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Human Computer Interactions in Next-Generation of Aircraft Smart Navigation Management Systems: Task Analysis and Architecture under an Agent-Oriented Methodological Approach

机译:下一代飞机智能导航管理系统中的人机交互:面向代理的方法论方法下的任务分析和体系结构

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The limited efficiency of current air traffic systems will require a next-generation of Smart Air Traffic System (SATS) that relies on current technological advances. This challenge means a transition toward a new navigation and air-traffic procedures paradigm, where pilots and air traffic controllers perform and coordinate their activities according to new roles and technological supports. The design of new Human-Computer Interactions (HCI) for performing these activities is a key element of SATS. However efforts for developing such tools need to be inspired on a parallel characterization of hypothetical air traffic scenarios compatible with current ones. This paper is focused on airborne HCI into SATS where cockpit inputs came from aircraft navigation systems, surrounding traffic situation, controllers’ indications, etc. So the HCI is intended to enhance situation awareness and decision-making through pilot cockpit. This work approach considers SATS as a system distributed on a large-scale with uncertainty in a dynamic environment. Therefore, a multi-agent systems based approach is well suited for modeling such an environment. We demonstrate that current methodologies for designing multi-agent systems are a useful tool to characterize HCI. We specifically illustrate how the selected methodological approach provides enough guidelines to obtain a cockpit HCI design that complies with future SATS specifications.
机译:当前空中交通系统效率有限,将需要依赖当前技术进步的下一代智能空中交通系统(SATS)。这一挑战意味着向新的导航和空中交通程序范式过渡,飞行员和空中交通管制员将根据新角色和技术支持来执行和协调其活动。执行这些活动的新人机交互(HCI)设计是SATS的关键要素。但是,需要在并行描述与当前情景兼容的假设空中交通情景时,激发开发此类工具的努力。本文的重点是进入SATS的机载HCI,其驾驶舱输入来自飞机导航系统,周围交通情况,管制员的指示等。因此,HCI旨在通过飞行员驾驶舱来增强态势感知和决策能力。该工作方法将SATS视为在动态环境中具有不确定性的大规模分布系统。因此,基于多主体系统的方法非常适合于对这种环境进行建模。我们证明当前设计多智能体系统的方法学是表征HCI的有用工具。我们将具体说明所选的方法论方法如何提供足够的指导方针,以获取符合未来SATS规范的座舱人机交互设计。

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