Implementing a finite state machine to achieve vehicle agile maneuvering

Stratis Kanarachos, Manuel Acosta

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

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Abstract

Rally drivers are known by their driving skills, controlling the vehicle beyond the linear region and generating impressive yaw moments to maximize the vehicle agility. In this study, the Moment Method Diagram and Beta Method representations are used to show the maximum achievable yaw moment generated by the front and rear tires. A new maneuverability map is proposed to bypass the limitations imposed by the steady state assumptions, based on the wheel slip – yaw moment representation. Furthermore, a simple strategy is developed to determine the sequence of inputs required to achieve a target yaw Moment. Finally, a finite state machine is modelled in a two track vehicle model to evaluate the proposed methodology.
Original languageEnglish
Title of host publication2016 IEEE Symposium Series on Computational Intelligence (SSCI)
PublisherIEEE
Number of pages8
ISBN (Electronic)978-1-5090-4240-1
ISBN (Print)978-1-5090-4241-8
DOIs
Publication statusE-pub ahead of print - 13 Feb 2017
Event2016 IEEE Symposium Series on Computational Intelligence - Athens, Greece
Duration: 6 Dec 20169 Dec 2016

Conference

Conference2016 IEEE Symposium Series on Computational Intelligence
Abbreviated titleSSCI 2016
CountryGreece
CityAthens
Period6/12/169/12/16

Bibliographical note

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Keywords

  • agile maneuvering
  • autonomous driving
  • finite state machine
  • drift

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  • Cite this

    Kanarachos, S., & Acosta, M. (2017). Implementing a finite state machine to achieve vehicle agile maneuvering. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI) IEEE. https://doi.org/10.1109/SSCI.2016.7850095