Title: Model-predictive-control complex-path tracking for self-driving cars

Authors: Wael A. Farag

Addresses: College of Engineering and Technology, American University of the Middle East, Egaila, 15453, Kuwait; Electrical Engineering Department, Cairo University, Giza, 12613, Egypt

Abstract: In this paper, a comprehensive model-predictive-control (MPC) controller that enables effective complex track manoeuvring for self-driving cars (SDC) is proposed. The full design details and the implementation stages of the proposed SDC-MPC are presented. The SDC-MPC generates a steering (angle) command to the SDC in addition to a throttle (speed/brake) command. The proposed cost function of the SDC-MPC is very comprehensive and is composed of several terms. Each term has its own sub-objective that contributes to the overall optimisation problem. The main goal is to find a solution that can satisfy the purposes of these terms according to their weights (contribution) in the combined objective (cost) function. Extensive simulation studies in complex tracks with many sharp turns have been carried out to evaluate the performance of the proposed controller at different speeds. The analysis shows that the proposed controller with its tuning technique outperforms the other classical ones like PID.

Keywords: MPC control; SDC; self-driving car; autonomous driving; MPC tuning; tracking; path planning; PID control; model predictive control; track follower.

DOI: 10.1504/IJMIC.2020.111624

International Journal of Modelling, Identification and Control, 2020 Vol.34 No.3, pp.265 - 277

Received: 28 Sep 2019
Accepted: 19 Feb 2020

Published online: 30 Nov 2020 *

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