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Logical Scenario Derivation by Clustering Dynamic-Length-Segments Extracted from Real-World-Driving-Data.

, , , , и . VEHITS, стр. 458-467. SciTePress, (2019)

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Unveiling Objects with SOLA: An Annotation-Free Image Search on the Object Level for Automotive Data Sets., , и . CoRR, (2023)Capturing the Variety of Urban Logical Scenarios from Bird-view Trajectories., , , , и . VEHITS, стр. 471-480. SCITEPRESS, (2021)Reducing Computer Vision Dataset Size via Selective Sampling., , , , , и . ITSC, стр. 1422-1428. IEEE, (2023)Logical Scenario Derivation by Clustering Dynamic-Length-Segments Extracted from Real-World-Driving-Data., , , , и . VEHITS, стр. 458-467. SciTePress, (2019)Test scenario selection for system-level verification and validation of geolocation-dependent automotive control systems., , , , и . ICE/ITMC, стр. 203-210. IEEE, (2017)Estimating the Uniqueness of Test Scenarios derived from Recorded Real-World-Driving-Data using Autoencoders., , , , , и . Intelligent Vehicles Symposium, стр. 1860-1866. IEEE, (2018)A Taxonomy and Survey on Validation Approaches for Automated Driving Systems., , , и . ISSE, стр. 1-8. IEEE, (2020)A Process Reference Model for the Virtual Application of Predictive Control Features., , , и . IV, стр. 1759-1764. IEEE, (2020)A Driving Scenario Representation for Scalable Real-Data Analytics with Neural Networks., , , , и . IV, стр. 2215-2222. IEEE, (2019)Qualitative Feature Assessment for Longitudinal and Lateral Control-features., , , , , и . VEHITS, стр. 115-122. SCITEPRESS, (2020)