2023
DOI: 10.1109/ojvt.2022.3226606
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On Scalable Network Communication for Infrastructure-Vehicle Collaborative Autonomous Driving

Abstract: Emerging topics such as environmental protection and energy utilization have pushed research and development of electric vehicles and hybrid electric vehicles (EVs/HEVs). In the last few decades, numerous technologies have been developed for EV/HEV importance. In this article, key research topics in the area of EVs/HEVs, namely electric machines, electrochemical energy sources, wireless charging infrastructure, and latest EV/HEV models are covered. This paper aims to consolidate the key emerging technologies i… Show more

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Cited by 3 publications
(2 citation statements)
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“…Network coding has found immense relevance in sparse networks [17,18], where the end-to-end path from source to destination may be absent or difficult to form; for example, in Ref. [17], due to their high design and manufacturing costs, sensor nodes in underwater wireless sensor networks (UWSNs) are sparingly dispersed throughout a broad sea region.…”
Section: Related Workmentioning
confidence: 99%
“…Network coding has found immense relevance in sparse networks [17,18], where the end-to-end path from source to destination may be absent or difficult to form; for example, in Ref. [17], due to their high design and manufacturing costs, sensor nodes in underwater wireless sensor networks (UWSNs) are sparingly dispersed throughout a broad sea region.…”
Section: Related Workmentioning
confidence: 99%
“…Their work emphasizes the importance of optimizing communication protocols and architectures. Moreover, Yang et al [26] studied infrastructure-vehicle collaborative autonomous driving, considering scenarios with a large number of RSUs and vehicles, providing insights into the design and deployment of large-scale V2X networks. Jia et al [27] demonstrated the benefits of infrastructure-assisted collaborative perception in automated valet parking, improving safety and increasing the maximum safe cruising speed.…”
Section: Infrastructure-assisted Autonomous Drivingmentioning
confidence: 99%