Road surface estimation based LPV control design for autonomous vehicles

Dániel Fényes, Balázs Németh, Péter Gáspár, Zoltán Szabó

Research output: Contribution to journalConference article

Abstract

The paper proposes a new road surface estimation algorithm for autonomous vehicles using a machine-learning based method, which is in cooperation with the lateral control of the vehicle. The algorithm uses large datasets, which can be collected e.g. from the on-board sensors of the vehicle, or it also can be provided by vehicle dynamic simulation softwares. The result of the surface estimation is built-in the lateral control system as a scheduling parameter. Furthermore, the lateral control design is based on the Linear Parameter Varying (LPV) method, which guarantees the safe motion of the vehicle against varying parameters of the system. Finally, a comprehensive simulation is presented to show the efficiency and the operation of the proposed control system.

Original languageEnglish
Pages (from-to)120-125
Number of pages6
JournalIFAC-PapersOnLine
Volume52
Issue number28
DOIs
Publication statusPublished - Jan 1 2019
Event3rd IFAC Workshop on Linear Parameter Varying Systems, LPVS 2019 - Eindhoven, Netherlands
Duration: Nov 4 2019Nov 6 2019

Keywords

  • autonomous vehicle systems
  • big data analysis
  • road surface estimation

ASJC Scopus subject areas

  • Control and Systems Engineering

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