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The purpose of this study is to provide an alternative graph-based airspace model for more effective free-route flight planning.

Based on graph theory and available data sets describing airspace, as well as weather phenomena, a new FRA model is proposed. The model is applied for near to optimal flight route finding. The software tool developed during the study and complexity analysis proved the applicability and timed effectivity of the flight planning approach.

The sparse bidirectional graph with edges connecting only (geographically) closest neighbours can naturally model local airspace and weather phenomena. It can be naturally applied to effective near to optimal flight route planning.

Practical results were acquired for one country airspace model.

More efficient and applicable flight planning methodology was introduced.

Aircraft following the new routes will fly shorter trajectories, which positively influence on the natural environment, flight time and fuel consumption.

The airspace model proposed is based on standard mathematical backgrounds. However, it includes the original airspace and weather mapping idea, as well as it enables to shorten flight planning computations.

Airspace sectorization is an important task, which has a significant impact in the everyday work of air control services. Especially in recent years, because of the constant increase in air traffic, existing airspace sectorization techniques have difficulties to tackle the large air traffic volumes, creating imbalanced sectors and uneven workload distribution among sectors. The purpose of this paper is to propose a new approach to find optimal airspace sectorization balancing the traffic controller workload between sectors, subject to airspace requirements.

A constraint programming (CP) model called equitable airspace sectorization problem (EQASP) relies on ordered weighted averaging (OWA) multiagent optimization and the parallel portfolio architecture has been developed, which integrates the equity into an existing CP approach (Trandac et al., 2005). The EQASP was evaluated and compared with the method of Trandac et al. (2005), according to the quality of workload balancing between sectors and the resolution performance. The comparison was achieved using real air traffic low-altitude network data sets of French airspace for five flight information regions for 24 h a day and the Algerian airspace for three various periods (off peak hours, peak hours and 24 h).

It has been demonstrated that the proposed EQASP model, which is based on OWA multicriteria optimization method, significantly improved both the solving performance and the workload equity between sectors, while offering strong theoretical properties of the balancing requirement. Interestingly, when solving hard instances, our parallel sectorization tool can provide, at any time, a workable solution, which satisfies all geometric constraints of sectorization.

This study can be used to design well-balanced air sectors in terms of workload between control units in the strategic phase. To fulfil the airspace users’ constraints, one can refer to this study to assess the capacity of each air sector (especially the overloaded sectors) and then adjust the sector’s shape to respond to the dynamic changes in traffic patterns.

This theoretical and practical approach enables the development and support of the definition of the “Air traffic management (ATM) Concept Target” through improvements in human factors specifically (balancing workload across sectors), which contributes to raising the level of capacity, safety and efficiency (SESAR Vision of ATM 2035).

In their approach, the authors proposed an OWA-based multiagent optimization model, ensuring the search for the best equitable solution, without requiring user-defined balancing constraints, which enforce each sector to have a workload between two user-defined bounds (W_min, W_max).

The purpose of this paper is to develop an analytical approach for workload measurement based on the task times and the changing task priorities of en route air traffic controllers (EATC).

A model called Total Airspace Workload Measurement Model was developed to measure EATC workload. Turkish airspace was chosen for practical application of the model. A survey was conducted of EATC to calculate the weighting coefficients and times of different tasks defined in the model. The survey results were analyzed with SPSS 15.0. The real traffic data of Turkish airspace for two peak hours period in heavy traffic covering August 2007 was provided by the General Directorate of Turkish airports. Geomedia 6.0 was employed for the visualization of the real traffic data.

The total airspace workload during two peak hours of traffic, estimated reference sector capacity and the number of operational sector were defined and calculated to analyze the distribution of workload among sectors.

This study can be used for en route sector design such as decision of the number of operational sectors and planning of sectors capacity in the strategic level. Air traffic control service providers can also refer to this study for human resources and equipment planning.

A number of parameters and variables were defined and included in the model by taking into consideration the different service types provided by EATC. All parameters and variables were identified with the task times of the controller. This analytical approach can be applied to those particular airspaces which have different characteristics.

The purpose of this paper was to elaborate the performance model of the remotely piloted aircraft systems (RPAS) which was destined for simulations of the construction characteristics, airspeeds and trajectory of flight in the controlled, non-segregated airspace according to the standard instrument departure and arrival procedures (SIDs and STARs).

This study used systems engineering approach: decomposition of RPAS performance model into components, relations and its connection with components of controlled the airspace system. Fast-time simulations (FTS) method, which included investigation of many scenarios of the system work, minimizing the number of input variables and low computing power demand, is also used.

Performance envelope of many fixed-wing RPAS was not published. The representative RPAS geometry configuration was feasible to implement. Power unit model and aerodynamic model needed to be accommodated to RPAS category. The range of aircraft minimum drag coefficient differed in the investigated range of take-off mass and wing loading.

