Demo: Enabling Efficient Perception Sharing via Infrastructure-to-Road Beamforming

Chenhao Wu, Youdong Wang, Jun Huang, Guoliang Xing

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

1 Citation (Scopus)
12 Downloads (CityUHK Scholars)

Abstract

Sharing the sensor data collected by roadside infrastructure is an emerging paradigm for extending the perception of autonomous vehicles and improving driving safety. However, enabling perception sharing is challenging due to the high data rate of perception data, which incurs significant communication overhead. Previous systems have relied on Infrastructure-to-Vehicle (I2V) communication, which is susceptible to high mobility and scales poorly with traffic density. This demo presents Infrastructure-to-Road (I2R) beam-forming, a new paradigm that enables efficient perception sharing for infrastructure-assisted autonomous driving. We demonstrate BeamDrop, a prototype that strategically beamforms tailored point cloud segments to geographic cells, allowing a receiver that enters a cell to receive the needed navigation data without the overhead of coordinating with the infrastructure to adapt beamforming under mobility. © 2024 Copyright held by the owner/author(s).
Original languageEnglish
Title of host publicationACM SIGCOMM Posters and Demos '24: Proceedings of the ACM SIGCOMM 2024 Conference: Posters and Demos
PublisherAssociation for Computing Machinery
Pages89-91
ISBN (Print)9798400707179
DOIs
Publication statusPublished - Aug 2024
Event2024 Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM 2024) - University of New South Wales, Sydney, Australia
Duration: 4 Aug 20248 Aug 2024
Conference number: 38
https://conferences.sigcomm.org/sigcomm/2024/

Publication series

NameSIGCOMM Posters and Demos - Proceedings of the SIGCOMM Poster and Demo Sessions, Part of: SIGCOMM

Conference

Conference2024 Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM 2024)
Country/TerritoryAustralia
CitySydney
Period4/08/248/08/24
Internet address

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Funding

We sincerely thank the anonymous reviewers for their valuable feedback and constructive suggestions. This work is supported in part by the Research Grants Council (RGC) of Hong Kong under General Research Fund No. 14222222.

Research Keywords

  • infrastructure-assisted autonomous driving
  • smart roadside infrastructure
  • V2X

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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