… vehicular networks and spatiotemporal knowledge transfer, is introduced in this section.
MEC-enabled vehicular networks … vehicular networks, the spatiotemporal knowledge transfer …

… On the other hand, the newly joined vehicles can use the experience of the expert vehicles
to quickly deploy their own knowledge system. Using knowledge transfer in our problem can …

… Neural Network in application scenarios envisioning the interaction between a vehicle user
… Then, in Section III-B we explain how cooperation and knowledge transfer is implemented …

… knowledge training, ie, when knowledge is … of knowledge distribution aspects in vehicular
networks, we specifically consider the following open questions: • Does knowledge networking …

… Therefore, mobility management solutions developed specifically for vehicular networks …
for vehicular networks. First, the requirements of mobility management for vehicular networks …

… vehicle velocity is set to v = 100 km/h, whereas in the transfer learning process, we initialize
the parameter as v = 60 km/h. It is verified that with the knowledge transfer, … proposed transfer …

… knowledge applied to vehicular networks, and suggests a structure for vehicular knowledge
… , it exposes the potential benefits for network load and delay of such knowledge structuring. …

… , transferring information from raw sensed data to knowledge and explores the knowledge of
risk reasoning through vehicular … knowledge of risky road users and risky locations. We use …

… collaboration is imperative in a vehicular network. Moreover, decentralized … vehicular
network to enhance trust, provenance, and eliminate unauthorized access to the vehicular …

… learning for RA in vehicular networks. In Section VII, we summarize three important future
directions for RA research in vehicular networks lead by network slicing, machine learning, …