The Digital Twin concept, initially introduced in the 1960s has experienced rapid uptake at the beginning of the twenty-first century. Over the last two decades,s is has evolved from a simple virtual replica mostly used in manufacturing to complex, real-time, AI-driven systems able to model cities, critical infrastructures, buildings, and traffic.
Digital Twin and CCAM
On May 15th, 2025, the FRODDO project was prominently featured at the Artificial Intelligence for Road Safety and Mobility Scientific Workshop, held in Athens and online. Dr. Panagiotis Fafoutellis from the National Technical University of Athens (NTUA) delivered a comprehensive presentation of FRODDO, showcasing the project’s innovative work in AI-assisted traffic management and smart mobility.
The workshop, organized by the NTUA Department of Transportation Planning and Engineering, brought together experts, researchers, and stakeholders from across Europe, with more than 20 research projects presented throughout the day. The event provided an excellent platform for sharing cutting-edge research and exchanging knowledge on how artificial intelligence is shaping the future of road safety and mobility.
In the transport system of the future, and before the full integration of autonomous vehicles (AVs), mixed traffic conditions involving both AVs and human-driven vehicles will coexist. In these transitional phases, traffic management strategies should be able to adapt to all users’ requirements and their effectiveness will be essential to maintain traffic flow and safety. Such TMS may refer to vehicle platooning—where AVs and human-driven vehicles travel in close, coordinated formations— or dynamic lane reversal strategies – where a specific part of the road changes its use based on the dynamic demand. This need is particularly crucial during non-recurrent events on the network, such as roadworks, accidents, and temporary lane closures.
Vehicle-to-vehicle (V2V) communications can be extremely useful in improving the safety of all road users. Connected, Cooperative and Automated Mobility approaches, such as those promoted by the CCAM consortium, allow the data received from on-board vehicle sensors to be complemented with information from vehicles outside the range of the sensors, thus improving the perception of ADAS systems and their ability to react promptly to dangerous conditions and prevent damage.
