Transactions of Nanjing University of Aeronautics & Astronautics
Volume 33,Issue 4,2016 Table of Contents
2 Evolution of Air Traffic Management Concept of Operations and Its Impact on the System Architecture
2016, 33(4):403-413.
Abstract:
The air traffic management system (ATM) has the task of ensuring safe, orderly and expeditious flow of air traffic. The ATM system architecture is very much dependent on the concept of operations (ConOps). Over the ears the evolution in ConOps has resulted in changes in the ATM′s physical architecture, improving its physical infrastructure, increasing the levels of automation and making operational changes to improve air traffic flow, to cope with increasing demand for air travel. However, what is less clear is the impact of such changes in ConOps on the ATM′s functional architecture. This is vital for ensuring optimality in the implementation of the physical architecture components to support the ATM functions. This paper reviews the changes in the ConOps over the years, proposes a temporally invariant ATM functional model, and discusses some of the main key technologies expected to make significant improvements to the ATM system.
The air traffic management system (ATM) has the task of ensuring safe, orderly and expeditious flow of air traffic. The ATM system architecture is very much dependent on the concept of operations (ConOps). Over the ears the evolution in ConOps has resulted in changes in the ATM′s physical architecture, improving its physical infrastructure, increasing the levels of automation and making operational changes to improve air traffic flow, to cope with increasing demand for air travel. However, what is less clear is the impact of such changes in ConOps on the ATM′s functional architecture. This is vital for ensuring optimality in the implementation of the physical architecture components to support the ATM functions. This paper reviews the changes in the ConOps over the years, proposes a temporally invariant ATM functional model, and discusses some of the main key technologies expected to make significant improvements to the ATM system.
2016, 33(4):414-424.
Abstract:
A highprecision nominal flight profile, involving controllers′ intentions is critical for 4D trajectory estimation in modern automatic air traffic control systems. We proposed a novel method to effectively improve the accuracy of the nominal flight profile, including the nominal altitude profile and the speed profile. First, considering the characteristics of trajectory data, we developed an improved K means algorithm. The approach was to measure the imilarity between different altitude profiles by integrating the space warp edit distance algorithm, thereby to acqu ire several fitted nominal flight altitude profiles. This approach breaks the constraints of traditional K means algorithms. Second, to eliminate the influence of meteorological factors, we introduced historical gridded binary data to de termine the enroute wind speed and temperature via inverse distance weighted interpolation. Finally, we facilitated the true airspeed determined by speed triangle relationships and the calibrated airspeed determined by aircraft data model to extract a more accurate nominal speed profile from each cluster, therefore we could describe the airspeed profiles above and below the airspeed transition altitude, respectively. Our experimental results showed that the proposed method could obtain a highly accurate nominal flight profile, which reflects the actual aircraft flight status.
A highprecision nominal flight profile, involving controllers′ intentions is critical for 4D trajectory estimation in modern automatic air traffic control systems. We proposed a novel method to effectively improve the accuracy of the nominal flight profile, including the nominal altitude profile and the speed profile. First, considering the characteristics of trajectory data, we developed an improved K means algorithm. The approach was to measure the imilarity between different altitude profiles by integrating the space warp edit distance algorithm, thereby to acqu ire several fitted nominal flight altitude profiles. This approach breaks the constraints of traditional K means algorithms. Second, to eliminate the influence of meteorological factors, we introduced historical gridded binary data to de termine the enroute wind speed and temperature via inverse distance weighted interpolation. Finally, we facilitated the true airspeed determined by speed triangle relationships and the calibrated airspeed determined by aircraft data model to extract a more accurate nominal speed profile from each cluster, therefore we could describe the airspeed profiles above and below the airspeed transition altitude, respectively. Our experimental results showed that the proposed method could obtain a highly accurate nominal flight profile, which reflects the actual aircraft flight status.
2016, 33(4):425-432.
Abstract:
Due to the particularity of its location algorithm, there are some unique difficulties and features regarding the test of target motion states of multilateration (MLAT) system for airport surface surveillance. This paper proposed a test method applicable for the airport surface surveillance MLAT system, which can effectively determine whether the target is static or moving at a certain speed. Via a normalized test statistic designed in the sliding data window, the proposed method not only eliminates the impact of geometry Dilution of precision (GDOP) effectively, but also transforms the test of different motion states into the test of different probability density functions. Meanwhile, by adjusting the size of the sliding window, it can fulfill different test performance requirements. The method was developed through strict theoretical extrapolation and performance analysis, and simulations results verified its correctness and effectiveness.
