TY  - GEN
AU  - Masini,Barbara Mavì
AU  - Silva,Cristiano M.
AU  - Balador,Ali
AU  - Masini,Barbara Mavì
AU  - Silva,Cristiano M.
AU  - Balador,Ali
TI  - Advances in Vehicular Networks
SN  - books978-3-03943-800-6
PY  - 2021///
CY  - Basel, Switzerland
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - History of engineering & technology
KW  - bicssc
KW  - vehicular networks
KW  - 5G
KW  - C-RAN
KW  - resource allocation
KW  - edge computing
KW  - optimization
KW  - vehicle-to-everything communication
KW  - pedestrian
KW  - vehicles
KW  - safety
KW  - automotive
KW  - damper
KW  - convolutional neural networks
KW  - fault detection
KW  - diagnosis
KW  - machine learning
KW  - deep learning
KW  - connected vehicles
KW  - reconfigurable meta-surface
KW  - smart environment
KW  - cooperative driving
KW  - vulnerable road user detection
KW  - collision probability
KW  - probabilistic flooding
KW  - vehicular communication
KW  - visible light communications
KW  - 5G networks
KW  - smart vehicles
KW  - field trials
KW  - infrastructure-to-vehicle
KW  - vehicle-to-vehicle
KW  - Intelligent Transportation Systems
KW  - Visible Light Communication
KW  - Fresnel lenses
KW  - AODV
KW  - end-to-end delay
KW  - packet loss ratio
KW  - throughput
KW  - VANET
KW  - n/a
N1  - Open Access
N2  - 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
UR  - https://mdpi.com/books/pdfview/book/3266
UR  - https://directory.doabooks.org/handle/20.500.12854/68269
ER  -