In order to handle increasing demand in air transportation, high-level automation support seems inevitable. This article presents an optimization-based autonomous air traffic control (ATC) system and the determination of airspace capacity with respect to the proposed system. We model aircraft dynamics and guidance procedures for simulation of aircraft motion and trajectory prediction. The predicted trajectories are used during decision process and simulation of aircraft motion is the key factor to create a traffic environment for estimation of airspace capacity. We define the interventions of an air traffic controller (ATCo) as a set of maneuvers that is appropriate for real air traffic operations. The decision process of the designed ATC system is based on integer linear programming (ILP) constructed via a mapping process that contains discretization of the airspace with predicted trajectories to improve the time performance of conflict detection and resolution. We also present a procedure to estimate the airspace capacity with the proposed ATC system. This procedure consists of constructing a stochastic traffic simulation environment that includes the structure of the evaluated airspace. The approach is validated on real air traffic data for enroute airspace, and it is also shown that the designed ATC system can manage traffic much denser than current traffic.

中文翻译：

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用于空域容量改进的基于优化的自主空中交通控制

为了应对航空运输日益增长的需求，高级自动化支持似乎是不可避免的。本文介绍了一种基于优化的自主空中交通管制 (ATC) 系统以及与所提议系统相关的空域容量的确定。我们对飞机动力学和制导程序进行建模，以模拟飞机运动和轨迹预测。在决策过程中使用预测的轨迹，飞机运动的模拟是创建用于估计空域容量的交通环境的关键因素。我们将空中交通管制员 (ATCo) 的干预定义为一组适用于实际空中交通运营的机动。设计的 ATC 系统的决策过程基于整数线性规划 (ILP)，通过映射过程构建，该过程包含具有预测轨迹的空域离散化，以提高冲突检测和解决的时间性能。我们还提出了一个程序来估计提议的 ATC 系统的空域容量。该程序包括构建一个随机交通模拟环境，其中包括评估空域的结构。该方法在航路空域的真实空中交通数据上得到验证，并且还表明设计的 ATC 系统可以管理比当前交通密集得多的交通。我们还提出了一个程序来估计提议的 ATC 系统的空域容量。该程序包括构建一个随机交通模拟环境，其中包括评估空域的结构。该方法在航路空域的真实空中交通数据上得到验证，并且还表明设计的 ATC 系统可以管理比当前交通密集得多的交通。我们还提出了一个程序来估计提议的 ATC 系统的空域容量。该程序包括构建一个随机交通模拟环境，其中包括评估空域的结构。该方法在航路空域的真实空中交通数据上得到验证，并且还表明设计的 ATC 系统可以管理比当前交通密集得多的交通。