Abstract: The existing evaluation of dynamic traffic capacity does not consider the controller's cognitive load. In order to improve the accuracy of air traffic flow management, a new sector dynamic traffic capacity evaluation model based on controller's cognitive load and improved ant colony algorithm was constructed. Firstly, a dynamic flight constrained region model which could describe the dynamic influence factors of the sector was constructed, and the dynamic control guided path planning was realized by improving ant colony algorithm, which could meet the calculation speed requirement of air traffic flow management. Then, the concept of control and guidance load intensity was proposed and used for the construction of sector dynamic traffic capacity evaluation model, which expanded the concept of controller's total cognitive load. Finally, taking the Sanya regulatory sector as an example, the dynamic traffic capacity of the sector at 9 moments in the next 2 hours was evaluated by taking 15 min as an interval. The results of example verification show that the results of dynamic traffic capacity obtained by the proposed model are different from the actual operating results by an airplane, and the effects are ideal.

Key words: air traffic management, cognitive load, dynamic traffic capacity, eye movement, improved ant colony algorithm

摘要： 针对现有动态通行能力的评估未考虑管制员认知负荷的不足，为了提高空中交通流量管理的准确性，构建了基于管制员认知负荷和改进蚁群算法的扇区动态通行能力评估模型。首先，构建了刻画扇区动态影响因素的动态飞行受限区模型，为了满足空中交通流量管理对速度的要求，改进了蚁群算法实现扇区动态管制引导路径规划；然后，提出了管制引导负荷强度的概念，扩展了管制员认知总负荷的概念，并将其应用于扇区动态通行能力评估模型的构建；最后，以三亚管制扇区为例，以15 min为间隔对未来2 h内9个时刻的扇区动态通行能力进行评估。实例验证结果表明所提评估模型计算得到的通行能力结果与实际运行结果相差1个架次，效果理想。

关键词: 空中交通管理, 认知负荷, 动态通行能力, 眼动, 改进蚁群算法