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.
|Title of host publication||2016 IEEE Symposium Series on Computational Intelligence (SSCI)|
|Number of pages||8|
|Publication status||E-pub ahead of print - 13 Feb 2017|
|Event||2016 IEEE Symposium Series on Computational Intelligence - Athens, Greece|
Duration: 6 Dec 2016 → 9 Dec 2016
|Conference||2016 IEEE Symposium Series on Computational Intelligence|
|Abbreviated title||SSCI 2016|
|Period||6/12/16 → 9/12/16|
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- agile maneuvering
- autonomous driving
- finite state machine
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