach for verifying and validating automated driving functions. For this purpose, scenarios have to be generated during the development process in a traceable manner. In early development stages, the operating scenarios of the item to be developed are usually described in an abstract, linguistic way.Within the scope of a simulationassisted test process, these linguistically described scenarios have to be transformed into a state space representation and converted into data formats which can be used with the respective simulation environment. Currently, this step of detailing scenarios takes a considerable manual effort. Furthermore, a standardized interpretation of the linguistically described scenarios and a consistent transformation into the data formats are not guaranteed due to multiple authors as well as many constraints between the scenario parameters. In this paper, the authors present an approach to automatically detail a keywordbased scenario description for execution in a simulation environment and provide a basis for test case generation. As a first step, the keywordbased description is transformed into a parameter space representation. At the same time, constraints regarding the selection and combination of parameter values are documented for the following process steps (e. g. evolutionary or stochastic test methods). As a second step, the parameter space representation is converted into data formats required by the simulation environment. As an example, the authors use scenarios on German freeways and convert them into the data formats OpenDRIVE (description of the road) and OpenSCENARIO (description of traffic participants and environmental conditions) for execution in the simulation environment Virtual Test Drive.

Comparing two systematic approaches for testing automated driving functions Thoroughly validating and verifying automated or autonomous driving functions is inevitable for assuring to meet quality criteria for safetycritical systems. In this paper, we discuss two system testing techniques that have been already used for detecting critical situations for the automated emergency braking function based on vehicle simulations. In particular, we introduce combinatorial testing and searchbased testing techniques and compare them. Whereas the first is for identifying interactions of parameters that lead to harmful situations considering predefined value domains, the latter is for finding parameter values that cause such critical situations. We discuss the underlying foundations behind the methods as well as their potential application areas. In addition, we summarize the results obtained when using these methods for testing automated emergency braking.