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@INPROCEEDINGS{IEEE VTC Spring 2023,
        author = {Rizzo, Gianluca},
      keywords = {6G, Distributed AI, vehicular communications},
         month = jun,
         title = {Towards AI-Native Vehicular Communications},
     booktitle = {IEEE VTC Spring 2023},
          year = {2023},
     publisher = {IEEE},
      location = {Florence, Italy},
  organization = {IEEE},
           url = {https://ieeexplore.ieee.org/abstract/document/10199974},
           doi = {10.1109/VTC2023-Spring57618.2023.10199974},
      abstract = {The role of fast yet reliable wireless communications
in various application domains is getting ever more important. At
the same time, as use cases are becoming more and more complex,
application requirements are getting ever more stringent. One
example is intelligent transportation, where the efficiency and
reliability of wireless data delivery is essential for effective service
support. As a consequence, in this context the adoption of AI
techniques is widely considered crucial for enabling vehicular
communications to adapt to dynamic changes of the environment.
In this position paper, we discuss some representative applications
of advanced AI tools in vehicular communications. In particular,
we elaborate on the potential of distributed learning based on
federated learning, of proactive service provisioning, and of graph
neural network for enabling AI-native vehicular communications}
}