A Framework for Robust Remote Driving Strategy Selection

Klöppel-Gersdorf, MichaelMichaelKlöppel-GersdorfOtto, ThomasThomasOtto2022-11-032022-11-032022https://publica.fraunhofer.de/handle/publica/42823710.5220/0011088900003191In this paper, a framework for assisting Connected Vehicle (CV) is proposed, with the goal of generating optimal parameters for existing driving functions, e.g., parking assistant or Adaptive Cruise Control (ACC), to allow the CV to move autonomously in restricted scenarios. Such scenarios encompass yard automation as well as valet parking. The framework combines Model predictive control (MPC) with particle filter estimators and robust optimization.endriving strategy selectionyard automationconnected vehiclerobust optimizationV2XA Framework for Robust Remote Driving Strategy Selectionconference paper