The IEEE Open Journal of the Communications Society (OJ-COMS) is an open access, all-electronic journal that publishes original high-quality manuscripts on advances in the state of the art of telecommunications systems and networks. The papers in IEEE OJ-COMS are included in Scopus. Submissions reporting new theoretical findings (including novel methods, concepts, and studies) and practical contributions (including experiments and development of prototypes) are welcome. Additionally, survey and tutorial articles are considered.

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Hallmarks of the IEEE Open Journal of the Communications Society (OJ-COMS) are a rapid peer review process and open access of all published papers.  The broad scope of the journal comprises, but is not limited to:

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Cloud Computing, Edge Computing, and Internet of Things
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Communications Theory and Systems
Green, Cognitive, and Intelligent Communications and Networks
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Special Issue on Intelligent Internet of Vehicular Communications: Challenges, Opportunities, and Future Directions
提出日: 2025-08-30

Vehicular communication presents compelling evidence for advancing road safety, enabling sustainable transportation, and enhancing the efficiency of traffic and autonomous vehicle management systems. Indeed, the impact of traffic control and safety is substantial for individuals who regularly traverse roadways. The anticipated gradual rise in road fatalities and accidents in the upcoming years is attributed to the rapidly growing number of vehicles on the road. Vehicular communication, facilitated by specialized short-range communication, enables communication services between roadside infrastructure (V2I) and nearby vehicles (V2V). These communication systems contribute to enhanced road safety, enabling more comprehensive monitoring and understanding of traffic patterns.

The development of the Internet of Vehicular (IoV) communications represents a pivotal technological breakthrough for the future implementation of intelligent transportation systems. IoV communication systems have garnered significant attention from academia, governments, and industry due to their notable contributions to improving road safety. By offering a range of services and delivering accurate reports to drivers, passengers, and regulatory authorities, IoV communication has the potential to enhance the safety and efficiency of transportation networks. A key feature of IoV communication is its ability to route information between source and destination vehicles, utilizing fixed communication infrastructures to establish optimal pathways. However, privacy remains a critical challenge in IoV networks, given their open nature, the absence of consistent infrastructure, high vehicle mobility, and legal constraints surrounding data protection. By leveraging Vehicle-to-Everything (V2X) connectivity, IoV communication facilitates seamless information sharing and data collection concerning vehicles, autonomous systems, road conditions, and their environments.

Artificial Intelligence (AI) algorithms serve as a key strategy for improving routing efficiency, ensuring secure communication, managing vehicle operations, and implementing sustainable traffic control within IoV networks. These algorithms excel at adapting to the ever-changing conditions of vehicular networks, uncovering valuable patterns in the data exchanged between vehicles, infrastructure, and pedestrians. In AI-powered IoV systems, there is a strong focus on tackling security and privacy issues, such as jamming attacks, data manipulation, and unauthorized data access.

However, designing an optimal IoV network presents considerable challenges due to the inherent characteristics of these systems. Key difficulties include the need for self-organization, frequent topology changes, high vehicle mobility, short-duration connections, and constrained bandwidth availability.

Technical Scope of the Proposal: This special section focuses on utilizing AI-powered IoV communications to address the latest challenges faced by IoV communications. Disciplines such as radio engineering, wireless communications, and computer science are expected to make significant contributions to this area of research. With the rising interest in IoV communications and the integration of AI into wireless and mobile communication standards, we anticipate a significant influx of contributions.

AI algorithms are well-equipped to manage the dynamic nature of vehicular communications, enabling the detection of patterns in the data exchanged between vehicles, infrastructure, and pedestrians. Additionally, intelligent IoV communications effectively address a variety of security and privacy issues, including threats such as jamming, data manipulation, and eavesdropping.

The main objective of this special issue is to encourage researchers to investigate essential AI techniques that can be utilized to improve intelligent and sustainable traffic and mobility management within the context of IoV communications.

The topics of interest include but are not limited to:

    Testbeds and standardization models for AI-driven IoV communications
    Intelligent architecture for future IoV communications
    Intelligent resource allocation for integrated terrestrial and non-terrestrial networks in vehicular communications
    AI Approaches for enhancing radio environment awareness in IoV communications
    Intelligent traffic control system for IoV communication
    Intelligent navigation and location-based services in IoV communication
    Intelligent protocols, applications, and systems for efficient traffic and vehicle management in IoV communications
    Integrating cloud-fog computing with IoV for AI-driven traffic management solutions
    Utilizing Blockchain for effective traffic and vehicle management in IoV communications
    Designing the Future Internet to Support IoV Communication Systems
    Deep Learning and Distributed Machine Learning Techniques in Vehicular Communication Networks
    AI-Based Cooperative Applications Between IoV and UAV Systems
    Blockchain-Integrated Autonomous Vehicular Networks for Secure Communication
    AI-Enhanced Mobile Computing for Traffic and Vehicle Control in IoV Systems
    Generative AI (and LLM) for semantic image transmission over wireless channels in IoV networks