Rollover Prevention and Path Following of Autonomous Vehicle Using Nonlinear Model Predictive Control

Abstract

Autonomous Ground Vehicles (AGVs) may be at risk of dangerous rollover if they operate without taking roll motion into consideration. In this paper we present a Nonlinear Model Predictive Control (NMPC) approach for combined braking and steering systems in AGV s. We formulate a predictive control problem in order to best follow a given path at maximum optimal speed by controlling the front steering angle and the brakes at the wheels, while fulfilling roll angle, yaw-rate and physical constraints to maintain vehicle stability. Open Source Software (OSS) known as Automatic Control and Dynamic Optimization (ACADO) is used to design and simulate the NMPC controller based on an eight Degrees of Freedom (8 DOF) nonlinear vehicle model. The simulation results show that the controller is able to track a given trajectory while preventing the vehicle from rolling over and spinning out by respecting given constraints. A maximum velocity of 6 m/s is observed when roll angle constraint is not active, and a minimum velocity of 4.32 m/s is observed when roll angle constraint is active.