Collective Situational Awareness for CCAM systems

FEV Türkiye is interested in submitting proposals to CL5-2026-01-D6-14: Predicting and avoiding road crashes based on Artificial Intelligence (AI) and big data and CL5-2026-01-D6-03: Next-generation environment perception for real world CCAM operations.

Started in an ongoing CCAM related Horizon Europe Research Project, we have developed situational awareness tools, and an explainable AI for anomaly detection. To extend these studies we are working on AI based cloud integrated collective perception in an effort to establish a collective situational awareness for CCAM environments. We are also working on an explainable AI that is trained to detect social norms violations in scope of our hybrid intelligence development studies.

We offer added value -aligned with the aforementioned two calls, in development of collective collision avoidance systems, AI based task arbitrators, road-users behaviour predicting AI models. In addition to those we can bring in our expertise in SotIF, cybersecurity, functional safety, system engineering, V2X, sensor-fusion, multi-object tracking and trajectory prediction, edge-AI and cloud edge-IoT technologies, xAI, LLMs, Knowledge Distillation, SLMs, GenAI based automated scenario and test case generation.