FusionEye: Perception Sharing for Connected Vehicles and its Bandwidth-Accuracy Trade-offs

Hansi Liu, Pengfei Ren, Shubham Jain, Mohannad Murad, Marco Gruteser, Fan Bai

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

4 Scopus citations

Abstract

Automated driving and advanced driver assistance systems benefit from complete understandings of traffic scenes around vehicles. Existing systems gather such data through cameras and other sensors in vehicles but scene understanding can be limited due to the sensing range of sensors or occlusion from other objects. To gather information beyond the view of one vehicle, we propose and explore FusionEye-a connected vehicle system that allows multiple vehicles to share perception data over vehicle-to-vehicle communications and collaboratively merge this data into a more complete traffic scene. FusionEye uses a self-adaptive topology merging algorithm based on bipartite graph. We explore its network bandwidth requirements and the trade-off with merging accuracy. Experimental results show that FusionEye creates more complete scenes and achieves a merging accuracy of 88% with 5% packet drop rate and transmission latency around 200ms. We show that richer vehicle descriptors offer only marginal accuracy improvements compared to lower communication overhead options.

Original languageEnglish (US)
Title of host publication2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2019
PublisherIEEE Computer Society
ISBN (Electronic)9781728112077
DOIs
StatePublished - Jun 2019
Event16th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2019 - Boston, United States
Duration: Jun 10 2019Jun 13 2019

Publication series

NameAnnual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks workshops
Volume2019-June
ISSN (Print)2155-5486
ISSN (Electronic)2155-5494

Conference

Conference16th Annual IEEE International Conference on Sensing, Communication, and Networking, SECON 2019
Country/TerritoryUnited States
CityBoston
Period6/10/196/13/19

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Keywords

  • ADAS
  • Connected Vehicles
  • Vehicle Verification

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