Wireless V2X Communication Testbed for Connected, Cooperative and Automated Mobility

Connected cooperative and automated mobility (CCAM) benefits from reliable wireless vehicle-to-everything (V2X) communication links in safety-critical and time-sensitive situations. The ego vehicle's perception, primarily derived from LIDAR, RADAR, and camera data, is limited by the line-of-sight (LOS). Sensor information beyond the LOS can be acquired by reliable V2X communication links from other cooperative vehicles or infrastructure elements. We identify CCAM use cases for both real-world applications and test phases, which stand to gain from understanding spatial reliability regions for communication links. Frame error rate (FER) classes for these regions, from the perspective of the ego vehicle, are provided to aid decision-making for autonomous vehicles. We propose a testbed architecture for system validation, verification, and test scenario generation, which integrates FER prediction through a high-performance open-source computing reference framework (HOPE). Our study demonstrates that the measured FER within a city scenario closely aligns with the FER obtained via a hardware-in-the-loop (HiL) framework and a non-stationary geometry-based stochastic channel model (GSCM) that utilizes OpenStreetMap data enriched with event-specific static objects. We use the GSCM and the HiL framework to overcome the fundamental limits of estimating the FER in non-stationary scenarios. As a final demonstration of the HOPE framework, we achieve an 80 % accuracy in predicting the FER class.