A novel big-data-based estimation method of side-slip angles for autonomous road vehicles

Dániel Fényes, Balázs Németh, P. Gáspár

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

Abstract

In the paper a novel side-slip estimation algorithm, which is based on big data approaches, is proposed. The idea of the estimation is based on the availability of a large amount of information of the autonomous vehicles, e.g. yaw-rate, accelerations and steering angles. The significant number of signals are processed through big data approaches to generate a simplified rule for the side-slip estimation using the onboard signals of the vehicles. Thus, a subset selection method for time-domain signals is proposed, by which the attributes are selected based on their relevance. Furthermore, a linear regression using the Ordinary Least Squares (OLS) method is applied to derive a relationship between the attributes and the estimated signal. The efficiency of the estimation is presented through several CarSim simulation examples, while the WEKA data-mining software is used for the OLS method.

Original languageEnglish
Title of host publicationICINCO 2018 - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics
EditorsOleg Gusikhin, Kurosh Madani
PublisherSciTePress
Pages420-426
Number of pages7
ISBN (Electronic)9789897583216
Publication statusPublished - Jan 1 2018
Event15th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2018 - Porto, Portugal
Duration: Jul 29 2018Jul 31 2018

Publication series

NameICINCO 2018 - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics
Volume1

Conference

Conference15th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2018
CountryPortugal
CityPorto
Period7/29/187/31/18

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Keywords

  • Big Data
  • Kalman Filtering
  • Regression Analysis
  • Side-slip Estimation

ASJC Scopus subject areas

  • Information Systems
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering

Cite this

Fényes, D., Németh, B., & Gáspár, P. (2018). A novel big-data-based estimation method of side-slip angles for autonomous road vehicles. In O. Gusikhin, & K. Madani (Eds.), ICINCO 2018 - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics (pp. 420-426). (ICINCO 2018 - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics; Vol. 1). SciTePress.