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Virtual Co-Pilot: Multimodal Large Language Model-enabled Quick-access Procedures for Single Pilot Operations

  • Fan Li
  • , Shanshan Feng
  • , Yuqi Yan
  • , Ching Hung Lee
  • , Yew Soon Ong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Advancements in technology, pilot shortages, and cost pressures are driving a trend towards single-pilot and even remote operations in aviation. Considering the extensive workload and huge risks associated with single-pilot operations, the development of a Virtual Co-Pilot (V-CoP) is expected to be a potential way to ensure aviation safety. This study proposes a V-CoP concept and explores how humans and virtual assistants can effectively collaborate. A preliminary case study is conducted to explore a critical role of V-CoP, namely automated quick procedures searching, using the multimodal large language model (LLM). The LLM-enabled V-CoP integrates the pilot's instruction and real-time cockpit instrumental data to prompt applicable aviation manuals and operation procedures. The results showed that the LLM-enabled V-CoP achieved high accuracy in situational analysis (90.5%) and effective retrieval of procedure information (86.5%). The proposed V-CoP is expected to provide a foundation for future virtual intelligent assistant development, improve the performance of single pilots, and reduce the risk of human errors in aviation.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE Conference on Artificial Intelligence, CAI 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1501-1506
Number of pages6
ISBN (Electronic)9798350354096
DOIs
Publication statusPublished - 2024
Event2nd IEEE Conference on Artificial Intelligence, CAI 2024 - Singapore, Singapore
Duration: 25 Jun 202427 Jun 2024

Publication series

NameProceedings - 2024 IEEE Conference on Artificial Intelligence, CAI 2024

Conference

Conference2nd IEEE Conference on Artificial Intelligence, CAI 2024
Country/TerritorySingapore
CitySingapore
Period25/06/2427/06/24

Keywords

  • Aviation
  • human-AI collaboration
  • large language model
  • virtual assistant

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Modelling and Simulation

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