LPV-based autonomous vehicle control using the results of big data analysis on lateral dynamics

Daniel Fenyes, Balazs Nemeth, Peter Gaspar

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

Abstract

The paper presents a new big data based control design for autonomous vehicles. The main contribution of this work is the longitudinal velocity optimization process, which is based on the approximation of the reachability sets of a passenger vehicle by using a machine-learning approach. The data, which is used for the approximation, is provided by the high-fidelity car simulation software, CarSim. The approximation is performed by applying a well-known decision tree algorithm, C4.5. The reachability sets are computed for different longitudinal velocities. Moreover, a LPV technique based lateral control design is proposed, which is used to guarantee the trajectory tracking of the vehicle. To enhance the capability of the LPV controller, the control scheme is extended with the longitudinal velocity optimization process. Thus, the stable and safe motion of the vehicle is guaranteed.

Original languageEnglish
Title of host publication2020 American Control Conference, ACC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2250-2255
Number of pages6
ISBN (Electronic)9781538682661
DOIs
Publication statusPublished - Jul 2020
Event2020 American Control Conference, ACC 2020 - Denver, United States
Duration: Jul 1 2020Jul 3 2020

Publication series

NameProceedings of the American Control Conference
Volume2020-July
ISSN (Print)0743-1619

Conference

Conference2020 American Control Conference, ACC 2020
CountryUnited States
CityDenver
Period7/1/207/3/20

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Fenyes, D., Nemeth, B., & Gaspar, P. (2020). LPV-based autonomous vehicle control using the results of big data analysis on lateral dynamics. In 2020 American Control Conference, ACC 2020 (pp. 2250-2255). [9147548] (Proceedings of the American Control Conference; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC45564.2020.9147548