Resilient Raw Format Live Video Streaming Framework for an Automated Driving System on an Ethernet-Based In-Vehicle Network

Kyungmin Go, Donghoon Shin

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The automotive Ethernet is an emerging area for exploiting the high network bandwidth and scalable network design in automated driving systems. Low-latency live video streaming over the automotive Ethernet is a challenging part of this concept because of its significance for driving situation awareness in real time. In order to achieve low-latency live video streaming on resource-constrained automotive electric control units, the streaming needs to be conducted with a fine-grained resource control. This article proposes a raw format live video streaming framework that resiliently controls the number of raw format video packets with consideration of available CPU resources. The evaluation on a testbed demonstrates that the proposed framework achieves low-latency live video streaming by securing available CPU resources.

Original languageEnglish
Pages (from-to)144364-144376
Number of pages13
JournalIEEE Access
Volume11
DOIs
StatePublished - 2023

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Automotive ethernet
  • autonomous driving
  • embedded system
  • low-latency
  • raw format live video streaming

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