A Performance Study of Hierarchical Lossless Compression Method for CAN Data in an Urban Network

DOI

Bibliographic Information

Other Title
  • 都市交通網におけるCAN データの階層的可逆圧縮の性能評価

Abstract

It is expected to realize safer autonomous driving control by collecting CAN data from autonomous vehicles in a Cyber-Physical System to achieve advanced self-driving. Therefore, real-time CAN data collection from autonomous vehicles to CPS is one of the most challenging problems in the current IoT. In this paper, I propose an MEC (Multi-access Edge Computing) enhanced network Redundancy Elimination service for CAN data collection. As a result of simulation evaluation, the proposed method can reduce the network traffic of CAN data by 63.2% in the mobile network and by 86.9% in the Internet.

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Keywords

Details 詳細情報について

  • CRID
    1390580561420871680
  • DOI
    10.11351/jsaeronbun.55.308
  • ISSN
    18830811
    02878321
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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