Advances in Vehicular Networks

doi:10.3390/books978-3-03943-800-6

Book License

Download Url(s)

https://mdpi.com/books/pdfview/book/3266

Contributor(s)

Masini, Barbara Mavì (editor)

Silva, Cristiano M. (editor)

Balador, Ali (editor)

Language

English

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Abstract

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.

URI

https://directory.doabooks.org/handle/20.500.12854/68269

Keywords

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; n/a