A digital twin-based platform towards intelligent automation with virtual counterparts of flight and air traffic control operations

Cho Yin Yiu, Kam K.H. Ng, Ching Hung Lee, Chun Ting Chow, Tsz Ching Chan, Kwok Chun Li, Ka Yeung Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Automation technologies have been deployed widely to boost the efficiency of production and operations, to trim the complicated process, and to reduce the human error involved. Nevertheless, aviation remains human-centred and requires collaboration between different parties. Given the lack of a collaborative decision-making training platform for air traffic operations in the industry, this study utilises the concept of cyber-physical systems (CPS) to formulate a system architecture for pilots and air traffic control officers training in collaborative decision making by linking and integrating the virtual counterparts of flights and air traffic control operations. Collaborative decisionmaking training and the corresponding intelligent automation aids could be realised and supported. A performance analysis via a flight task undertaken with different computational load settings was prepared to evaluate the platform’s latency and integrity. The latency is presented using its 95% confidence interval, and integrity is presented using the percentage of data loss during wireless transmission. The results demonstrated convincing performance and a promising system robustness in both domains.

Original languageEnglish
Article number10923
JournalApplied Sciences (Switzerland)
Volume11
Issue number22
DOIs
Publication statusPublished - 18 Nov 2021

Keywords

  • Air transport operations
  • Collaborative decision making
  • Digital twin
  • Intelligent automation
  • Shared situational awareness

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

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