Multi-agent Collaborative Perception for Autonomous Driving: Unsettled Aspects

EPR2023017

08/15/2023

Features
Authors Abstract
Content
This report delves into the field of multi-agent collaborative perception (MCP) for autonomous driving: an area that remains unresolved. Current single-agent perception systems suffer from limitations, such as occlusion and sparse sensor observation at a far distance.
Multi-agent Collaborative Perception for Autonomous Driving: Unsettled Aspects addresses three unsettled topics that demand immediate attention:
  • Establishing normative communication protocols to facilitate seamless information sharing among vehicles
  • Defining collaboration strategies, including identifying specific collaboration projects, partners, and content, as well as establishing the integration mechanism
  • Collecting sufficient data for MCP model training, including capturing diverse modal data and labeling various downstream tasks as accurately as possible
Meta TagsDetails
DOI
https://doi.org/10.4271/EPR2023017
Pages
26
Citation
Chen, G., "Multi-agent Collaborative Perception for Autonomous Driving: Unsettled Aspects," SAE Research Report EPR2023017, 2023, https://doi.org/10.4271/EPR2023017.
Additional Details
Publisher
Published
Aug 15, 2023
Product Code
EPR2023017
Content Type
Research Report
Language
English