Trajectory Tracking for High-Performance Autonomous Vehicles with Real-Time Model Predictive Control

This work is the development of a Model Predictive Controller (MPC) for the integrated control of lateral and longitudinal dynamics of a high-performance autonomous car, which follows a given trajectory on a racetrack. The MPC model is based on an Affine-Force-Input single-track nonlinear bicycle model that accounts for actuation dynamics and delays. The MPC problem is formulated as a quadratic problem, enabling efficient real-time solution with a specific quadratic programming (QP) solver. The controller is implemented in C++ and tested in a real-time hardware-in-the-loop (HIL) simulator, showing excellent tracking performance up to 280 km/h.