Artificial Intelligence and Machine Learning as key enablers for V2X communications: A comprehensive survey

M Christopoulou, S Barmpounakis, H Koumaras… - Vehicular …, 2023 - Elsevier
The automotive industry is undergoing a profound digital transformation to create
autonomous vehicles. Vehicle-to-Everything (V2X) communications enable the provisioning …

AI-driven, QoS prediction for V2X communications in beyond 5G systems

S Barmpounakis, N Maroulis, N Koursioumpas… - Computer Networks, 2022 - Elsevier
On the eve of 5G-enabled Connected and Automated Mobility, challenging Vehicle-to-
Everything services have emerged towards safer and automated driving. The requirements …

Platoonsafe: An integrated simulation tool for evaluating platoon safety

S Hasan, J Gorospe, S Girs, AA Gómez… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Platooning is highly tractable for enabling fuel savings for autonomous and semi-
autonomous cars and trucks. Safety concerns are one of the main impediments that need to …

LSTM-based QoS prediction for 5G-enabled Connected and Automated Mobility applications

S Barmpounakis, L Magoula… - 2021 IEEE 4th 5G …, 2021 - ieeexplore.ieee.org
Determining whether the network can provide the required resources-and as a result the
required Quality of Service (QoS)-for Connected and Automated Mobility (CAM) applications …

Informer-based QoS prediction for V2X communication: A method with verification using reality field test data

Y Xu, Y Shi, Y Ge, S Chen, L Wang - Computer Networks, 2023 - Elsevier
Abstract Vehicle-to-everything (V2X) communication plays a critical role in connected and
automated driving applications, which requires strict Quality of Service (QoS) performance in …

Raven: Vision-Based Connected Vehicle Safety Platform Using Infrastructure Sensing, 5 G, and MEC

K Ali, B Yu, VV Kumar, K Hariharan… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
5G cellular communication and Multi-access Edge Computing (MEC) have provided a new
opportunity to support connected vehicles safety applications complementing Dedicated …

CAV-enabled data analytics for enhancing adaptive signal control safety environment

W Lin, H Wei - Accident Analysis & Prevention, 2023 - Elsevier
Given the connected and autonomous vehicle (CAV) generated trajectories as a “floating
sensor” data source to obtain high resolution CAV-generated mobility data at intersections …

Predictive Modeling of Delay in an LTE Network by Optimizing the Number of Predictors Using Dimensionality Reduction Techniques

M Stojčić, MK Banjanin, M Vasiljević, D Nedić… - Applied Sciences, 2023 - mdpi.com
Delay in data transmission is one of the key performance indicators (KPIs) of a network. The
planning and design value of delay in network management is of crucial importance for the …

Resource Demand Prediction for Network Slices in 5G using ML Enhanced with Network Models

LA Garrido, A Dalgkitsis, K Ramantas… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The new technologies introduced by 5G, such as network slicing, will improve the
capabilities of Vehicle-to-Vehicle (V2V) communications, enabling the introduction of a new …

Latency Estimation and Computational Task Offloading in Vehicular Mobile Edge Computing Applications

W Zhang, M Feng, M Krunz - IEEE Transactions on Vehicular …, 2023 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a key enabler of time-critical vehicle-to-everything (V2X)
applications. Under MEC, a vehicle has the option to offload computationally intensive tasks …