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 …
autonomous vehicles. Vehicle-to-Everything (V2X) communications enable the provisioning …
AI-driven, QoS prediction for V2X communications in beyond 5G systems
On the eve of 5G-enabled Connected and Automated Mobility, challenging Vehicle-to-
Everything services have emerged towards safer and automated driving. The requirements …
Everything services have emerged towards safer and automated driving. The requirements …
Platoonsafe: An integrated simulation tool for evaluating platoon safety
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 …
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 …
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 …
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
5G cellular communication and Multi-access Edge Computing (MEC) have provided a new
opportunity to support connected vehicles safety applications complementing Dedicated …
opportunity to support connected vehicles safety applications complementing Dedicated …
CAV-enabled data analytics for enhancing adaptive signal control safety environment
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 …
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
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 …
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 …
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
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 …
applications. Under MEC, a vehicle has the option to offload computationally intensive tasks …