Driver-in-the-Loop Testing of Genetic Algorithm-Tuned Active Anti-Roll Bar for Vehicle Lateral Stability

This study presents the assessment of an Active Anti-Roll Bar (AARB) system using a driving simulator, aiming to enhance vehicle lateral stability and overall handling performance. The research focuses on optimizing the control strategy through a genetic algorithm and evaluating its effectiveness via offline simulations and Driver-in-the-Loop (DiL) testing, utilizing a 14-degree-of-freedom vehicle model from VI-CarRealTime. The proposed AARB system dynamically adjusts the roll stiffness of the front and rear axles, effectively reducing body roll and improving stability during high-speed maneuvers. The results highlight significant improvements in mitigating understeer and oversteer, enhancing both driver confidence and vehicle safety. The findings indicate that integrating genetic algorithms for control tuning, combined with real-time validation through DiL testing, offers a robust approach to advancing vehicle dynamics control systems.