Fixed-wing RPAS of small and medium categories cover take-off mass (25–450 kg), wing loading (40–900 N/m²) and power loading (8–40 W/N).

This is a research on integration of the RPAS in the controlled, non-segregated airspace. The results of the work may be used in broadening the knowledge of the RPAS characteristics from the perspective of operators, designers and air traffic services.

The elaborated performance model of the RPAS used the minimum number of three input variables (take-off mass, wing loading and power loading) in identification of the complete RPAS characteristics, i.e. construction features (aerodynamic, propulsion and loads) and flight parameters (airspeeds and flight trajectory).

Modeling and system performance analysis play an important role in the planning of air traffic system. In particular, this paper aims to concentrate on the modeling and the performance evaluation of air transportation system.

It has shown that system matrices inherent in the airspace network can be acquired based on the service times of flights. This paper deals with a logical modeling which can avoid temporal synchronization conflict of resources. As a result, a class of queuing system is investigated to obtain a representation of the airspace network dynamics using dioid model.

The analysis of the air traffic system is conducted by solving the system state model. This indicates that it is feasible to use eigenvalues of system model for acquiring characteristics of the considered air transport systems.

The departure scheduling prototype presented in this paper can offer air traffic controller a decision support tool to build optimal departure sequences for aircraft.

The properties of max-plus algebra described allow us to apply linear algebra concepts like eigenvalue and eigenvectors to obtain a solution to the air traffic system being modeled. By solving and analyzing the dioid model, this paper evaluated some performance measures of airspace network.

This work presents the part of the research in the integration of the remotely piloted aircraft systems (RPAS) in non-segregated airspace. The purpose of this study is to elaborate the reference shape of the Standard Instrument Arrivals (STARs) procedures of controlled airports. The STARs parameters are unique for the aerodromes and depend on navigational aids (NAVAIDs), manoeuvres and aircraft categories. Therefore, the elaboration of reference shapes was advisable in the context of RPAS integration research.

The models were based on the procedure design guidelines by International Civil Aviation Organization. The statistics of existing STARs were prepared using Aeronautical Information Publications to determine the representative procedural parameters. Construction of procedural shapes required to define the nominal flight path and tolerance areas.

In statistics, the standard deviation of distances was below the determined reference mean values, thus the models were convergent with existing procedures.

The modelling was limited to initial, intermediate, final and missed approach segments. Arrival segment was not modelled. NAVAIDs include Instrument Landing System Category 1 (in final and missed approach) and very high-frequency omni-directional ranging or global navigation satellite systems (in initial and intermediate approach segments).

Prepared models may be used in research in the integration of the new types of aerial vehicles in existing air traffic management systems.

The reference STARs possess commonly used procedural manoeuvres (straight-in, turn, racetrack and base turn) and different NAVAIDs. The parameters of approach segments were determined as representative of the existing procedures. Moreover, the models are suitable to place at arbitrary origin and runway axis bearing.

The current air traffic management (ATM) operational approach is changing; “time” is now integrated as an additional fourth dimension on trajectories. This notion will impose on aircraft the compliance of accurate arrival times over designated checkpoints (CPs), called time windows (TWs). This paper aims to clarify the basic requirements and foundations for the practical implementation of this functional framework.

This paper reviews the operational deployment of 4D trajectories, by defining its relationship with other concepts and systems of the future ATM and communications, navigation and surveillance (CNS) context. This allows to establish the main tools that should be considered to ease the application of the 4D-trajectories approach. This paper appraises how 4D trajectories must be managed and planned (negotiation, synchronization, modification and verification processes). Then, based on the evolution of a simulated 4D trajectory, the necessary corrective measures by evaluating the degradation tolerances and conditions are described and introduced.

The proposed TWs model can control the time tolerance within less than 100 s along the passing CPs of a generic trajectory, which is in line with the expected future ATM time-performance requirements.

The main contribution of this work is the provision of a holistic vision of the systems and concepts that will be necessary to implement the new 4D-trajectory concept efficiently, thus enhancing performance. It also proposes tolerance windows for trajectory degradation, to understand both when an update is necessary and what are the conditions required for pilots and air traffic controllers to provide this update.

The aim of this study is to identify the nodes where congestion occurs in the manoeuvring area of a large-scale airport and to provide appropriate suggestions for improvement.

