This study presents a new framework for vehicle motion planning and control based on the automatic generation of model predictive controllers (MPC) named MPC Builder. In this framework, several components necessary for MPC, such as models, constraints, and cost functions, are prepared in advance. The MPC Builder then online generates various MPCs according to traffic situations in a unified manner. This scheme enabled us to represent various driving tasks with minimal design effort. 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.
翻译:这项研究在自动生成称为MPC建设器的模型预测控制器(MPC)的基础上,为车辆运动规划和控制提供了一个新的框架,在这一框架内,预先准备了对移动控制器必要的若干组成部分,例如模型、限制和成本功能,随后,移动控制器(MPC)构建器(MPC)根据交通情况统一生成了各种移动控制器,这个计划使我们能够以最小的设计努力来代表各种驾驶任务,拟议框架的实施考虑到了能够降低计算成本的连续/通用最低残留(C/GMRES)方法优化求解器(C/GMRES),最后,对多种驾驶方案进行了数字实验。