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Advances in Vehicular Networks
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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.

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Keywords

  • 5G
  • 5G networks
  • AODV
  • Automotive
  • C-RAN
  • collision probability
  • Connected vehicles
  • convolutional neural networks
  • Cooperative driving
  • damper
  • deep learning
  • Diagnosis
  • edge computing
  • end-to-end delay
  • fault detection
  • field trials
  • Fresnel lenses
  • History of engineering & technology
  • infrastructure-to-vehicle
  • intelligent transportation systems
  • Machine learning
  • n/a
  • optimization
  • packet loss ratio
  • Pedestrian
  • probabilistic flooding
  • reconfigurable meta-surface
  • Resource allocation
  • Safety
  • smart environment
  • smart vehicles
  • Technology, engineering, agriculture
  • Technology: general issues
  • throughput
  • VANET
  • vehicle-to-everything communication
  • vehicle-to-vehicle
  • Vehicles
  • vehicular communication
  • Vehicular networks
  • visible light communication
  • visible light communications
  • vulnerable road user detection

Links

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

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