To investigate the air traffic flow in a highly complex system such as an airport manoeuvring area, a two-stage method based on fast- and real-time simulation techniques is applied. The first stage involves the analysis with fast- and real-time simulations of a baseline model created to determine the congestion points. Based on the analysis, improvements to be performed in the layout of the manoeuvring area are proposed. In the second stage, alternative scenarios implementing these improvements are generated and evaluated in a fast-time simulation environment. Based on the results of simulations of different runway configurations, the main areas of congestion in the baseline airport model are determined. Congestion nodes are identified in the departure queue points and in the taxiway system. To mitigate congestion at these points, three alternative models comprising taxiway and fast-exit taxiway reconfigurations are tested using the fast-time simulation technique. The alternative solution found to be the best in these tests is selected for further testing in real-time simulations.

It is shown that the solution would result in an increase in the number of hourly operations and a significant decrease in total ground delays. When conducting the studies needed to identify congestion and design improvements, simulation techniques save both expense and time. Although fast-time simulations are usually adequate for identifying solutions, when critical configurations for the airport are considered, it is shown that it is necessary to also test the results of the fast-time simulations in real-time simulations.

The effects of meteorological events, such as rain, fog and snow, etc. are ignored in the simulations. Ground movements in manoeuvring areas are significantly affected by the runways used. Consequently, to enable a comprehensive evaluation in the study, three alternative runway use scenarios are examined.

This study utilizes a combination of fast- and real-time simulation techniques to identify the points where congestion occurs in the manoeuvring areas of large-scale airports and to find solutions to minimize the congestion. This approach attempts to combine advantages of both techniques while reducing their shortcomings. No study is found in the literature using both of these techniques together for the capacity analysis of airport manoeuvring areas.

The purpose of this paper is to create a flight route optimization for all flights that aims to minimize the total cost consists of fuel cost, ground delay cost and air delay cost over the fixed route and free route airspaces.

Efficient usage of current available airspace capacity becomes more and more important with the increasing flight demands. The efficient capacity usage of an airspace is generally in contradiction to optimum flight efficiency of a single flight. It can only be achieved with the holistic approach that focusing all flights over mixed airspaces and their routes instead of single flight route optimization for a single airspace. In the scope of this paper, optimization methods were developed to find the best route planning for all flights considering the benefits of all flights not only a single flight. This paper is searching for an optimization to reduce the total cost for all flights in mixed airspaces. With the developed optimization models, the determination of conflict-free optimum routes and delay amounts was achieved with airway capacity and separation minimum constraints in mixed airspaces. The mathematical model and the simulated annealing method were developed for these purposes.

The total cost values for flights were minimized by both developed mathematical model and simulated annealing algorithm. With the mathematical model, a reduction in total route length of 4.13% and a reduction in fuel consumption of 3.95% was achieved in a mixed airspace. The optimization algorithm with simulated annealing has also 3.11% flight distance saving and 3.03% fuel consumption enhancement.

Although the wind condition can change the fuel consumption and flight durations, the paper does not include the wind condition effects. If the wind condition effect is considered, the shortest route may not always cause the least fuel consumption especially under the head wind condition.

The results of this paper show that a flight route optimization as a holistic approach considering the all flight demand information enhances the fuel consumption and flight duration. Because of this reason, the developed optimization model can be effectively used to minimize the fuel consumption and reduce the exhaust emissions of aircraft.

This paper develops the mathematical model and simulated annealing algorithm for the optimization of flight route over the mixed airspaces that compose of fixed and free route airspaces. Each model offers the best available and conflict-free route plan and if necessary required delay amounts for each demanded flight under the airspace capacity, airspace route structure and used separation minimum for each airspace.

Air traffic resources mainly include two parts, namely, air traffic controller (ATC) and physical system resources, such as airspace. Reasonable assessment and effective management of ATC and airspace resources are the premise and foundation of ensuring the safety and efficiency of air traffic management systems. The previous studies focussed on subjective workload control and the statistics of control communication time; they revealed the lack of kinetic universality analyses of controlling actions. Although frequency distribution patterns were generated by controlling the timing sequence, the correlation between the controlling actions and terminal airspace (TMA) sector capacity was not revealed. The paper aims to discuss these issues.

Thus, given the immeasurable complexity of controlling actions and statistical features of the controlling communications, a dynamical model of ATC was built in this study to identify the frequency distribution patterns generated by controlling the timing sequence. With the Directorate of Operational and Analysis Task method, TMA sector capacity was estimated through multiple linear regression analysis.

With data from the Kunming sector, the power exponent was calculated as 2.55, and the mathematical expectation was determined to be 47.21 s. The correlation between controlling actions (workload) and sector capacity was obtained. Finally, the data were integrated in the verification of the model and its feasibility.

Airspace capacity is an index to measure the ability of the airspace system to deliver services to meet the air traffic demand. A scientific and accurate forecast of airspace capacity is a foundation of the effective management and rational allocation of the airspace resources. The study is of great significance for the efficient use of airspace resources, controller resources.