Advances in Vehicular Networks

Advances in Vehicular Networks

Connected and automated vehicles have revolutionized the way we move, granting new services on roads. This Special Issue collects contributions that address reliable and ultra-low-latency vehicular applications that range from advancements at the access layer, such as using the visible light spectru...

Descripción completa

Detalles Bibliográficos
Otros Autores: Masini, Barbara Mavì (Editor), Silva, Cristiano M. (Otro), Balador, Ali
Formato: Libro electrónico
Idioma:Inglés
Publicado: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Materias:
History of engineering & technology
vehicular networks
5G
C-RAN
resource allocation
edge computing
optimization
vehicle-to-everything communication
pedestrian
vehicles
safety
automotive
damper
convolutional neural networks
fault detection
diagnosis
machine learning
deep learning
connected vehicles
reconfigurable meta-surface
smart environment
cooperative driving
vulnerable road user detection
collision probability
probabilistic flooding
vehicular communication
visible light communications
5G networks
smart vehicles
field trials
infrastructure-to-vehicle
vehicle-to-vehicle
Intelligent Transportation Systems
Visible Light Communication
Fresnel lenses
AODV
end-to-end delay
packet loss ratio
throughput
VANET
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009654847606719
Descripción
Sumario:Connected and automated vehicles have revolutionized the way we move, granting new services on roads. This Special Issue collects contributions that address reliable and ultra-low-latency vehicular applications that range from advancements at the access layer, such as using the visible light spectrum to accommodate ultra-low-latency applications, to data dissemination solutions. Further, articles discuss edge computing, neural network-based techniques, and the use of reconfigurable intelligent surfaces (RIS) to boost throughput and enhance coverage.
Descripción Física:1 electronic resource (138 p.)
Acceso:Open access

Ejemplares similares