Version 1
: Received: 13 December 2023 / Approved: 14 December 2023 / Online: 14 December 2023 (12:21:57 CET)
How to cite:
Ali Shah, S.A.; Fernando, X.N.; Kashef, R. A Survey on Artificial Intelligence based Internet of Vehicles utilizing Unmanned Aerial Vehicles. Preprints2023, 2023121096. https://doi.org/10.20944/preprints202312.1096.v1
Ali Shah, S.A.; Fernando, X.N.; Kashef, R. A Survey on Artificial Intelligence based Internet of Vehicles utilizing Unmanned Aerial Vehicles. Preprints 2023, 2023121096. https://doi.org/10.20944/preprints202312.1096.v1
Ali Shah, S.A.; Fernando, X.N.; Kashef, R. A Survey on Artificial Intelligence based Internet of Vehicles utilizing Unmanned Aerial Vehicles. Preprints2023, 2023121096. https://doi.org/10.20944/preprints202312.1096.v1
APA Style
Ali Shah, S.A., Fernando, X.N., & Kashef, R. (2023). A Survey on Artificial Intelligence based Internet of Vehicles utilizing Unmanned Aerial Vehicles. Preprints. https://doi.org/10.20944/preprints202312.1096.v1
Chicago/Turabian Style
Ali Shah, S.A., Xavier N Fernando and Rasha Kashef. 2023 "A Survey on Artificial Intelligence based Internet of Vehicles utilizing Unmanned Aerial Vehicles" Preprints. https://doi.org/10.20944/preprints202312.1096.v1
Abstract
The vehicular ad hoc network (VANET) when augmented with internet is called internet of vehicles (IoV). In the IoV, vehicles have on board units (OBUs), use communication technologies and customized software to communicate with infrastructure around them. The vehicles can have permanent connectivity and global network awareness based on cloud computing. IoV technologies are still being assessed to ensure that the network is protected from attacks, supports a dynamic vehicular mobility scenarios and meets the low latency communication requirements between the vehicles and the surrounding infrastructure. To meet these strict Quality of Service (QoS) demands, Unmanned Aerial Vehicles (UAVs) play a vital role in IoV ecosystems. An UAV can serve as a mobile roadside unit (mRSU) to transmit data between vehicles, stationery RSUs and other UAVs. The UAVs have better line of sight (LOS) connections which result in better channel states and lower path loss than fixed RSUs. Although the inclusion of UAVs in vehicular networks has improved the system performance by providing better resource management and routing solutions, the traditional optimization techniques with their limitations are often not applicable. Therefore, in recent years, research community is integrating Artificial Intelligence (AI) and Machine Learning (ML) into UAV based IoV ecosystem to better manage resource allocation, routing and mobility management issues to optimize the overall network performance. In this survey paper we review the existing research done in AI/ML based UAV-IoV networks and communications with focus on resource management and routing from year 2019 to 2023. We have studied different AI techniques, their training attributes and architectures in various research works. The limitations of AI-based approaches in terms of required computational resources, availability of real world data and AI models’ complexity for the UAV-IoV environment are also discussed. Finally, the future directions for UAV-IoV research opportunities that can leverage the full potential of AI are presented.
Keywords
Internet of vehicles; unmanned aerial vehicles; artificial intelligence; resource management; routing; machine learning
Subject
Engineering, Telecommunications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
