Development of an I2V solution designes an Infrastructure-to-Vehicle (I2V) solution in order to inform in real time connected and autonomous vehicles about traffic conditions (position, speed, braking, lane changes, etc.) and incidents.


Core technologies used segmentation technology
Lanes segmentation

Automatic segmentation mask

Automatic Incident detection (AID) by
Incident detection

Stopped vehicle, pedestrian, smoke, etc.

Tracking Technology by

Vehicle tracking and occlusion management

Classification Technology by
Vehicle characterization

Classification, profiling, etc.

Real-time tracking technology by
Dynamic data

Turn signal, braking and speed information

Reported data

Position and speed




Autonomous Vehicle GIF by
Cofiroute Logo

As part of the SAM Project, has designed for Cofiroute an image processing solution designed to inform connected and autonomous vehicles of the traffic conditions and incidents in the A86 Duplex Tunnel. This solution has been based on the video surveillance cameras already installed into the tunnel, and therefore does not require any change of equipment.

10.5 km of tunnel

194 cameras

18,000 vehicles per day


“Thanks to the algorithm developed by, connected and autonomous vehicles will benefit from qualified information on traffic conditions, events and singularities of the motorway network. This data will enable them to anticipate risk situations to provide the user with a safe and continuous autonomous experience.”

Pierre Delaigue, Director of Autonomous, Connected and Electric Mobility Projects Leonard | VINCI Autoroutes