An Autonomous Steering Control Scheme for Articulated Heavy Vehicles Using - Model Predictive Control Technique

Abstract

<div class="section abstract"><div class="htmlview paragraph">This article presents an autonomous steering control scheme for articulated heavy vehicles (AHVs). Despite economic and environmental benefits in freight transportation, lateral stability is always a concern for AHVs in high-speed highway operations due to their multi-unit vehicle structures, and high centers of gravity (CGs). In addition, North American harsh winter weather makes the lateral stability even more challenging. AHVs often experience amplified lateral motions of trailing vehicle units in high-speed evasive maneuvers. AHVs represent a 7.5 times higher risk than passenger cars in highway operation. Human driver errors cause about 94% of traffic collisions. However, little attention has been paid to autonomous steering control of AHVs. To improve the directional performance of AHVs under a high-speed lane-change maneuvers, an autonomous steering control scheme is proposed for a tractor/semi-trailer using a model predictive control (MPC) technique, which controls the steering angle of the tractor front wheels. Various control methods are developed to improve the path following of AHVs, but they only focus on the trajectory tracking of the tractor. The current MPC-based scheme considers both the tractor and trailer for path tracking to improve directional performance of the AHV. The effectiveness of the proposed scheme is examined using co-simulations, in which the MPC controller is designed using MatLab/SimuLink and the virtual tractor/semi-trailer is generated in TruckSim. Simulation results demonstrate the effectiveness of the proposed autonomous steering control scheme.</div></div>