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  4. A Framework for Robust Remote Driving Strategy Selection
 
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2022
Conference Paper
Title

A Framework for Robust Remote Driving Strategy Selection

Abstract
In 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.
Author(s)
Klöppel-Gersdorf, Michael  
Fraunhofer-Institut für Verkehrs- und Infrastruktursysteme IVI  
Otto, Thomas  
Fraunhofer-Institut für Verkehrs- und Infrastruktursysteme IVI  
Mainwork
Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2022  
Project(s)
Leitstelle zur Fernüberwachung und -steuerung von automatisierten Fahrzeugen im öffentlichen Personennahverkehr mittels 5G-Funknetzwerken  
Funder
Bundesministerium für Verkehr und digitale Infrastruktur -BMVI-, Deutschland  
Conference
International Conference on Vehicle Technology and Intelligent Transport Systems 2022  
Open Access
DOI
10.5220/0011088900003191
Language
English
Fraunhofer-Institut für Verkehrs- und Infrastruktursysteme IVI  
Keyword(s)
  • driving strategy selection

  • yard automation

  • connected vehicle

  • robust optimization

  • V2X

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