Predictive Active Steering Control for Autonomous Vehicle Systems

TLDR

The paper proposes a model predictive control framework for active front steering in autonomous vehicles, offering two computationally distinct approaches. The MPC controller predicts a finite‑horizon trajectory and computes steering angles to follow it on slippery roads at high entry speed, using either a nonlinear vehicle model or successive online linearization, with discussions of computational complexity and performance. Simulation and experimental tests up to 21 m/s on icy roads confirm the effectiveness of the proposed MPC formulation.

Abstract

In this paper, a model predictive control (MPC) approach for controlling an active front steering system in an autonomous vehicle is presented. At each time step, a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to follow the trajectory on slippery roads at the highest possible entry speed. We present two approaches with different computational complexities. In the first approach, we formulate the MPC problem by using a nonlinear vehicle model. The second approach is based on successive online linearization of the vehicle model. Discussions on computational complexity and performance of the two schemes are presented. The effectiveness of the proposed MPC formulation is demonstrated by simulation and experimental tests up to 21 m/s on icy roads