2022/10/29 by Kohei Honda, Hiroyuki Okuda, Honda, Kohei +5 · 1 citation
Engineering · #Advanced Control Systems Optimization #FOS: Computer and information sciences #FOS: Electrical engineering #Real-time simulation and control systems #Robotics (cs.RO) #Systems and Control (eess.SY) #Vehicle Dynamics and Control Systems #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2210.16512
openalex publication_date 2022/10/29 · openalex created_date 2022/11/06 · openalex updated_date 2026/07/28
This study presents a new framework for vehicle motion planning and control based on the automatic generation of model predictive controllers (MPCs) named MPC Builder. In this framework, several components necessary for MPC, such as prediction models, constraints, and cost functions, are prepared in advance. The MPC Builder then generates various MPCs online in a unified manner according to traffic situations. This scheme enabled us to represent various driving tasks with less design effort than typical switched MPC systems. The proposed framework was implemented considering the continuation/generalized minimum residual (C/GMRES) method optimization solver, which can reduce computational costs. Finally, numerical experiments on multiple driving scenarios were presented.