… of high mobility vehicular networks and motivate the use of machine learning to address the
… of machine learning, we discuss its applications to learn the dynamics of vehicular networks …

… Apart from the traditional vehicular networks, we also consider modern vehicular network
architectures. We propose a taxonomy of security attacks in vehicular networks and discuss …

… in vehicular networks from the networking aspect. Research topics covered in this article
include network … management, and energy efficiency in vehicular networks. The findings of this …

… to apply advanced machine learning into vehicular communications and networking. It …
ML-enabled evolution for vehicular networks in terms of communication, networking, and security …

… in applying machine learning in vehicular networks and … in applying machine learning in
vehicular networks to facilitate … resource management using reinforcement learning in detail. …

… in applying machine learning in vehicular networks and attempt … machine learning, we
present some application examples of machine learning in solving problems arising in vehicular …

… in a vehicular network. 3GPP is a de-facto standard for LTE-V2V communication standard …
vehicular networks that may provide optimization of resource allocation in a vehicular network, …

… vehicular networks using machine learning. Therefore, a thorough understanding of how
machine learning … a dynamic resource allocation in vehicular networks is provided in this study. …

… In Section IV, we describe the applications of machine learning in vehicular network for …
Then, we investigate the machine learning based approaches for intelligent vehicular networking …

… We have introduced machine learning concepts to frame trust rules and Artificial Neural
Network (ANN) to selftrain the vehicular nodes to ensure reliable message propagation. …