AI-Enhanced Proactive Model Predictive Control for Off-Road Autonomous Vehicles

This paper investigates the use of artificial intelligence (AI) to enhance autonomous vehicle (AV) controls in unstructured off-road environments. Recent research developments address the utilization of AI and deep learning (DL) models to share information with AVs, enabling intelligent navigation in urban environments. The suggested research allows AVs to navigate in an off-road environment by utilizing AI-predicted trajectories while avoiding obstacles. Our method aims to enhance vehicle autonomy, enabling it to move promptly and responsively while interacting with other vehicles in an off-road environment. We demonstrate the efficacy of AI-driven trajectory predictions through comprehensive simulation validations. Moreover, the research demonstrates the use of AI prediction to construct a proactive Model Predictive Controller (MPC) for off-road autonomous vehicles. Simulation studies and comparisons with existing approaches validate the effectiveness and advantages of the proposed approach for off-road autonomous vehicle controls.