Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the opera...Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the operational efficiency of air transport systems. Thus,objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment,and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary,we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast,the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models,we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.展开更多
Airway networks are the basic carriers of air traffic.Characterizing airway networks will significantly improve the operating efficiency of aviation.This study is targeted at the airway network composed of 1479 waypoi...Airway networks are the basic carriers of air traffic.Characterizing airway networks will significantly improve the operating efficiency of aviation.This study is targeted at the airway network composed of 1479 waypoints in 2018 of China.Together with spatial structures,traffic flow characteristics,and the dominating traffic flow,four airway network models are constructed from the perspective of complex networks,including physical airway network,airway traffic network,directed airway traffic network,and dominance-based directed airway traffic network.Then the topological characteristics of different networks are statistically analyzed by using typical network measure indices,and the differences of these indices among different networks are investigated.Thereby,composite indices are proposed.Statistical results show that the airway network under the influence of traffic flows exhibits richer heterogeneity and asymmetrical between-node relationship,and the distributions of indices among different networks are significantly different.Comparative analysis of composite indices and traffic flows show that some waypoints yield great results in multiple composite indices and traffic volumes;some waypoints display large results in multiple composite indices but low traffic flows,and other waypoints only perform well in certain composite indices.The importance levels of waypoints are divided,by the K-means method based on degree composite index,betweenness composite index and closeness composite index,into three levels,and the reasonableness of clustering results is validated by the statistical results of traffic flows,airport number,and flight delay.展开更多
基金supported by the National Natural Science Foundation of China (Nos.U1833103, 71801215, U1933103)the Fundamental Research Funds for the Central Universities (No.3122019129)。
文摘Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the operational efficiency of air transport systems. Thus,objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment,and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary,we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast,the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models,we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.
基金This work was supported by the National Natural Science Foundations of China(Nos.U1833103,71801215,and U1933103)。
文摘Airway networks are the basic carriers of air traffic.Characterizing airway networks will significantly improve the operating efficiency of aviation.This study is targeted at the airway network composed of 1479 waypoints in 2018 of China.Together with spatial structures,traffic flow characteristics,and the dominating traffic flow,four airway network models are constructed from the perspective of complex networks,including physical airway network,airway traffic network,directed airway traffic network,and dominance-based directed airway traffic network.Then the topological characteristics of different networks are statistically analyzed by using typical network measure indices,and the differences of these indices among different networks are investigated.Thereby,composite indices are proposed.Statistical results show that the airway network under the influence of traffic flows exhibits richer heterogeneity and asymmetrical between-node relationship,and the distributions of indices among different networks are significantly different.Comparative analysis of composite indices and traffic flows show that some waypoints yield great results in multiple composite indices and traffic volumes;some waypoints display large results in multiple composite indices but low traffic flows,and other waypoints only perform well in certain composite indices.The importance levels of waypoints are divided,by the K-means method based on degree composite index,betweenness composite index and closeness composite index,into three levels,and the reasonableness of clustering results is validated by the statistical results of traffic flows,airport number,and flight delay.
