空中交通管理（以下简称空管）是民航系统三大支柱行业之一。随着大众对航空运输需求的日益增长，肩负航班运行保障重任的空中交通管制员（简称管制员）的效能问题日益凸显。对管制员工作效能特别是工作负荷进行研究，实现对管制员工作的有效监控、评价及管理，已成为运行管理者必须面对并解决的问题。管制员工作负荷受空中交通流量、空域复杂度、天气状况、管制员心理素质等多方面影响，利用传统的研究方法已无法满足动态监控和评估要求。本项目提出了基于人眼视线行为分析的管制员状态评估方法，通过基于可见光、可见光/红外混合相机的视线跟踪新理论和实现、视线跟踪与雷达屏幕对象/视觉显著性区域联合分析优化、基于视线跟踪的管制员工作负荷、疲劳程度等评估模型三个方面深入研究，实现对管制员工作技能水平、疲劳程度等情况自动、定量和及时评估。本项目的研究成果在空管行业安全生产管理、管制技能培训以及空域的管理与规划等方面具有直接应用前景。

Air traffic control is one of the three key components of the civil aviation system. With the drastic growth of air traffic in recent years, air traffic control workload issue has attracted attention from airspace decision makers, participants and air travelers. It is also the bottleneck for the development of the safe, efficient civil aviation operations. The air traffic control workload is impacted by various factors, such as airspace condition, air traffic flow density, psychological/cognitive condition of air traffic controller, experience and skill level of air traffic controller and air traffic controller's health condition. Many of these factors are not easy to predict or manage. Traditional workload measurement and analysis methods are not able to provide real-time monitoring and evaluation. This proposed project focuses on gaze tracking based air traffic control workload measurement. In particular, our research covers three major topics, including gaze tracking under visible/IR illuminations, joint optimization for both gaze and radar screen and the saliency regions, and the model for workload and fatigue level estimation of air traffic controllers. Our goal is to automatically estimate the skill level, cognitive condition, fatigue level of air traffic controllers, and obtain quantitative and objective results timely. Our research achievement will show good potential in the fields of safety management, skill training and air space management.