investigates four application scenarios
targeting automation levels ranging
from SAE L0 to L4.



  • will provide a platform trough which vehicles will be able to exchange  speeds, positions, intended trajectories/manoeuvres, and other helpful data.

  • The on-board systems will then use this information to derive an optimized driving  strategy or a recommended course of action to follow in order to actively optimize traffic  flow and avoid dangerous situations.

  • For example, cooperative lane changing on highways can help create the needed gaps for  smooth transitions. will explore distributed and centralized approaches for cooperative lane merging.

  • The former involves direct exchanges between the vehicles, while the latter builds upon a MEC server and the 5G network, which support the vehicles’ systems in determining the optimal behaviour to either execute or pass on to the driver as a recommendation.


  • Automated vehicles and human drivers are limited in their ability to ensure safe and efficient travel by their perception of the road traffic situation.

  • The sensors utilized for automated driving (cameras, lidars, and radars) can only “see” until the next obstruction and the same applies to the human eye.

  • Hence, sources of danger (e.g. objects on the road, other vehicles or vulnerable road users like pedestrians or motorcyclists) are often hidden until the very last moment.

  • Moreover, sudden changes in the weather conditions (e.g. dense fog, fog benches, ice on the road) dramatically increase the risk of accidents if the traveling speed is not adapted accordingly.

  • will promote extended situation awareness by enabling vehicles and infrastructure to share their perception of the environment. This will allow detecting potentially dangerous situations well in advance.



  • As wireless networks and phones have become more advanced, also the content consumed by its users has evolved with on-demand video streaming taking the lion’s share of current Internet traffic.

  • With high levels of autonomous driving, passengers’ expectation will be to sit back and enjoy multimedia content (e.g. a movie) during their daily commute, just as if they were in the comfort of their homes.

  • will explore different network architectures and configurations with the goal of making high-quality video streaming always available including in cross-border scenarios.

  • Synergies between LTE, 5G, C-V2X and other technologies will be investigated by in order to satisfy not only the data rate requirements but also the needed coverage at all times.



  • will provide solutions geared towards the promotion of greener driving styles which in time will lead to significant improvements in terms of air quality.

  • will take advantage of information coming from vehicles and will combine it with other data sources to support the road operators and the traffic authorities in determining a course of action that limits the negative impact of vehicular transportation on the environment.

  • One prominent example for such actions is the use of electric drive mode by hybrid vehicles in critical areas.

  • Once such an area is recognized, this can be communicated to the hybrid vehicles approaching it, such that their automated systems or the driver are informed in advance of the need to utilize electric drive.

The 5G-CARMEN project is now over!

For more information.

Copyright © 2018 by 5G CARMEN

This project has received funding from the European Horizon 2020 Programme for research, technological development and demonstration under grant agreement n° 825012 – 5G CARMEN

Fondazione Bruno Kessler – content production and content management | Comunicazionedesign Trento – graphic and web developing