@inproceedings{307530421b9c48d0bb0bc4f334be6b6c,
title = "A Decoupling Control Scheme for Path Tracking with Model Predictive Path Integral and Output Regulator",
abstract = "The coupling and nonlinearity of vehicle dynamics present considerable challenges to path tracking of autonomous vehicles. In this paper, a necessary condition is derived to decouple the translational motion from yawing motion based on the time-scale separation. Consequently, the translational motion is regulated over an extended control horizon to generate a human-like tracking trajectory. The yawing motion is regulated based on a high-fidelity control model. In addition, model predictive path integral (MPPI) is developed to mitigate the computational burden of nonlinear motion planning through sampling-based optimization. A predictive output regulator is developed to solve the underactuated problem in the 2-DOF lateral dynamics with only 1-DOF of control input. Simulation results show that the proposed method enhances computing efficiency and reduces the lateral jerk by an average of 50% with only one set of parameters.",
keywords = "Autonomous vehicle, Decouple, MPPI, Underactuated control",
author = "Hang Wan and Hui Liu and Shida Nie and Lijin Han",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.; 16th International Symposium on Advanced Vehicle Control, AVEC 2024 ; Conference date: 02-09-2024 Through 06-09-2024",
year = "2024",
doi = "10.1007/978-3-031-70392-8_88",
language = "English",
isbn = "9783031703911",
series = "Lecture Notes in Mechanical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "625--631",
editor = "Giampiero Mastinu and Francesco Braghin and Federico Cheli and Matteo Corno and Savaresi, {Sergio M.}",
booktitle = "16th International Symposium on Advanced Vehicle Control - Proceedings of AVEC 2024 – Society of Automotive Engineers of Japan",
address = "Germany",
}