A Hierarchical Model Predictive Control Framework for Autonomous Ground Vehicles

• A hierarchical framework based on Model Predictive Control (MPC) for autonomous vehicles is presented. We formulate a predictive control problem in order to best follow a given path by controlling the front steering angle while fulfilling various physical and design constraints.We start from the low-level active steering-controller presented in [3], [9] and integrate it with a high level trajectory planner. At both levels MPC design is used. At the high-level, a trajectory is computed on-line, in a receding horizon fashion, based on a simplified point-mass vehicle model. At the low-level a MPC controller computes the vehicle inputs in order to best follow the desired trajectory based on detailed nonlinear vehicle model.This article presents the approach, the method for implementing it, and successful preliminary simulative results on slippery roads at high entry speed.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)

Keyword

point-mass vehicle model

high level trajectory planner

low-level active steering-controller

autonomous ground vehicles

slippery roads

nonlinear vehicle model

hierarchical model predictive control

front steering angle

Publication and Content Type

kon (subject category)

ref (subject category)