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Cong W.,Nanjing University of Aeronautics and Astronautics | Cong W.,National Key Laboratory of Air Traffic Flow Management | Hu M.,Nanjing University of Aeronautics and Astronautics | Hu M.,National Key Laboratory of Air Traffic Flow Management | And 5 more authors.
Chinese Journal of Aeronautics | Year: 2016

Air transport network, or airport network, is a complex network involving numerous airports. Effective management of the air transport system requires an in-depth understanding of the roles of airports in the network. Whereas knowledge on air transport network properties has been improved greatly, methods to find critical airports in the network are still lacking. In this paper, we present methods to investigate network properties and to identify critical airports in the network. A novel network model is proposed with airports as nodes and the correlations between traffic flow of airports as edges. Spectral clustering algorithm is developed to classify airports. Spatial distribution characteristics and intraclass correlation of different categories of airports are carefully analyzed. The analyses based on the fluctuation trend of distance-correlation and power spectrum of time series are performed to examine the self-organized criticality of the network. The results indicate that there is one category of airports which dominates the self-organized critical state of the network. Six airports in this category are found to be the most important ones in the Chinese air transport network. The flights delay occurred in these six airports can propagate to the other airports, having huge impact on the operation characteristics of the entire network. The methods proposed here taking traffic dynamics into account are capable of identifying critical airports in the whole air transport network. © 2016 Chinese Society of Aeronautics and Astronautics.


Wang Y.,Nanjing University of Aeronautics and Astronautics | Wang Y.,National Key Laboratory of Air Traffic Flow Management | Zhang Q.,Nanjing University of Aeronautics and Astronautics | Zhang Q.,National Key Laboratory of Air Traffic Flow Management | And 4 more authors.
Physica A: Statistical Mechanics and its Applications | Year: 2016

Recent human dynamics research has unmasked astonishing statistical characteristics such as scaling behaviors in human daily activities. However, less is known about the general mechanism that governs the task-specific activities. In particular, whether scaling law exists in human activities under high pressure remains an open question. In air traffic management system, safety is the most important factor to be concerned by air traffic controllers who always work under high pressure, which provides a unique platform to study human activity. Here we extend fluctuation scaling method to study air traffic controller's communication activity by investigating two empirical communication datasets. Taken the number of controlled flights as the size-like parameter, we show that the relationships between the average communication activity and its standard deviation in both datasets can be well described by Taylor's power law, with scaling exponent α≈0.77±0.01 for the real operational data and α≈0.54±0.01 for the real-time training data. The difference between the exponents suggests that human dynamics under pressure is more likely dominated by the exogenous force. Our findings may lead to further understanding of human behavior. © 2015 Elsevier B.V.


Wang Y.,Nanjing University of Aeronautics and Astronautics | Wang Y.,National Key Laboratory of Air Traffic Flow Management | Cong W.,Nanjing University of Aeronautics and Astronautics | Cong W.,National Key Laboratory of Air Traffic Flow Management | And 6 more authors.
Proceedings of the 11th USA/Europe Air Traffic Management Research and Development Seminar, ATM 2015 | Year: 2015

Eye movements are important indicators of information seeking behavior, and provide an insight into information about interests, goals, plans and cognitive strategies. The understanding of eye movements is thus of great importance to study the behaviors of human who are responsible for the safety and efficiency of a complex system. In air traffic management, much previous research has focused on the investigations on pilots' eye movements. Little has been done on the study of controllers' eye movements. Here, we present statistical analysis of controllers' eye movements that are recorded during real-time simulations. Specifically, we examine two commonly investigated oculomotor behaviors, fixation and saccades, to study effect of working experience on eye movements. By comparing the statistical properties of defined metrics and by applying Multifractal Detrended Fluctuation Analysis method to the time series data, we show that working experience do have notable effects on eye movements patterns. Both fixation and saccades are different between qualified controllers and novices. Qualified controllers can use more efficient searching strategies than novices. These findings may help to enhance the quality of controller training. More importantly, they may shed lights on understanding of mechanisms of information seeking of human when execute complex tasks.


