Eze, Elias and Eze, Joy. 2023. Artificial intelligence support for 5G/6G-enabled Internet of Vehicles networks: An overview. ITU Journal on Future and Evolving Technologies, 4(1), pp. 178-195. ISSN 2616-8375 [Article]

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Abstract or Description

Improving transportation efficiency and on-road safety using Intelligent Transportation Systems (ITSs) has become crucial as road congestion and vehicle complexity increase coupled with ongoing rapid development and deployment of electric vehicles across the globe. Applying data-driven methods enables AI to address high mobility and dynamic vehicular communications and network issues facing traditional solutions and approaches like network optimization techniques and conventional control loop design. This study provides a concise review of DL, ML and SI techniques and applications that are currently being explored by different research efforts within the application area of vehicular networks.

Item Type:	Article
Identification Number (DOI):	https://doi.org/10.52953/IEZN8770
Additional Information:	© International Telecommunication Union, available under the CC BY-NC-ND 3.0 IGO license.
Keywords:	5G/6G, artificial intelligence, deep learning, intelligent transportation systems, Internet of Vehicles, Internet of Things, machine learning, swarm intelligence
Departments, Centres and Research Units:	Computing
Dates:	Date Event 2022 Accepted 10 March 2023 Published
Item ID:	38234
Date Deposited:	30 Jan 2025 12:42
Last Modified:	30 Jan 2025 12:51
Peer Reviewed:	Yes, this version has been peer-reviewed.
URI:	https://research.gold.ac.uk/id/eprint/38234

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