Autonomous Driving is, nowadays, a topic widely studied by the most renowned automotive companies and universities. This interest is motivated by several advantages, which include fuel consumption optimization, pollution reduction, accidents decrease and comfort enhancement. In this work, the self-driving topic is applied to a vehicle moving in a highway environment. In particular, this thesis focuses on: 1. the design of a single layer predictive control architecture, based on Artificial Potential Fields techniques, that provides the optimal control inputs in terms of steering angle and acceleration; 2. the use of Machine Learning (ML) techniques to obtain a Neural Network (NN) approximation of the control law designed at the previous point.