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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.

The purpose of this study is to develop an operational level decision support system model for air traffic controllers (ATCos) within the framework of the Flexible Use of Airspace (FUA) concept to enable more efficient use of airspace capacity. This study produces a systematic solution to the route selection process so that the ATCo can determine the most efficient route with an operational decision support system model using Dijkstra’s Shortest Path Algorithm.

In this study, a new decision support system model for ATCos in decision-making positions was recommended and used. ATCos use this model as a main model for determining the shortest and safest route for aircraft as an operational-level decision support system. Dijkstra Algorithm, used in the model, is defined step by step and then explained with the pseudocode.

It has been determined that when the FUA concept and DSS are used while the ATCo chooses a route, significant fuel, time and capacity savings are achieved in flight operations. Emissions resulting from the negative environmental effects of air transportation are reduced, and significant capacity increase can be achieved. The operational level decision support system developed in the study was tested with 55 scenarios on the Ankara–Izmir flight route compared to the existing fixed route. The results for the proposed most efficient route were achieved at 11.22% distance (nm), 9.36%-time (min) savings and 837.71 kg CO₂ emission savings.

As far as the literature is reviewed, most studies aimed at increasing airspace efficiency produce solutions that try to improve rather than replace the normal process. Considering the literature positioning of this study compared to other studies, the proposed model provides a new systematic solution to the problems that cause human-induced route inefficiency within the framework of the FUA concept.

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 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).

The purpose of this paper is to create and analyze the effectiveness of a new runway system, which is totally created for the future free route operations.

This paper researches and analyses the new generated runway concept with the fast time simulation method. Fuel consumption and environmental effect of the new runway system are calculated based on simulation results.

According to different traffic density analyses the Omnidirectional Runway with Infinite Heading (ORIH) reduced fuel consumption and CO₂ emissions up to 46.97%. Also the total emissions of the ORIH concept, for the hydro carbon (HC), carbon monoxide (CO) and nitrogen oxides (NOx) pollutants were lower than the total emissions with the conventional runway up to 83.13, 74.36 and 51.49%, respectively.

Free route airspaces bring many advantages to air traffic management and airline operations. Direct routes become available from airport to airport thanks to free route airspace concept. However, conventional single runway structure does not allow aircraft operations for every direction. The landing and take-off operations of a conventional airport with a single runway must be executed with only two heading direction. This limitation brings a bottleneck direct approach and departure route usage as convenient with free route airspace concept. This paper suggests and analyzes the omnidirectional runway with infinite heading (ORIH) as a solution for free route airspace.

This paper suggests a new and futuristic runway design and operation for the free route operations. This paper has its originality from the suggested and newly created runway system.

This paper aims to present a hybrid logical-arithmetic approach for selecting optimal flight routes. It can be used in the framework of free route airspace (FRA), which is aimed at achieving higher efficiency of air traffic management.

At the first stage, an initial subset of flight routes is selected that are promising alternatives with respect to single numerical criteria. At the second stage, a hybrid multicriteria decision model is constructed, consisting of numerical criteria and additional linguistic criteria. At the third stage, the numerical and linguistic criteria are integrated into a crisp decision matrix for determining the final ranking using the technique for order preferences by similarity to an ideal solution (TOPSIS) method.

The considered decision-making problem involves different kinds of criteria. Numerical (objective) criteria are given as real numbers. Linguistic (subjective) criteria are expressed with the help of fuzzy linguistic values. In consequence, a (logical) reasoning process prior to performing an (arithmetic) optimization procedure is necessary. Furthermore, a uniform optimization procedure requires a way of combining numerical and linguistic attributes.

The proposed approach can be applied to solving various multicriteria decision-making problems, where both objective and subjective criteria are taken into account.

First, a fuzzy information system that includes linguistic condition attributes is constructed. Second, a fuzzy inference system that is necessary for determining the resulting fuzzy criterion “turbulence conditions” for all flight routes is introduced. Finally, a way of combining numerical and linguistic criteria is proposed. This is done by converting values of fuzzy attributes into crisp ones, basing on the preferences of a decision-maker.

This paper aims to assess the implications in safety levels by the integration of remotely piloted aircraft system (RPAS). The goal is to calculate the number of RPAS that can jointly operate with conventional aircraft regarding conflict risk, without exceeding current safety levels.

This approach benchmarks a calculated level of safety (CLS) with a target level of safety (TLS). Monte Carlo (MC) simulations quantify the TLS based on the current operation of conventional aircraft. Then, different experiments calculate the CLS associated with combinations of conventional aircraft and RPAS. MC simulations are performed based on probabilistic distributions of aircraft performances, entry times and geographical distribution. The safety levels are based on a conflict risk model because the safety metrics are the average number of conflicts and average conflict duration.

The results provide restrictions to the number of RPAS that can jointly operate with conventional aircraft. The TLS is quantified for four conventional aircraft. MC simulations confirm that the integration of RPAS demands a reduction in the total number of aircraft. The same number of RPAS than conventional aircraft shows an increase over 90% average number of conflicts and 300% average conflict time.

The methodology is applied to one flight level of en-route airspace without considering climbing or descending aircraft.

This paper is one of the most advanced investigations performed to quantify the number of RPAS that can be safely integrated into non-segregated airspace, which is one of the challenges for the forthcoming integration of RPAS. Particularly, Europe draws to allow operating RPAS and conventional aircraft in non-segregated airspace by 2025, but this demanding perspective entails a thorough analysis of operational and safety aspects involved.

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 study aims to design a new route model for unmanned aerial vehicles (UAVs) to integrate them into non-segregated airspace.

The proposed route model was assessed and validated through real-time simulations.

The comparison results of baseline and proposed route model show that a reduction of 38% and 41% in the total flight time and total flight distance were obtained in favour of the proposed model, respectively.

The proposed route model can be applied by airspace designers and UAV users to perform safe and efficient landing in non-segregated airspace.

In this study, a new proposed route model is constructed for UAVs. Quantitative results, using a real-time simulation method, are achieved in terms of flight distance and flight time.