Traffic Commander, developed by the Hellenic Police, already brings together information from traffic systems, cameras, drones, incidents, weather, roadworks, public transport and operational reports. By correlating these data across space and time, it transforms isolated events into a unified operational picture.
Its next possible evolutionary step could be the integration of a SUMO-based traffic digital twin.
Inspired by the Digital Twin-Aided Municipal Traffic Control—DiTAT—research project, a digital-twin layer could reproduce current traffic conditions virtually and test alternative responses, such as:
🔹 changing traffic-light timings;
🔹 coordinating neighbouring intersections;
🔹 protecting emergency routes;
🔹 redirecting traffic;
🔹 deploying officers or drones;
🔹 combining signal changes with field interventions.
Each alternative could be evaluated against measurable indicators such as travel time, throughput, queue length, congestion propagation, recovery time and resource requirements.
The result would be a closed decision-support cycle:
Data → Operational picture → Simulation → Recommended intervention → Human approval → Action → Measured outcome → Institutional knowledge.
This would not replace the Traffic Police operator or the Κ.Ο.Μ.Β.Ο.Σ. team. It would provide them with a safe virtual environment in which alternative measures could be compared before implementation.
Traffic Commander already helps answer:
“Where is the problem, how serious is it, and what does it affect?”
A digital twin could add:
“What is likely to happen next—and which intervention is most likely to improve it?”
From observing the city to understanding, simulating and anticipating it.
References:
- Traffic Commander: Ο ψηφιακός εγκέφαλος διαχείρισης της κυκλοφορίας στην Αττική
- Official Traffic Commander overview presentation
- Official Traffic Commander technical architecture presentation
- Pradhananga, R. et al. (2025). Digital Twin-Aided Municipal Traffic Control, SUMO Conference Proceedings, 6, 149–161.
- Conference presentation: Digital Twin-Aided Municipal Traffic Control
