  With Regulation UNECE R157 on Automated Lane-Keeping Systems, the first
framework for the introduction of passenger cars with Level 3 systems has
become available in 2020. In accordance with recent research projects including
academia and the automotive industry, the Regulation utilizes scenario based
testing for the safety assessment. The complexity of safety validation of
automated driving systems necessitates system-level simulations. The
Regulation, however, is missing the required parameterization necessary for
test case generation. To overcome this problem, we incorporate the exposure and
consider the heterogeneous behavior of the traffic participants by extracting
concrete scenarios according to Regulation's scenario definition from the
established naturalistic highway dataset highD. We present a methodology to
find the scenarios in real-world data, extract the parameters for modeling the
scenarios and transfer them to simulation. In this process, more than 340
scenarios were extracted. OpenSCENARIO files were generated to enable an
exemplary transfer of the scenarios to CARLA and esmini. We compare the
trajectories to examine the similarity of the scenarios in the simulation to
the recorded scenarios. In order to foster research, we publish the resulting
dataset called ConScenD together with instructions for usage with both
simulation tools. The dataset is available online at
https://www.levelXdata.com/scenarios.
