4.6 Article

A Digital Twin-Based Platform towards Intelligent Automation with Virtual Counterparts of Flight and Air Traffic Control Operations

期刊

APPLIED SCIENCES-BASEL
卷 11, 期 22, 页码 -

出版社

MDPI
DOI: 10.3390/app112210923

关键词

digital twin; intelligent automation; collaborative decision making; shared situational awareness; air transport operations

资金

  1. Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong SAR [AAE07]
  2. Undergraduate Research and Innovation Scheme (URIS) of The Hong Kong Polytechnic University [TA20]
  3. [2021/22 (AAE07)]

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This study successfully established a collaborative decision-making training platform using the CPS concept to integrate flight and air traffic control operations, demonstrating system reliability and performance through performance analysis.
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 decision-making 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.

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