Content adaptive video compression for autonomous vehicle remote driving

Itai Dror, Raz Birman, Oren Solomon, Tomer Zehavi, Lior Taib, Amit Doran, Roee Ezra, Noui Rengenzad, Ofer Hadar

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

Abstract

It is anticipated that in some extreme situations, autonomous cars will benefit from the intervention of a "Remote Driver". The vehicle computer may discover a failure and decide to request remote assistance for safe roadside parking. In a more extreme scenario, the vehicle may require a complete remote-driver takeover due to malfunctions or an inability to resolve unknown decision logic. In such cases, the remote driver will need a sufficiently good quality real-time video stream of the vehicle cameras to respond quickly and accurately enough to the situation at hand. Relaying such a video stream to the remote Command and Control (C&C) center is especially challenging when considering the varying wireless channel bandwidths expected in these scenarios. This paper proposes an innovative end-to-end content-sensitive video compression scheme to allow efficient and satisfactory video transmission from autonomous vehicles to the remote C&C center.

Original languageEnglish
Title of host publicationApplications of Digital Image Processing XLIV
EditorsAndrew G. Tescher, Touradj Ebrahimi
PublisherSPIE
ISBN (Electronic)9781510645226
DOIs
StatePublished - 1 Jan 2021
EventApplications of Digital Image Processing XLIV 2021 - San Diego, United States
Duration: 1 Aug 20215 Aug 2021

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11842
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceApplications of Digital Image Processing XLIV 2021
Country/TerritoryUnited States
CitySan Diego
Period1/08/215/08/21

Keywords

  • Autonomous cars
  • Driving Simulator
  • HEVC
  • Photorealistic
  • Region of Interest
  • Remote Driver
  • Video Compression

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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