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Qualitative Feature Assessment for Longitudinal and Lateral Control-features.

, , , , , and . VEHITS, page 115-122. SCITEPRESS, (2020)

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Logical Scenario Derivation by Clustering Dynamic-Length-Segments Extracted from Real-World-Driving-Data., , , , and . VEHITS, page 458-467. SciTePress, (2019)Approximate dynamic programming methods applied to far trajectory planning in optimal control., , and . Intelligent Vehicles Symposium, page 1085-1090. IEEE, (2014)Test scenario selection for system-level verification and validation of geolocation-dependent automotive control systems., , , , and . ICE/ITMC, page 203-210. IEEE, (2017)Estimating the Uniqueness of Test Scenarios derived from Recorded Real-World-Driving-Data using Autoencoders., , , , , and . Intelligent Vehicles Symposium, page 1860-1866. IEEE, (2018)Stochastic Forecasting of Vehicle Dynamics Using Sequential Monte Carlo Simulation., , , and . IEEE Trans. Intell. Veh., 2 (2): 111-122 (2017)A Process Reference Model for the Virtual Application of Predictive Control Features., , , and . IV, page 1759-1764. IEEE, (2020)A real-time capable enhanced dynamic programming approach for predictive optimal cruise control in hybrid electric vehicles., , , and . ITSC, page 1662-1667. IEEE, (2013)Driver state estimation for prediction of vehicle states within control systems., , , and . Intelligent Vehicles Symposium, page 1386-1391. IEEE, (2016)Qualitative Feature Assessment for Longitudinal and Lateral Control-features., , , , , and . VEHITS, page 115-122. SCITEPRESS, (2020)Map Attribute Validation using Historic Floating Car Data and Anomaly Detection Techniques., , , , and . VEHITS, page 504-514. SCITEPRESS, (2020)