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 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 and effective retrieval of procedure information. 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.

翻译：技术进步、飞行员短缺及成本压力正推动航空业向单驾驶员甚至远程操作模式发展。考虑到单驾驶员操作中繁重的工作量及巨大风险，开发虚拟副驾驶（V-CoP）有望成为保障航空安全的潜在途径。本研究提出V-CoP概念，并探索人类与虚拟助理有效协作的方式。通过初步案例研究，本文利用多模态大语言模型（LLM）探讨了V-CoP的关键角色——即自动化快速程序搜索功能。基于LLM的V-CoP整合飞行员指令与实时驾驶舱仪表数据，以触发适用的航空手册与操作程序。结果表明，基于LLM的V-CoP在情境分析（90.5%）和程序信息有效检索（86.5%）方面均实现了高准确率。所提出的V-CoP有望为未来虚拟智能助手开发奠定基础，提升单驾驶员操作效能，并降低航空领域中人为失误的风险。