MPC Builder for Autonomous Drive: Automatic Generation of MPCs for Motion Planning and Control

TL;DR

This paper introduces MPC Builder, a framework that automatically generates model predictive controllers for vehicle motion planning, reducing design effort and computational costs in autonomous driving scenarios.

Contribution

The paper presents a novel framework for automatic MPC generation that simplifies design and adapts to traffic situations efficiently.

Findings

Reduced computational costs using C/GMRES solver

Flexible representation of driving tasks

Effective in multiple driving scenarios

Abstract

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.