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Guest Editors:

Xuemin (Sherman) Shen
Romano Fantacci
Shanzhi Chen

Special Issue Papers

Scanning the Issue

By X. (Sherman) Shen, R. Fantacci, and S. Chen

Mobile Edge Intelligence and Computing for the Internet of Vehicles

By J. Zhang and K. B. Letaief

This article overviews the edge information system (EIS), including edge caching, edge computing, and edge AI, which will enable a plethora of new exciting intelligent IoV applications.

Learning Driving Models From Parallel End-to-End Driving Data Set

By L. Chen, Q. Wang, X. Lu, D. Cao, and F.-Y. Wang

This article concerns how simulated-world data and real- world data can be efficiently used to improve the performance of parallel end- to-end autonomous driving. It introduces a parallel end-to-end driving data set (PED), containing real-world images, corresponding simulated-world images, and vehicle information.

SDN/NFV-Empowered Future IoV With Enhanced Communication, Computing, and Caching

By W. Zhuang, Q. Ye, F. Lyu, N. Cheng, and J. Ren

This article presents an overview of SDN/NFV-enabled IoV, a new network architecture for IoV. Here, SDN/NFV technologies are leveraged to enhance the performance of IoV and enable diverse IoV scenarios and applications.

Future Intelligent and Secure Vehicular Network Toward 6G: Machine-Learning Approaches

By F. Tang, Y. Kawamoto, N. Kato, and J. Liu

This article reveals the potential to apply advanced machine learning into vehicular communications and networking. It provides a survey on various machine learning techniques applied to communication, networking, and security parts in vehicular networks, and envisions the ways of enabling AI toward future 6G vehicular networks.

Evolutionary V2X Technologies Toward the Internet of Vehicles: Challenges and Opportunities

By H. Zhou, W. Xu, J. Chen, and W. Wang

This article surveys the historical process and status quo of V2X technologies, while listing the major V2X communication technology standards in North America, Europe, and Asia.

Toward Reliable and Scalable Internet of Vehicles: Performance Analysis and Resource Management

By Y. Ni, L. Cai, J. He, A. Vinel, Y. Li, H. Mosavat-Jahromi, and J. Pan

This article concerns how to ensure reliable and scalable wireless transmissions for IoV based on performance modeling and analysis.

Deep-Learning-Based Wireless Resource Allocation With Application to Vehicular Networks

By L. Liang, H. Ye, G. Yu, and G. Y. Li

This article discusses the key motivations and roadblocks of using deep learning for wireless resource allocation with applications to vehicular networks.

The Security of Autonomous Driving: Threats, Defenses, and Future Directions

By K. Ren, Q. Wang, C. Wang, Z. Qin, and X. Lin

This article gives a systematic study on the security threats surrounding autonomous driving, from the angles of perception, navigation, and control.

5G Vehicle-to-Everything Services: Gearing Up for Security and Privacy

By R. Lu, L. Zhang, J. Ni, and Y. Fang

This article reviews the architecture and the use cases of 5G V2X; studies a series of trust, security, and privacy issues in 5G V2X services; and discusses the potential attacks on trust, security, and privacy in 5G V2X.

Point of View

A Grid of Microgrids: Is it the Right Answer?

By N. Martins, A. L. Diniz, and J. G. C. Barros