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Research on the Principle and Technology of a Collaborative Information Transparency Diagnosis System for Aviation Formations

  • Xiaoxiang Wu
  • , Mengmeng Gao
  • , Liping Pang*
  • , Ning Li
  • , Deqiang Fu
  • *Corresponding author for this work
  • Beihang University
  • China CDC

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

Abstract

Human society is entering the era of intelligence, and the cognitive, interactive, and autonomous functions of intelligent agents are gradually increasing. Intelligent assistance is also gradually being applied in the aviation field. Aviation formation collaboration is one of the important combat methods in the future. However, existing drones are difficult to make accurate judgments and decisions independently, and cannot gain sufficient trust from operators during task execution, leading to frequent collaboration problems and negative impacts on work efficiency and mission results. At present, the mechanism of collaboration in aviation formations is still unclear, and higher levels of intelligence in aviation formations also need to be developed. This article starts with the transparency of information in aviation formation collaboration and elaborates on the impact of information transparency on aviation formation collaboration. In typical collaboration scenarios, an information transparency diagnosis system is established to timely discover the reasons for collaboration mismatch and provide solutions to improve collaboration efficiency and stability.

Original languageEnglish
Title of host publicationMan-Machine-Environment System Engineering - Proceedings of the 24th Conference on MMESE
EditorsShengzhao Long, Balbir S. Dhillon, Long Ye
PublisherSpringer Science and Business Media Deutschland GmbH
Pages838-843
Number of pages6
ISBN (Print)9789819771387
DOIs
StatePublished - 2024
Event24th Conference on Man-Machine-Environment System Engineering, MMESE 2024 - Beijing, China
Duration: 18 Oct 202420 Oct 2024

Publication series

NameLecture Notes in Electrical Engineering
Volume1256 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference24th Conference on Man-Machine-Environment System Engineering, MMESE 2024
Country/TerritoryChina
CityBeijing
Period18/10/2420/10/24

Keywords

  • Human machine collaboration‧System diagnosis‧Information transparency

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