Reprint

Advances in Vehicular Networks

Edited by
January 2021
138 pages
  • ISBN978-3-03943-799-3 (Hardback)
  • ISBN978-3-03943-800-6 (PDF)

This is a Reprint of the Special Issue Advances in Vehicular Networks that was published in

Computer Science & Mathematics
Engineering
Physical Sciences
Summary
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.
Format
  • Hardback
License and Copyright
© 2021 by the authors; CC BY-NC-ND license
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; vehicular networks; 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