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With Regulation UNECE R157 on Automated Lane-Keeping Systems, the firstframework for the introduction of passenger cars with Level 3 systems hasbecome available in 2020. In accordance with recent research projects includingacademia and the automotive industry, the Regulation utilizes scenario basedtesting for the safety assessment. The complexity of safety validation ofautomated driving systems necessitates system-level simulations. TheRegulation, however, is missing the required parameterization necessary fortest case generation. To overcome this problem, we incorporate the exposure andconsider the heterogeneous behavior of the traffic participants by extractingconcrete scenarios according to Regulation's scenario definition from theestablished naturalistic highway dataset highD. We present a methodology tofind the scenarios in real-world data, extract the parameters for modeling thescenarios and transfer them to simulation. In this process, more than 340scenarios were extracted. OpenSCENARIO files were generated to enable anexemplary transfer of the scenarios to CARLA and esmini. We compare thetrajectories to examine the similarity of the scenarios in the simulation tothe recorded scenarios. In order to foster research, we publish the resultingdataset called ConScenD together with instructions for usage with bothsimulation tools. The dataset is available online athttps://www.levelXdata.com/scenarios.

The ConScenD Dataset: Concrete Scenarios from the highD Dataset According to ALKS Regulation UNECE R157 in OpenX