Object Detection Performance According to Packet Loss of C-V2X

Eunmin Choi, Dongyoon Kwon, Kyungtae Kim, Ji Woong Choi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Studies on vehicle-to-everything (V2X) and edge computing to provide autonomous driving services mainly focus on low latency. However, in order to provide driving safety, it is also important to evaluate the performance considering the reliability of communication. In this paper, we evaluate the object detection performance according to the packet loss of V2X communication when transmitting video frames in consideration of the environment where camera sensor data is transmitted from the vehicle to the edge computer to recognize and judge.

Original languageEnglish
Title of host publicationICUFN 2022 - 13th International Conference on Ubiquitous and Future Networks
PublisherIEEE Computer Society
Pages228-232
Number of pages5
ISBN (Electronic)9781665485500
DOIs
StatePublished - 2022
Event13th International Conference on Ubiquitous and Future Networks, ICUFN 2022 - Virtual, Barcelona, Spain
Duration: 5 Jul 20228 Jul 2022

Publication series

NameInternational Conference on Ubiquitous and Future Networks, ICUFN
Volume2022-July
ISSN (Print)2165-8528
ISSN (Electronic)2165-8536

Conference

Conference13th International Conference on Ubiquitous and Future Networks, ICUFN 2022
Country/TerritorySpain
CityVirtual, Barcelona
Period5/07/228/07/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Vehicle-to-everything
  • deep learning
  • detection performance
  • object detection
  • packet error rate
  • video data transmission

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