Artificial intelligence and 6G technologies for achieving as safe interconnected mobility as possible

Simulation of a busy urban environment with vehicles connected to various communication systems
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Simulation of a busy urban environment with vehicles connected to various communication systems

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Application of 6G-EWOC technologies to most demanding vertical applications: a 6G fibre-wireless network for AI-based 3D live maps in support for connected mobility. Copyright: 6G EWOC Consortium

Photonic integrated circuit for optical beamforming. Copyright: AIT Austrian Institute of Technology
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Photonic integrated circuit for optical beamforming. Copyright: AIT Austrian Institute of Technology

Project coordinator José Antonio Lázaro together with UPC researchers participating in the European initiative.
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Project coordinator José Antonio Lázaro together with UPC researchers participating in the European initiative.

Representatives of the institutions and companies participating in the project gathered at the kick-off meeting on the UPC’s North Diagonal Campus on 30 January.
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Representatives of the institutions and companies participating in the project gathered at the kick-off meeting on the UPC’s North Diagonal Campus on 30 January.

A multidisciplinary team from the UPC is working on the development of a network that, combining artificial intelligence with 6G technologies, remote sensing systems and optical communication—both wireless and through optical fibres—allows autonomous and human-driven vehicles to circulate safely and avoiding accidents in areas with heavy traffic or large crowds.

Feb 21, 2024

The European project  AI-Enhanced Fibre-Wireless Optical 6G Network in Support for Connected Mobility (6G-EWOC), coordinated by the Universitat Politècnica de Catalunya - BarcelonaTech (UPC), has been one of 27 selected projects in the second call of the Smart Networks and Services in 6G (6GSNS) programme under Horizon Europe.

The project aims to develop the necessary technologies and design a fibre-wireless optical 6G network that, through AI, is capable of supporting a connected mobility system in areas with heavy traffic or large crowds.

Coordinated by professor José Antonio Lázaro, who is a researcher at the UPC’s Advanced Broadband Communications Centre (CCABA), this multidisciplinary project involves 11 other European partners, including companies and technology centres. It has funding of over five million euros, four of them provided by the EU and the rest by the Swiss government.

The University’s participation is coordinated by researchers from three UPC specific research centres (CER): the Intelligent Data Science and Artificial Intelligence (IDEAI-UPC) research centre, led by Josep Ramon Casas; the Centre for Sensors, Instruments and Systems Development (CD6), led by Santiago Royo; and the Remote Sensing, Antennas, Microwaves and Superconductivity Group (CommSensLab-UPC), led by Adolfo Comerón.

The other national partners are the Telecommunications Technology Centre of Catalonia (CTTC)—also linked to the UPC—and the UPC spin-off BEAMAGINE, based in Barcelona. And the European partners are the Austrian Institute of Technology in Vienna, Austria; BIFROST Communications in Copenhagen, Denmark; NOKIA Networks and the III-V LAB in Paris, France; telecommunications operator OTE and NVIDIA-Mellanox in Athens, Greece; manufacturer MAGNA MAGNA Electronics, Sweden; and LIGENTEC, a spin-off from the École Polytechnique Fédérale de Lausanne, Switzerland.

Representatives of these institutions and companies gathered at the project’s official kick-off meeting, which took place on the UPC’s North Diagonal Campus on 30 and 31 January.

Precise knowledge for autonomous driving
To put the project into context, José Antonio Lázaro states that in a few years “it will be usual for vehicles to drive autonomously, since the necessary technologies to perceive everything around them are evolving rapidly. However, what’s important is to go one step further and make future vehicles capable of driving autonomously and better than humans.”

To achieve this, he explains, it is necessary that in addition to detecting objects, other vehicles and people around them, they are capable of “knowing”, with accuracy, “at what distance they are, at what speed they are going and in what direction. With all this data, the vehicle’s intelligence will be able to decide the safest route—for people both inside and outside the vehicle—to detect blind spots and to realise difficult to perceive situations that are a common cause of car and pedestrian accidents, such as a vehicle or an object blocking the driver’s view of a pedestrian about to cross.”


A complete real-time 3D map

The ideal solution would be for both autonomous and human-driven vehicles to have a real-time map, with detailed 3D information of streets, traffic jams and all of the vehicles, people, animals and objects found wherever they are driving. To reach this solution, “connected” vehicles are needed that can exchange the large volumes of information generated by their powerful sensors both between the vehicles and with the computing centres, which are responsible for merging everything they detect or “see” at each moment through RADAR and LiDAR sensors or through the cameras of the various vehicles in real time.

This system—connected mobility—requires very powerful networks to manage the amount of data generated and uses several technologies, such as those developed and combined under the 6G-EWOC project.

These technologies range from laser-based sensors (such as LiDAR, which can make 3D models of everything around you) to wireless optical communications between vehicles and with elements such as street lights or traffic lights, which can act as an additional 6G antenna.

The project will also rely on high-capacity optical fibres—increasingly present in homes, cities, highways and urban furniture—which can transport all that large volume of data to the nearest distributed computing centre.

In addition, AI techniques are used to organise and direct all data traffic to the various distributed computing centres. Other AI tools will merge the data from the vehicles in each area, thus building a piece of the 3D map and integrating it with other pieces generated by the distributed computing elements in other areas to make that great final puzzle.

The developed network will make it possible to transmit a detailed, complete and updated map to drivers and vehicles in real time, making driving as safe as possible.

José Antonio Lázaro and other researchers in the team teach at the Barcelona School of Telecommunications Engineering (ETSETB), while others are professors at the Terrassa School of Industrial, Aerospace and Audiovisual Engineering (ESEIAAT) and at the Terrassa School of Optics and Optometry (FOOT).