Driving the Future of Connected, Safe and Sustainable Mobility
The Cynergy4MIE project brings together 44 European partners from research, industry, and academia — coordinated by AVL List GmbH — to develop next-generation intelligent, connected mobility and infrastructure systems.
The project’s mission is to seamlessly integrate mobility, infrastructure, and energy, building a foundation for sustainable, safe, and resilient transportation through the application of cyber-physical systems and artificial intelligence (AI).
Within this European collaboration, VIRTUAL VEHICLE Research GmbH plays a leading role in defining the overall system architecture, simulation framework, and demonstrator development. The institute leads Work Package 2 – System Architecture, Modelling and Simulations, and coordinates Supply Chain 5 (SC5), while also contributing actively to Supply Chain 4 (SC4).
SC4: Crowd-Based Road Infrastructure Monitoring
Under Supply Chain 4 – Crowd-Sourced Road Condition and Traffic Risk Monitoring, Cynergy4MIE is advancing a multi-layered system for dynamic road condition assessment.
By fusing multiple data sources, the project creates a comprehensive digital representation of real road segments, as well as a digital twin that supports predictive maintenance and improved traffic safety.
Three complementary data layers form the foundation of this approach:
- Vehicle data (crowdsensing): Artificial intelligence models analyse sensor data, such as IMU signals, to detect potholes, cracks, and surface irregularities in real time.
- Direct sensor data: LiDAR, camera, and acoustic sensors capture high-resolution 3D models of the road surface, providing the ground truth for calibration and validation.
- Satellite data (InSAR): Enables millimetre-scale detection of ground deformation, allowing early identification of structural risks in critical infrastructure.
By combining these sources, Cynergy4MIE establishes a data-driven monitoring pipeline that transforms conventional maintenance into predictive, cost-efficient road management.
SC5: Swarm Intelligence for Search & Rescue Missions
Under Supply Chain 5 – Multi-Agent and Cooperative Sensing & Control in Emergency Response Applications, the project develops autonomous multi-agent systems — including drones and robotic ground units — to assist in search and rescue (SAR) operations.
The research focuses on designing resilient, cooperative control strategies that remain effective even in GNSS-denied or extreme environments. Through the integration of AI-based coordination and realistic field simulations, the system enables reliable communication and decision-making among multiple autonomous agents.
The demonstrator platforms include Drones (DJI Matrice 4T, DJI Mini 3), a UGV (Unitree Go2 robotic dog).
Together, these agents simulate post-earthquake and disaster scenarios, supporting the rapid localisation of survivors. A newly developed A*-based coverage algorithm enables strategic, multi-agent area coverage, significantly improving both search efficiency and operational safety in real-world rescue missions.
From Research to Real-World Impact
Through Cynergy4MIE, European partners are building a bridge between cutting-edge research and real-world applications — connecting AI-driven road monitoring, autonomous systems, and emergency response robotics. These developments are essential steps toward the European vision of connected, sustainable, and safe mobility, in alignment with the broader principles of Society 5.0, a society where technology and human well-being advance hand in hand.
Blog signed by: ViF team