Due to the particularity of its location algorithm, there are some unique difficulties and features regarding the test of target motion states of multilateration (MLAT) system for airport surface surveillance. This paper proposed a test method applicable for the airport surface surveillance MLAT system, which can effectively determine whether the target is static or moving at a certain speed. Via a normalized test statistic designed in the sliding data window, the proposed method not only eliminates the impact of geometry Dilution of precision (GDOP) effectively, but also transforms the test of different motion states into the test of different probability density functions. Meanwhile, by adjusting the size of the sliding window, it can fulfill different test performance requirements. The method was developed through strict theoretical extrapolation and performance analysis, and simulations results verified its correctness and effectiveness.
2016, 33(4):433-441.
Abstract:
Air traffic controllers are the important parts of air traffic management system who are res ponsible for the safety and efficiency of the system. They make traffic management decisions based on information acquired from various sources. The understanding of their information seeking behaviors is still limited. We aim to identify controllers′ behavior through the examination of the correlations betwe en controllers′ eye movements and air traffic. Sixteen air traffic controllers were invited to participate realtime simulation experiments, during which the data of their eyeball movements and air traffic were recorded. Twenythree air traffic complexity metrics and six eye movements metrics were calculated to examine their relationships. Two correlational methods, Pearson′s correlation and Spearman′s correlation, were tested between every eyetraffic pair of metrics. The results indicate that controllers′ two kinds of informationseeking behaviors can be identified from their eye movements: Targets tracking, and confliction recognition. The study on controllers′ eye movements may contribute to the understanding of informationseeking mechanisms leading to the development of more intelligent automations in the future.
Air traffic controllers are the important parts of air traffic management system who are res ponsible for the safety and efficiency of the system. They make traffic management decisions based on information acquired from various sources. The understanding of their information seeking behaviors is still limited. We aim to identify controllers′ behavior through the examination of the correlations betwe en controllers′ eye movements and air traffic. Sixteen air traffic controllers were invited to participate realtime simulation experiments, during which the data of their eyeball movements and air traffic were recorded. Twenythree air traffic complexity metrics and six eye movements metrics were calculated to examine their relationships. Two correlational methods, Pearson′s correlation and Spearman′s correlation, were tested between every eyetraffic pair of metrics. The results indicate that controllers′ two kinds of informationseeking behaviors can be identified from their eye movements: Targets tracking, and confliction recognition. The study on controllers′ eye movements may contribute to the understanding of informationseeking mechanisms leading to the development of more intelligent automations in the future.
2016, 33(4):442-450.
Abstract:
Terminal airspace (TMA) is the airspace centering several military and civil aviation airports with complex route structure, limited airspace resources, traffic flow, difficult management and considerable airspace complexity. A scientific and rational sectorization of TMA can optimize airspace resources, and sufficiently utilize the control of human resources to ensure the safety of TMA. The functional sectorization model was established based on the route structure of arriving and departing aircraft as well as controlling requirements. Based on principles of sectorization and topological relations within a network, the arrival and departure sectorization model was established, using tree based ant colony algorithm (ACO) searching. Shanghai TMA was taken as an example to be sectorizaed, and the result showed that this model was superior to traditional ones when arrival and departure routes were separated at dense airport terminal airspace.
Terminal airspace (TMA) is the airspace centering several military and civil aviation airports with complex route structure, limited airspace resources, traffic flow, difficult management and considerable airspace complexity. A scientific and rational sectorization of TMA can optimize airspace resources, and sufficiently utilize the control of human resources to ensure the safety of TMA. The functional sectorization model was established based on the route structure of arriving and departing aircraft as well as controlling requirements. Based on principles of sectorization and topological relations within a network, the arrival and departure sectorization model was established, using tree based ant colony algorithm (ACO) searching. Shanghai TMA was taken as an example to be sectorizaed, and the result showed that this model was superior to traditional ones when arrival and departure routes were separated at dense airport terminal airspace.
2016, 33(4):451-460.
