Online Robust Model Predictive Control Based Emergency Maneuvering System for Autonomous Vehicles

Abstract

Nonlinear robust model predictive control (RMPC) provides a promising solution to the problem of automatic emergency maneuvering and it is capable of handling multiple, possibly conflicting objectives of robustness and performance. Even though RMPC gives a suboptimal solution, the critical challenge in its realtime implementation is the high computational demand. This paper presents a realtime capable, robust tube MPCbased framework for steering control during emergency obstacle avoidance maneuvers. The novelty of this framework lies in the robust integration of path planning and pathfollowing tasks of autonomous vehicles. A simulation study showcases the robust performance improvements of the proposed strategy over a nonrobust MPC in different extreme maneuvering scenarios.