Side-slip Angle Estimation of Autonomous Road Vehicles Based on Big Data Analysis

Daniel Fenyes, Balazs Nemeth, Mate Asszonyi, P. Gáspár

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

2 Citations (Scopus)

Abstract

The paper proposes a side-slip angle estimation method for autonomous road vehicles using a big data approach. The core of the solution is that on-board signals of numerous autonomous vehicles are available, which can be used to generate the side-slip estimator. The estimation is based on the ordinary linear regression method with OLS subset selection using large amount of data collected from the car sensors. The advantage of the proposed solution is that the numerically complex data mining operations are performed off-line, while the side-slip angle estimation of the vehicle using only its own on-board signals requires low computation effort. The efficiency of the estimation is presented through several CarSim simulations, in which the parameters of the vehicle and the road are varied. Moreover, the method is compared to the simulation results of a sensor fusion based Kalman filtering method.

Original languageEnglish
Title of host publicationMED 2018 - 26th Mediterranean Conference on Control and Automation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages849-854
Number of pages6
ISBN (Print)9781538678909
DOIs
Publication statusPublished - Aug 20 2018
Event26th Mediterranean Conference on Control and Automation, MED 2018 - Zadar, Croatia
Duration: Jun 19 2018Jun 22 2018

Other

Other26th Mediterranean Conference on Control and Automation, MED 2018
CountryCroatia
CityZadar
Period6/19/186/22/18

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization

Cite this

Fenyes, D., Nemeth, B., Asszonyi, M., & Gáspár, P. (2018). Side-slip Angle Estimation of Autonomous Road Vehicles Based on Big Data Analysis. In MED 2018 - 26th Mediterranean Conference on Control and Automation (pp. 849-854). [8443010] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MED.2018.8443010