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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/books978-3-03943-800-6Editions