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Article

A Variable-Sampling Time Model Predictive Control Algorithm for Improving Path-Tracking Performance of a Vehicle

1
The Graduate School of Automotive Engineering, Kookmin University, Seoul 02707, Korea
2
Department of Congno-Mechatronics Engineering, Pusan National University, Busan 46241, Korea
3
Department of Optics and Mechatronics Engineering, Pusan National University, Busan 46241, Korea
4
Department of Automobile and IT Convergence, Kookmin University, Seoul 02707, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Arturo de la Escalera Hueso and Steven Waslander
Sensors 2021, 21(20), 6845; https://doi.org/10.3390/s21206845
Received: 14 September 2021 / Revised: 11 October 2021 / Accepted: 13 October 2021 / Published: 14 October 2021
(This article belongs to the Section Electronic Sensors)
This paper proposes a novel model predictive control (MPC) algorithm that increases the path tracking performance according to the control input. The proposed algorithm reduces the path tracking errors of MPC by updating the sampling time of the next step according to the control inputs (i.e., the lateral velocity and front steering angle) calculated in each step of the MPC algorithm. The scenarios of a mixture of straight and curved driving paths were constructed, and the optimal control input was calculated in each step. In the experiment, a scenario was created with the Automated Driving Toolbox of MATLAB, and the path-following performance characteristics and computation times of the existing and proposed MPC algorithms were verified and compared with simulations. The results prove that the proposed MPC algorithm has improved path-following performance compared to those of the existing MPC algorithm. View Full-Text
Keywords: model predictive control; variable sampling time; autonomous driving; path tracking; autonomous vehicle model predictive control; variable sampling time; autonomous driving; path tracking; autonomous vehicle
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MDPI and ACS Style

Choi, Y.; Lee, W.; Kim, J.; Yoo, J. A Variable-Sampling Time Model Predictive Control Algorithm for Improving Path-Tracking Performance of a Vehicle. Sensors 2021, 21, 6845. https://doi.org/10.3390/s21206845

AMA Style

Choi Y, Lee W, Kim J, Yoo J. A Variable-Sampling Time Model Predictive Control Algorithm for Improving Path-Tracking Performance of a Vehicle. Sensors. 2021; 21(20):6845. https://doi.org/10.3390/s21206845

Chicago/Turabian Style

Choi, Yoonsuk, Wonwoo Lee, Jeesu Kim, and Jinwoo Yoo. 2021. "A Variable-Sampling Time Model Predictive Control Algorithm for Improving Path-Tracking Performance of a Vehicle" Sensors 21, no. 20: 6845. https://doi.org/10.3390/s21206845

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