人工智能(AI)在单驾驶员操作商用飞机设计中的实现

Dimitrios Ziakkas, K. Pechlivanis, Abner Del Cid Flores
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The\n progression of events in the field of commercial air transport can be broken\n down into three distinct stages:•First step: crew assistance/ augmentation\n (2022-2025)•Second step: human/ machine collaboration (2025-2030)•Third\n step: autonomous commercial air transport (2035+)There have been identified\n two different operational concepts:Extended Minimum-Crew Operations (eMCOs),\n formerly known as \"Reduced Crew Operations,\" in which single-pilot\n operations are permitted during the cruise phase of the flight with a level\n of safety similar to that of today's two-pilot operations (to be implemented\n beginning in the year 2025).Single-Pilot Operations (SiPOs), in which, at a\n later stage, end-to-end single-pilot operations might be allowed, also based\n on a level of safety equivalent to today's two-pilot operations, to be\n implemented as of the year 2030. Single-Pilot Operations (SiPOs), in which,\n at a later stage, end-to-end single-pilot operations might be allowed.The\n proposed artificial intelligence aviation decision-making research in\n cockpit design and users' experience was constructed by first surveying the\n current literature about Artificial Intelligence (AI). The findings point to\n the difficulties artificial intelligence poses, including its limitations\n and users' resistance, in shifting from multi-crew operations to e-MCO and\n SiPO. This resistance to change should be considered when designing any\n potential upgrades to the AI cockpit design or user interactions. However,\n the existing commercially available  AI technology may be ready to serve\n some low-impact or non-time-critical applications (for example, weather in\n destination and alternate airports update during the cruise phase) in this\n transitional period to eMCOs and SiPOs, which would postpone the necessity\n for a complete flight deck redesign at this time (Stanton & Harris,\n 2015). 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引用次数: 0

摘要

本研究旨在展示、识别和提出人工智能技术在航空决策中的实施,并研究人工智能如何影响从多机组向eMCO和SiPO的过渡,其基本原理是,单飞行员操作员以及时和自然交互的方式获得可访问的数据可以增强自然决策(NDM) (Klein, 2008;Orasanu & Fischer, 1997)。根据工业路线图,第一个飞行员辅助认证预计将在2025年出现,随后将在2035年左右逐步过渡到完全自主。商业航空运输领域的事件进展可以分为三个不同的阶段:•第一步:机组人员协助/增强(2022-2025)•第二步:人机协作(2025-2030)•第三步:目前已经确定了两种不同的操作概念:扩展最小机组操作(eMCOs),以前称为“减少机组操作”,其中在飞行的巡航阶段允许单飞行员操作,其安全级别类似于今天的双飞行员操作(将于2025年开始实施)。单先导作业(SiPOs),在后期阶段可能允许端到端单先导作业,其安全水平相当于目前的双先导作业,将于2030年实施。单导操作(SiPOs),在此操作中,在后期阶段可能允许端到端单导操作。本文首先通过对人工智能相关文献的梳理,构建了基于座舱设计和用户体验的人工智能航空决策研究。研究结果指出了人工智能在从多人员操作转向电子管理和知识产权局时所带来的困难,包括其局限性和用户的抵制。在设计AI座舱设计或用户交互的任何潜在升级时,应该考虑到这种变化的阻力。然而,在向emco和SiPOs过渡期间,现有的商用人工智能技术可能已经准备好服务于一些低影响或非时间关键型应用(例如,目的地天气和巡航阶段备用机场的更新),这将推迟此时完全重新设计飞行甲板的必要性(Stanton & Harris, 2015)。将人工智能用于系统管理和信息检索有可能提高飞行员的感知(一级SA)和理解(二级SA) (Endsley, 1995)。因此,在NDM驾驶舱环境中,单飞行员的人类操作员能够以一种自然参与的方式迅速获取数据,从而能够在NDM环境中做出更令人满意和更接近最佳的判断(Klein, 2008;Orasanu & Fischer, 1997)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence (AI) implementation in the Design of Single Pilot Operations Commercial Airplanes
This research aims to present, identify, and propose the implementation of AI technology in aviation decision-making, as well as examine how AI can affect the transition from multi-crew to eMCO and SiPO, based on the rationale that the single-pilot human operator having accessible data in a timely and naturally interactive fashion could enhance natural decision making (NDM) (Klein, 2008; Orasanu & Fischer, 1997).According to the industrial roadmaps, the first certification of assistance for pilots is anticipated to occur in the year 2025, and this will be followed by a gradual transition to full autonomy sometime around the year 2035. The progression of events in the field of commercial air transport can be broken down into three distinct stages:•First step: crew assistance/ augmentation (2022-2025)•Second step: human/ machine collaboration (2025-2030)•Third step: autonomous commercial air transport (2035+)There have been identified two different operational concepts:Extended Minimum-Crew Operations (eMCOs), formerly known as "Reduced Crew Operations," in which single-pilot operations are permitted during the cruise phase of the flight with a level of safety similar to that of today's two-pilot operations (to be implemented beginning in the year 2025).Single-Pilot Operations (SiPOs), in which, at a later stage, end-to-end single-pilot operations might be allowed, also based on a level of safety equivalent to today's two-pilot operations, to be implemented as of the year 2030. Single-Pilot Operations (SiPOs), in which, at a later stage, end-to-end single-pilot operations might be allowed.The proposed artificial intelligence aviation decision-making research in cockpit design and users' experience was constructed by first surveying the current literature about Artificial Intelligence (AI). The findings point to the difficulties artificial intelligence poses, including its limitations and users' resistance, in shifting from multi-crew operations to e-MCO and SiPO. This resistance to change should be considered when designing any potential upgrades to the AI cockpit design or user interactions. However, the existing commercially available  AI technology may be ready to serve some low-impact or non-time-critical applications (for example, weather in destination and alternate airports update during the cruise phase) in this transitional period to eMCOs and SiPOs, which would postpone the necessity for a complete flight deck redesign at this time (Stanton & Harris, 2015). The utilization of AI for the administration of systems and the retrieval of information has the potential to improve both the perception (Level 1 SA) and comprehension (Level 2 SA) of pilots (Endsley, 1995). Therefore, the single-pilot human operator in the NDM cockpit environment who has data accessible promptly and in a naturally engaging fashion would be able to make judgments that are more fulfilling and closer to optimums in the NDM environment (Klein, 2008; Orasanu & Fischer, 1997).
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