Abstract:
Due to the everincreasing air traffic flow, the influence of aircraft noise around the airport has become significant. As most airlines are trying to decrease operation cost, stringent requirements for more simple and efficient departure trajectory are on a rise. Therefore, a departure trajectory design was established for performancebased navigation technology, and a multiobjective optimization model was developed, with constraints of safety and noise influence, as well as optimization targets of efficiency and simplicity. An improved ant colony algorithm was then proposed to solve the optimization problem. Finally, an experiment was conducted using the Lanzhou terminal airsp ace operation data, and the results showed that the designed departure trajectory was feasible and efficient in decreasing the aircraft noise influence.
Due to the everincreasing air traffic flow, the influence of aircraft noise around the airport has become significant. As most airlines are trying to decrease operation cost, stringent requirements for more simple and efficient departure trajectory are on a rise. Therefore, a departure trajectory design was established for performancebased navigation technology, and a multiobjective optimization model was developed, with constraints of safety and noise influence, as well as optimization targets of efficiency and simplicity. An improved ant colony algorithm was then proposed to solve the optimization problem. Finally, an experiment was conducted using the Lanzhou terminal airsp ace operation data, and the results showed that the designed departure trajectory was feasible and efficient in decreasing the aircraft noise influence.
2016, 33(4):461-468.
Abstract:
In order to quantitatively analyze air traffic operation complexity, multidimensional metrics were selected based on the operational characteristics of traffic flow. The kernel principal component analysis method was utilized to reduce the dimensionality of metrics, therefore to extract crucial information in the metrics. The hierarchical clustering method was used to analyze the complexity of different airspace. F ourteen sectors of Guangzhou Area Control Center were taken as samples. The operation complexity of traffic situation in each sector was calculated based on real flight radar data. Clustering analysis verified the feasibility and rationality of the method, and provided a reference for airspace operation and management.
In order to quantitatively analyze air traffic operation complexity, multidimensional metrics were selected based on the operational characteristics of traffic flow. The kernel principal component analysis method was utilized to reduce the dimensionality of metrics, therefore to extract crucial information in the metrics. The hierarchical clustering method was used to analyze the complexity of different airspace. F ourteen sectors of Guangzhou Area Control Center were taken as samples. The operation complexity of traffic situation in each sector was calculated based on real flight radar data. Clustering analysis verified the feasibility and rationality of the method, and provided a reference for airspace operation and management.
2016, 33(4):469-478.
Abstract:
Air route network (ARN) planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation. Here, the ARN shortest path was taken as the objective function, and an air route network node (ARNN) optimization model was developed to circumvent the restrictions imposed by ″three areas ″, also known as prohibited areas, restricted areas, and dangerous areas (PRDs), by creating a grid environment. And finally the objective function was solved by means of an adaptive ant colony algorithm (AACA). The A593, A470, B221, and G204 air routes in the busy ZSHA flight information region, where the airspace includes areas with different levels of PRDs, were taken as an example. Based on current flight patterns, a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs. The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%.
Air route network (ARN) planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation. Here, the ARN shortest path was taken as the objective function, and an air route network node (ARNN) optimization model was developed to circumvent the restrictions imposed by ″three areas ″, also known as prohibited areas, restricted areas, and dangerous areas (PRDs), by creating a grid environment. And finally the objective function was solved by means of an adaptive ant colony algorithm (AACA). The A593, A470, B221, and G204 air routes in the busy ZSHA flight information region, where the airspace includes areas with different levels of PRDs, were taken as an example. Based on current flight patterns, a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs. The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%.
2016, 33(4):479-490.
Abstract:
Airlines adjust their flight schedules to satisfy more stringent airport capacity constraints caused by inclement weather or other unexpected disruptions. The problem will be more important and complicated if uncertain disruptions occur in hub airports. A twostage stochastic programming model was established to deal with the realtime flight schedule recovery and passenger reaccommodation problem. The firststage model represents the flight retiming and refleeting decision in current time period when capacity information is deterministic, while the secondstage recourse model evaluates the passenger delay given the firststage solutions when one future scenario is realized. Aiming at the large size of the problem and requirement for quick response, an algorithmic framework combining the sample average approximation and heuristic method was proposed. The computational results indicated of that the proposed method could obtain solutions with around 5% optimal gaps, and the computing time was linearly positive to the sample size.