Ma Y.,Nanjing University of Aeronautics and Astronautics | Ma Y.,National Key Laboratory of Air Traffic Flow Management | Hu M.,Nanjing University of Aeronautics and Astronautics | Hu M.,National Key Laboratory of Air Traffic Flow Management | And 6 more authors.
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | Year: 2015

In order to relieve the congestions and delays at multi-airport system in metroplex region, an optimized method for collaborative arrival sequencing and scheduling in metroplex terminal area is proposed in this work. By analyzing deeply the spatio-temporal characteristics of metroplex terminal area and taking into consideration control handoff separation, wake turbulence separation and multi-runway operating separation, an optimized model for collaborative arrival sequencing and scheduling in metroplex terminal area is established to balance scientifically different parties in interest such as safety, economy and fairness with the introduction of innovative idea of multi-restricted time window. An elitist non-dominated sorting genetic algorithm is designed combined with the multi-objective optimization theory and applied to solving the problem of multi-airport arrival sequencing and scheduling to search for the Pareto optimal solutions. Simulation results show that the above model and algorithm can achieve optimized sequencing and scheduling for arrivals in metroplex terminal area, remarkably reducing the flight delays, and effectively enhancing the fairness of using the common airspace resources in multi-airport system. Compared with the classical strategy of first-come-first-served (FCFS), the optimized one brings about a striking effect which results in a 31.0% reduction in flight delays. The proposed method can significantly relieve the flight delays of arrivals at multi-airport system in metroplex region and effectively improve the service quality of air transportation. ©, 2015, AAAS Press of Chinese Society of Aeronautics and Astronautics. All right reserved.


Yin J.,Nanjing University of Aeronautics and Astronautics | Yin J.,National Key Laboratory of Air Traffic Flow Management | Hu M.,Nanjing University of Aeronautics and Astronautics | Hu M.,National Key Laboratory of Air Traffic Flow Management | And 6 more authors.
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | Year: 2015

In order to relieve the congestions and delays at busy airports with large flow and high density of air traffic, an optimized method for multi-runway spatio-temporal resource scheduling in the mode of independent departures is proposed in this work. Firstly, from the perspective of the field of production scheduling, multi-runway departure scheduling problem is regarded as an NP-Hard combinatorial optimization problem of typical job shop scheduling. Secondly, the optimization targets of flight delays, runway capacity and pollutant discharge amounts of aeroengine are established by deeply analyzing the needs of the stakeholders in air transportation industry, then an optimized model is established considering the restricts such as wake turbulence separation, surface taxiing separation and runway crossing separation. Finally, an elitist non-dominated sorting genetic algorithm (NSGA-II) is designed combined with the multi-objective optimization theory and applied to solving the problem of multi-runway scheduling to search for Pareto optimal solutions. Simulation results show that the above model and algorithm can achieve optimized scheduling for aircraft in the mode of independent departures, effectively reduce the flight delays and pollutant discharge amounts of aeronautical engine and improve the runway capacity. Compared with the rand and alternate scheduling strategy of multi-runway, the optimized one brings about a striking effect which results in a 51.2% and 42.7% reduction in flight delays. The proposed method can significantly relieve the flight delays of departures at large busiest airport and effectively improve the service quality of air transportation. ©, 2015, AAAS Press of Chinese Society of Aeronautics and Astronautics. All right


Yin J.,Nanjing University of Aeronautics and Astronautics | Yin J.,National Key Laboratory of Air Traffic Flow Management | Hu M.,Nanjing University of Aeronautics and Astronautics | Hu M.,National Key Laboratory of Air Traffic Flow Management | And 6 more authors.
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | Year: 2014

As the convergence part of the airfield and terminal area at an airport system, the runway causes frequent air traffic congestions and flight delays due to the unbalanced demand and capacity. In this work, an optimized method for multi-runway spatio-temporal resource scheduling in the mode of dependent approaches is proposed to improve the service ability of multi-runway systems. By analyzing in depth the spatio-temporal characteristics of multi-runway systems and taking into considerations the control handoff separation, wake turbulence separation, longitudinal separation, and slope separation, an optimized model is established to balance different factors of interest such as safety, economy and environment. Then an elitist non-dominated genetic sorting algorithm is designed in combination with the multi-objective optimization theory, and applied to solve the problem of multi-runway scheduling. Simulation results show that the above model and algorithm can achieve optimized scheduling for aircraft in dependent approaches, and it can effectively reduce flight delays as well as pollutant discharges of aeronautical engines. Compared with the random and alternate scheduling strategy of multi-runway, the optimized model brings about a striking effect of 39.3% and 32.6% reduction in flight delays. The method which is entirely applicable to the mode of independent approaches can significantly relieve the flight delays at large busy airports, and effectively improve the flight punctuality rate. ©, 2014, Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica. All right reserved.


