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.

翻译：本研究提出了一种基于模型预测控制器（MPC）自动生成的新型车辆运动规划与控制框架，命名为"MPC构建器"。在该框架中，预测模型、约束条件和代价函数等MPC所需的多个组件被预先准备就绪。随后，MPC构建器根据交通场景，以统一方式在线生成各类MPC控制器。这一方案使得我们能够以较传统切换式MPC系统更少的设计工作量，表征多种驾驶任务。所提出的框架采用可降低计算成本的连续/广义最小残差（C/GMRES）法优化求解器进行实现。最后，展示了多个驾驶场景下的数值实验结果。