Airlines adjust their flight schedules to satisfy more stringent airport capacity constraints caused by inclement weather or other unexpected disruptions. The problem will be more important and complicated if uncertain disruptions occur in hub airports. A twostage stochastic programming model was established to deal with the realtime flight schedule recovery and passenger reaccommodation problem. The firststage model represents the flight retiming and refleeting decision in current time period when capacity information is deterministic, while the secondstage recourse model evaluates the passenger delay given the firststage solutions when one future scenario is realized. Aiming at the large size of the problem and requirement for quick response, an algorithmic framework combining the sample average approximation and heuristic method was proposed. The computational results indicated of that the proposed method could obtain solutions with around 5% optimal gaps, and the computing time was linearly positive to the sample size.
11 Estimation of Standard Operation Time of Flight Legs Based on Clustering and Probability Analysis
2016, 33(4):491-501.
Abstract:
A clustering algorithm and a probability statistics method were applied to different phases of a flight to analyze operation time during aircraft ground taxiing and airborne flight. And the clustering pattern, distribution characteristics and dynamically changing rules of the two phases were identified. Further, an estimate method was established to measure operation time of flight legs, with creative steps of calculating individual segment separately and then integrating them accordingly. The method can both objectively and dynamically measure operation time, and accurately ref lect real situation. It helps to better utilize airport slot resources and provides a strong support for air traffic flow management when scheduling flight plan in strategic and pretactic phases.
A clustering algorithm and a probability statistics method were applied to different phases of a flight to analyze operation time during aircraft ground taxiing and airborne flight. And the clustering pattern, distribution characteristics and dynamically changing rules of the two phases were identified. Further, an estimate method was established to measure operation time of flight legs, with creative steps of calculating individual segment separately and then integrating them accordingly. The method can both objectively and dynamically measure operation time, and accurately ref lect real situation. It helps to better utilize airport slot resources and provides a strong support for air traffic flow management when scheduling flight plan in strategic and pretactic phases.
2016, 33(4):502-509.
Abstract:
A scheduling model of closely spaced parallel runways for arrival aircraft was proposed, with multiobjections of the minimum flight delay cost, the maximum airport capacity, the minimum workload of air traffic controller and the maximum fairness of airlines′ scheduling. The time interval between two runways and changes of aircraft landing order were taken as the constraints. Genetic algorithm was used to solve the model, and the model constrained unit delay cost of the aircraft with multiple flight tasks to reduce its delay influence range. Each objective function value or the fitness of particle unsatisfied the constrain condition would be punished. Finally, one hub of a domestic airport was introduced to verify the algorithm and the model. The results showed that the genetic algorithm presented strong convergence and timeliness for solving constraint multiobjective aircraft landing problem on closely spaced parallel runways, and the optimization results were better than that of actual scheduling.
A scheduling model of closely spaced parallel runways for arrival aircraft was proposed, with multiobjections of the minimum flight delay cost, the maximum airport capacity, the minimum workload of air traffic controller and the maximum fairness of airlines′ scheduling. The time interval between two runways and changes of aircraft landing order were taken as the constraints. Genetic algorithm was used to solve the model, and the model constrained unit delay cost of the aircraft with multiple flight tasks to reduce its delay influence range. Each objective function value or the fitness of particle unsatisfied the constrain condition would be punished. Finally, one hub of a domestic airport was introduced to verify the algorithm and the model. The results showed that the genetic algorithm presented strong convergence and timeliness for solving constraint multiobjective aircraft landing problem on closely spaced parallel runways, and the optimization results were better than that of actual scheduling.
13 Effects of Deck Motion and Ship Airwake on SkiJump Takeoff Performance of CarrierBased Aircraft
2016, 33(4):510-518.
Abstract:
We first analyzed the force and motion of naval aircraft during launching process. Further, we investigated the ship deck with the form of a ramp and established deck motion model and ship airwake model. Finally, we conducted simulations at medium sea. Results showed that the effects of deck motion on takeoff varied with initial phases, and airwake could help reducing aircraft′s sinkage. We also found that the deck motion played a major role in the effects caused by the interaction of deck motion and ship airwake.
We first analyzed the force and motion of naval aircraft during launching process. Further, we investigated the ship deck with the form of a ramp and established deck motion model and ship airwake model. Finally, we conducted simulations at medium sea. Results showed that the effects of deck motion on takeoff varied with initial phases, and airwake could help reducing aircraft′s sinkage. We also found that the deck motion played a major role in the effects caused by the interaction of deck motion and ship airwake.
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