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Application of distributed artificial intelligence in autonomous aircraft operations

机译:分布式人工智能在飞机自动驾驶中的应用

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Outlines the study of the application of distributed artificial intelligence (DAI) concepts and techniques in the development of algorithms and operational methods to support flight crew decision-aids for airborne separation assurance in autonomous aircraft operations (AAO). In the future envisaged for air traffic management (ATM), autonomous aircraft operations will be allowed in specifically allocated volumes of airspace. In AAO airspace, the aircraft will fly user-preferred routes and the responsibility for separation assurance will be fully transferred to the flight crew. To explore the potential of adopting a DAI approach to AAO, autonomous aircraft are modelled as agents and their interactions are considered in the context of a multi-agent system. In this framework, the aircraft-agents are willing to collaborate in the resolution of conflicts to coordinate their actions and share the costs of the conflict resolution. Thus, separation assurance in AAO is regarded as a co-operative process that takes place in a multi-agent system. A co-operation mechanism to support separation assurance for AAO with no point-to-point data-link communications facility is presented. The mechanism is based on automatic dependent surveillance-broadcast (ADS-B) and relies on a trajectory-planning algorithm that is implemented on board the autonomous aircraft. The algorithm produces resolution manoeuvres that take into account the possible reactions of the conflicting aircraft to the selected resolution trajectory.
机译:概述了对分布式人工智能(DAI)概念和技术在算法和操作方法开发中的应用的研究,这些算法和操作方法可为飞行器自主飞行(AAO)中的空降保证提供支持,以支持机组人员的决策辅助。在未来的空中交通管理(ATM)设想中,将允许飞机在特定分配的空域内进行自主飞行。在AAO空域中,飞机将飞行用户偏爱的航线,并将保证间隔的责任完全转移给机组人员。为了探索将DAI方法应用于AAO的潜力,将自主飞机建模为代理,并在多代理系统的背景下考虑了它们之间的相互作用。在这种框架下,飞机代理商愿意合作解决冲突,以协调其行动并分担解决冲突的费用。因此,AAO中的分离保证被认为是在多主体系统中发生的合作过程。提出了一种在没有点对点数据链路通信功能的情况下支持AAO分离保证的合作机制。该机制基于自动相关监视广播(ADS-B),并依赖于在自动驾驶飞机上实现的轨迹规划算法。该算法产生考虑到冲突飞机对所选分辨率轨迹可能发生的反应的分辨率演算。

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