This article advocates for adaptive model predictive control (Apd_MPC) in autonomous vehicle driver assistance systems. Apd_MPC quickly adjusts parameters using Kalman observers to enhance steering accuracy when changing dynamics. Results demonstrate its ability to improve navigation in complex situations, adapting to sudden obstacles and varying road conditions, thus increasing safety and performance for reliable autonomous driving. MATLAB/SIMULINK simulations at different speeds confirm the effectiveness of this approach. Overall, Apd_MPC holds significant promise for enhancing safety, performance, and the driving experience in a challenging scenario.

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