Investigating remote driving over the LTE network

Ruilin Liu, Daehan Kwak, Srinivas Devarakonda, Kostas Bekris, Liviu Iftode

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations

Abstract

Remote driving brings human operators with sophisticated perceptual and cognitive skills into an over-the-network control loop, with the hope of addressing the challenging aspects of vehicular autonomy based exclusively on artificial intelligence (AI). This paper studies the human behavior in a remote driving setup, i.e., how human remote drivers perform and assess their workload under the state-of-the-art network conditions. To explore this, we build a scaled remote driving prototype and conduct a controlled human study with varying network delays based on current commercial LTE network technology. The study demonstrates that remote driving over LTE is not immediately feasible, primarily caused by network delay variability rather than delay magnitude. In addition, our findings indicate that the negative effects of remote driving over LTE can be mitigated by a video frame arrangement strategy that regulates delay magnitude to achieve a smoother display.

Original languageEnglish (US)
Title of host publicationAutomotiveUI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Proceedings
PublisherAssociation for Computing Machinery, Inc
Pages264-269
Number of pages6
ISBN (Electronic)9781450351508
DOIs
StatePublished - Sep 24 2017
Event9th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2017 - Oldenburg, Germany
Duration: Sep 24 2017Sep 27 2017

Publication series

NameAutomotiveUI 2017 - 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, Proceedings

Other

Other9th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2017
Country/TerritoryGermany
CityOldenburg
Period9/24/179/27/17

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Software
  • Automotive Engineering

Keywords

  • Feedback delay
  • Human-vehicle interaction
  • Remote driving

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