One of the most groundbreaking innovations of our time is the development of autonomous vehicles (AVs) technology, which has the potential to significantly improve traffic flow, increase road safety, and support environmental sustainability. However, achieving fully autonomous driving (AD) remains a formidable challenge due to the need – among others – for advanced control systems capable of managing highly dynamic, nonlinear, and uncertain driving environments. Indeed, AVs must navigate complex traffic scenarios, make real-time decisions, and satisfy strict safety and performance constraints. In this context, the present thesis focuses on the design and implementation of a control framework based on Nonlinear Model Predictive Control (NMPC) for AD applications.