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Estimating the Uniqueness of Test Scenarios derived from Recorded Real-World-Driving-Data using Autoencoders., , , , , and . Intelligent Vehicles Symposium, page 1860-1866. IEEE, (2018)Classification of Automotive Electric/Electronic Features and the Consequent Hierarchization of the Logical System Architecture - From Functional Chains to Functional Networks., , and . SMARTGREENS/VEHITS (Selected Papers), volume 921 of Communications in Computer and Information Science, page 229-255. Springer, (2017)SceML - A Graphical Modeling Framework for Scenario-based Testing of Autonomous Vehicles., , , and . CoRR, (2021)Model based scenario specification for development and test of automated driving functions., , and . Intelligent Vehicles Symposium, page 1149-1155. IEEE, (2016)Exploring the Range of Possible Outcomes by means of Logical Scenario Analysis and Reduction for Testing Automated Driving Systems., , and . CoRR, (2023)Integrating Static Code Analysis Toolchains., , , , , , and . CoRR, (2024)Logical Scenario Derivation by Clustering Dynamic-Length-Segments Extracted from Real-World-Driving-Data., , , , and . VEHITS, page 458-467. SciTePress, (2019)Test scenario selection for system-level verification and validation of geolocation-dependent automotive control systems., , , , and . ICE/ITMC, page 203-210. IEEE, (2017)A Taxonomy and Systematic Approach for Automotive System Architectures - From Functional Chains to Functional Networks., , and . VEHITS, page 90-101. SciTePress, (2017)Model-based Variant Management in Automotive Systems Engineering., , , and . ISSE, page 1-7. IEEE, (2019)