A survey on deep learning-based vehicular communication applications

CH Lin, YC Lin, YJ Wu, WH Chung, TS Lee - Journal of Signal Processing …, 2021 - Springer
Besides the use of information transmission, vehicular communications also perform an
essential role in intelligent transportation systems (ITS) for exchanging critical driving …

Introducing intelligence in vehicular ad hoc networks using machine learning algorithms

I Seth, K Guleria, SN Panda - ECS Transactions, 2022 - iopscience.iop.org
The automotive industry has gained popularity in the past decade, leading to tremendous
advancements in intelligent vehicular networks. The increase in the number of vehicles on …

[PDF][PDF] Harnessing machine learning for next-generation intelligent transportation systems: a survey

T Yuan, WB da Rocha Neto… - Proceedings of the …, 2019 - intrig.dca.fee.unicamp.br
Abstract Intelligent Transportation Systems, or ITS for short, includes a variety of services
and applications such as road traffic management, traveler information systems, public …

Deep reinforcement learning techniques for vehicular networks: Recent advances and future trends towards 6G

A Mekrache, A Bradai, E Moulay, S Dawaliby - Vehicular Communications, 2022 - Elsevier
Employing machine learning into 6G vehicular networks to support vehicular application
services is being widely studied and a hot topic for the latest research works in the literature …

Routing using reinforcement learning in vehicular ad hoc networks

M Saravanan, P Ganeshkumar - Computational Intelligence, 2020 - Wiley Online Library
In vehicular ad hoc networks (VANETs), the frequent change in vehicle mobility creates
dynamic changes in communication link and topology of the network. Hence, the key …

A probabilistic neural network-based road side unit prediction scheme for autonomous driving

N Aljeri, A Boukerche - ICC 2019-2019 IEEE International …, 2019 - ieeexplore.ieee.org
Vehicular Networks will play a leading role in the next generation of Autonomous Driving
(AD), as recent advances in vehicular networks are a promising solution for traffic …

[图书][B] Machine learning: theory to applications

SL Mirtaheri, R Shahbazian - 2022 - taylorfrancis.com
The book reviews core concepts of machine learning (ML) while focusing on modern
applications. It is aimed at those who want to advance their understanding of ML by …

Federated learning in vehicular networks: Opportunities and solutions

J Posner, L Tseng, M Aloqaily, Y Jararweh - IEEE Network, 2021 - ieeexplore.ieee.org
The emerging advances in personal devices and privacy concerns have given the rise to the
concept of Federated Learning. Federated Learning proves its effectiveness and privacy …

Machine learning for next‐generation intelligent transportation systems: A survey

T Yuan, W da Rocha Neto… - Transactions on …, 2022 - Wiley Online Library
Intelligent transportation systems, or ITS for short, includes a variety of services and
applications such as road traffic management, traveler information systems, public transit …

How to train your ITS? Integrating machine learning with vehicular network simulation

M Schettler, DS Buse, A Zubow… - 2020 IEEE Vehicular …, 2020 - ieeexplore.ieee.org
Machine Learning (ML) is becoming ever more popular in many application domains,
including vehicular networking. It has been shown already that Intelligent Transportation …