Yin J.,Nanjing University of Aeronautics and Astronautics | Yin J.,National Key Laboratory of Air Traffic Flow Management | Hu M.,Nanjing University of Aeronautics and Astronautics | Hu M.,National Key Laboratory of Air Traffic Flow Management | And 4 more authors.
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | Year: 2014

Low service ability of an airfield area causes frequent air traffic congestion and flight delays at busy airports. The airport system calls for capacity and efficiency improvements urgently to relieve the current congested situation. In this work, an optimization approach for the collaborative operating modes of multi-runway systems is proposed to balance the demand and capacity. Runway operating modes are classified in detail taking into consideration the airport layout, air traffic characteristics, weather conditions and other factors comprehensively. Based on the theory of runway capacity envelope, a corresponding optimization model is established by introducing the capacity loss coefficient which objectively reflects the mode switching characteristics. Then an elitist non-dominated sorting genetic algorithm is designed combined with the multi-objective optimization theory, and applied to solve the problem of multi-runway operating mode configuration. Simulation results show that the above model and algorithm can achieve optimized multi-runway configuration and improve demand-capacity balancing. Compared with the single runway mode, the combined runway modes bring about a striking optimization effect which results in a 38.1% reduction in the cost of flight delays and a 46.4% decrease in the quantity of adjusted flights. The approach provided can significantly enhance collaborative operating efficiency of a multi-runway system, and effectively improve air traffic punctuality.


Wang Y.,Nanjing University of Aeronautics and Astronautics | Wang Y.,National Key Laboratory of Air Traffic Flow Management | Bu J.,Nanjing University of Aeronautics and Astronautics | Bu J.,National Key Laboratory of Air Traffic Flow Management | And 7 more authors.
Transportation Research Part C: Emerging Technologies | Year: 2016

Air traffic controllers play critical roles in the safety, efficiency, and capacity of air traffic management. However, there is inadequate knowledge of the dynamics of the controllers' activities, especially from a quantitative perspective. This paper presents a novel network approach to uncover hidden patterns of the controllers' behavior based on the voice communication data. We convert the time series of the controllers' communication activities, which contain flights' information, into a time-varying network and a static network, referred to as temporal network and time-aggregated network, respectively. These networks reflect the interaction between the controllers and the flights on a sector level, and allow us to leverage network techniques to yield new and insightful findings regarding regular patterns and unique characteristics of the controllers' communication activities. The proposed methodology is applied to three real-world datasets, and the resulting networks are closely examined and compared in terms of degree distribution, community structure, and motifs. This network approach introduces a "spatial" element to the conventional analysis of the controllers' communication events, by identifying connectivity and proximity among flights. It constitutes a major step towards the quantitative description of the controller-flight dynamics, which is not widely seen in the literature. © 2016 Elsevier Ltd.


Cong W.,Nanjing University of Aeronautics and Astronautics | Cong W.,National Key Laboratory of Air Traffic Flow Management | Hu M.-H.,Nanjing University of Aeronautics and Astronautics | Hu M.-H.,National Key Laboratory of Air Traffic Flow Management | And 2 more authors.
Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China | Year: 2015

The voice communication of air traffic controllers is critical to the operating safety and efficiency of an air traffic management system. Based on the previous human dynamics studies, air traffic controller's voice communication data, which were collected from Beijing, Shanghai, Chongqing and Guiyang, are carefully analyzed. The use of detrended fluctuation analysis finds that controller's communications are long-rang correlated. Five typical statistical models are used to model the inter-communication times of controller. The parameters of the models are estimated by the means of maximum likelihood estimation. Our results show that although the inverse Gaussian distribution is better to describe all the inter-communication data approximately, the inter-communication data that fall between 11 seconds and 240 seconds can be better described by the power-law distribution with exponent α ≈ 1.8. Comparisons on the data from en route sectors and approach sectors further shows that there is little difference on the power-law distributions, indicating that sector types has little impact on air traffic controller's communication activities. ©, 2015, Univ. of Electronic Science and Technology of China. All right reserved.


Xu Y.,Nanjing University of Aeronautics and Astronautics | Xu Y.,University of Barcelona | Zhang H.,Nanjing University of Aeronautics and Astronautics | Zhang H.,University of Barcelona | And 3 more authors.
Aerospace Science and Technology | Year: 2016

This paper provides a special view on air traffic flow parameters and presents certain influences from airspace to traffic flow characteristics. Based on statistics on measurement radar data within terminal airspace, we obtain time distributions and interrelationships of the basic parameters, and accordingly divide traffic flow states into 3 phases: free flow, mild-controlled and strong-controlled flow. Through analyzing characteristics shown in different phase states, as well as aircraft performing in real airspace operations, we establish dynamic models to describe potential behaviors including following, holding and maneuvering, while programing them into simulation tools. Relationship patterns are validated by comparison analysis on the similar simulation results against measurement data. Taking air route adjustment as simulation example, we conduct experiments on airspace elements that may have effects on traffic flow, with further discussing on possible reasons. © 2016 Elsevier Masson SAS.

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