Advanced Steering Stability Controls for Autonomous Articulated Vehicles Based on Differential Braking

Articulated vehicles are essential for global freight transportation but are highly susceptible to instability phenomena such as jackknifing, trailer sway, and rollover, particularly under high-speed or emergency maneuvers. These challenges become even more critical in the context of autonomous driving, where stability must be guaranteed without human intervention. Conventional systems like Electronic Stability Control (ESC) and Roll Stability Control (RSC) provide reactive interventions but lack predictive capability, while other advanced methods often address isolated objectives. To overcome these limitations, this paper proposes a Model Predictive Control (MPC)-based control strategy that integrates trajectory tracking, yaw stability, and longitudinal speed regulation within a unified optimization framework, using differential braking as the primary actuator. A dynamic model of a tractor–semitrailer combination was developed, and the proposed controller was validated through high-fidelity simulations under varying operating conditions, including speeds exceeding the critical threshold of 31.04 m/s. Results demonstrate that the MPC-based system effectively mitigates instability, reduces articulation angle and yaw rate deviations, and maintains accurate path tracking while proactively managing vehicle speed. These findings highlight MPC’s potential as a cornerstone technology for safe and reliable autonomous operation of articulated vehicles. Future work will focus on experimental validation and multi-actuator coordination to further enhance performance.