A Real-Time Vehicle-in-the-Loop Platform with Cooperative UAV Edge Computing and Passenger-in-the-Loop Integration

To enable safe and scalable autonomous driving experimentation, this paper presents a novel Vehicle-in-the-Loop framework coupling a physical test vehicle with a high-fidelity, georeferenced digital environment for realistic closed-loop experimentation. The platform integrates three core components: a physical test vehicle with robotic actuation; a deterministic real-time control unit executing Behavioral Planning and Nonlinear Model Predictive Control (NMPC); and a high-fidelity virtual environment rendered in Unreal Engine, enabling interaction with dynamically generated scenarios while preserving physical consistency. A key contribution is a cooperative perception layer based on an Unmanned Aerial Vehicle (UAV), operating as an external sensing and edge-computing node. By processing visual data in real time, the UAV extends situational awareness beyond onboard sensor limitations. The platform also supports a Passenger-in-the-Loop configuration, combining real vehicle dynamics with immersive virtual reality for safe evaluation of human–machine interaction during autonomous maneuvers. Results demonstrate accurate trajectory tracking, reliable real-time performance of the NMPC controller, and consistent operation of the distributed perception pipeline under strict timing constraints.