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The emergence of the 5G mobile network has a huge impact on the evolution of services and functionalities offered to its customers; this latest version of mobile networks will allow the simultaneous connection of a significant number of people and IoT devices, in addition to the improvement of several other features. 5G will serve in a large part of smart cities and especially in the field of intelligent transportation systems (ITS). Vehicular Ad-Hoc Network (VANET) is one of the promising projects on which the ITS is relying on. Its main purpose is to provide communication and information-sharing support for the vehicles in its network. VANET is based on a heterogeneous network architecture composed mainly of two infrastructures, the first one is the cellular infrastructure, and the second is the road infrastructure. This paper proposes a new approach based on Fuzzy multiple attribute decision making (MADM) methods for the selection of the most appropriate infrastructure in the VANET network and consequently enhance the number of executed vertical handover to move from one infrastructure to another without loss of connection.

6G of mobile networks plays a crucial role in improving the capacity and enhancing the quality of services of Vehicle-to-Everything (V2X) based networks evolving in an intelligent environment. VANET is a promising project in the intelligent transportation field using V2X communications. The emergence of several 5G and 6G technologies has raised several challenges for scientists and researchers to allow vehicles and road users to enjoy several services while ensuring their safety on the road. Among these technologies, the unmanned aerial vehicle (UAV), which can perform different tasks for road users and vehicle drivers such as data caching, packet relaying and processing. In this article, we present a new approach based on 6G Unmanned Aerial Vehicles (UAV) technology on a vehicular cloud architecture while exploiting the exchange support of information-centric networking (ICN) for the improvement of network capacity.

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