Machine learning technologies for secure vehicular communication in internet of vehicles: recent advances and applications

ES Ali, MK Hasan, R Hassan, RA Saeed… - Security and …, 2021 - Wiley Online Library
Recently, interest in Internet of Vehicles'(IoV) technologies has significantly emerged due to
the substantial development in the smart automobile industries. Internet of Vehicles' …

A survey of collaborative machine learning using 5G vehicular communications

SV Balkus, H Wang, BD Cornet… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
By enabling autonomous vehicles (AVs) to share data while driving, 5G vehicular
communications allow AVs to collaborate on solving common autonomous driving tasks …

Artificial intelligence for vehicle-to-everything: A survey

W Tong, A Hussain, WX Bo, S Maharjan - IEEE Access, 2019 - ieeexplore.ieee.org
Recently, the advancement in communications, intelligent transportation systems, and
computational systems has opened up new opportunities for intelligent traffic safety, comfort …

BERT-based deep spatial-temporal network for taxi demand prediction

D Cao, K Zeng, J Wang, PK Sharma… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Taxi demand prediction plays a significant role in assisting the pre-allocation of taxi
resources to avoid mismatches between demand and service, particularly in the era of the …

Machine learning models and techniques for VANET based traffic management: Implementation issues and challenges

S Khatri, H Vachhani, S Shah, J Bhatia… - Peer-to-Peer Networking …, 2021 - Springer
Low latency in communication among the vehicles and RSUs, smooth traffic flow, and road
safety are the major concerns of the Intelligent Transportation Systems. Vehicular Ad hoc …

Federated learning of explainable AI models in 6G systems: Towards secure and automated vehicle networking

A Renda, P Ducange, F Marcelloni, D Sabella… - Information, 2022 - mdpi.com
This article presents the concept of federated learning (FL) of eXplainable Artificial
Intelligence (XAI) models as an enabling technology in advanced 5G towards 6G systems …

A survey of deep learning on mobile devices: Applications, optimizations, challenges, and research opportunities

T Zhao, Y Xie, Y Wang, J Cheng, X Guo… - Proceedings of the …, 2022 - ieeexplore.ieee.org
Deep learning (DL) has demonstrated great performance in various applications on
powerful computers and servers. Recently, with the advancement of more powerful mobile …

A comprehensive survey of the key technologies and challenges surrounding vehicular ad hoc networks

Z Xia, J Wu, L Wu, Y Chen, J Yang, PS Yu - ACM Transactions on …, 2021 - dl.acm.org
Vehicular ad hoc networks (VANETs) and the services they support are an essential part of
intelligent transportation. Through physical technologies, applications, protocols, and …

Deep-learning-based intelligent intervehicle distance control for 6G-enabled cooperative autonomous driving

X Chen, S Leng, J He, L Zhou - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
Research on the sixth-generation cellular networks (6G) is gaining huge momentum to
achieve ubiquitous wireless connectivity. Connected autonomous vehicles (CAVs) is a …

A survey on deep learning for challenged networks: Applications and trends

K Bochie, MS Gilbert, L Gantert, MSM Barbosa… - Journal of Network and …, 2021 - Elsevier
Computer networks are dealing with growing complexity, given the ever-increasing volume
of data produced by all sorts of network nodes. Performance improvements are a non-stop …