Enhancement of autonomous vehicle control via the contributions of big data analysis

Daniel Fenyes, Balazs Nemeth, Peter Gaspar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The paper presents a novel road surface estimation method using a big-data analysis approach. The generation of the estimation model is based on the pace regression technique, which utilizes the large amount of data provided by the sensors of autonomous vehicles. The result of the estimation is used in the lateral control design of vehicles. The control design is based on the LPV method, in which the result of the road surface estimation is used as a scheduling variable. The effectiveness and the performances of the proposed control system are examined through a comprehensive simulation which is conducted in a vehicle simulation environment.

Original languageEnglish
Title of host publicationINES 2019 - IEEE 23rd International Conference on Intelligent Engineering Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages319-324
Number of pages6
ISBN (Electronic)9781728112138
DOIs
Publication statusPublished - Apr 2019
Event23rd IEEE International Conference on Intelligent Engineering Systems, INES 2019 - Godollo, Hungary
Duration: Apr 25 2019Apr 27 2019

Publication series

NameINES 2019 - IEEE 23rd International Conference on Intelligent Engineering Systems, Proceedings

Conference

Conference23rd IEEE International Conference on Intelligent Engineering Systems, INES 2019
CountryHungary
CityGodollo
Period4/25/194/27/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Mechanical Engineering

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  • Cite this

    Fenyes, D., Nemeth, B., & Gaspar, P. (2019). Enhancement of autonomous vehicle control via the contributions of big data analysis. In INES 2019 - IEEE 23rd International Conference on Intelligent Engineering Systems, Proceedings (pp. 319-324). [9109434] (INES 2019 - IEEE 23rd International Conference on Intelligent Engineering Systems, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INES46365.2019.9109434