A Framework for Robust Remote Driving Strategy Selection

Michael Kloeppel-Gersdorf,Thomas Otto

VEHITS: PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON VEHICLE TECHNOLOGY AND INTELLIGENT TRANSPORT SYSTEMS（2022）

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摘要

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.

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关键词

Driving Strategy Selection, Yard Automation, Particle Filter, Robust Optimization, Valet Parking, V2X, IEEE 802.11p

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