Predictive Path-Tracking Control of AVs

My research at Stellantis focuses on decision and control systems for autonomous vehicles (AVs), with the objective of extending automated driving control strategies to heterogeneous and critical driving scenarios. I investigate multi-scenario and multi-objective Model Predictive Control (MPC) architectures that adapt online to changing driving contexts while balancing safety, tracking accuracy, comfort, and robustness. The work aims to move beyond single-controller approaches by designing modular and context-aware control frameworks validated in high-fidelity simulation environments such as IPG CarMaker and extended to real-vehicle validation.