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Congestion as a consequence of the rapidly growing air traffic is one of the outstanding problems of the air transportation industry. Traffic impediment rates, having an increasing acceleration while the airport capacities have been kept constant due to several reasons, cause problems such as arrival/departure delays, schedule interruptions, cancellations and customer dissatisfaction. In this paper, the author aims to study transitioning from a single-hub air transportation system to a multi-hub infrastructure via Monte Carlo simulation.

The current hub has reached its capacity limits for long so that the growth potential of the air transportation has been affected adversely. One of the possible remedies suggested by authorities, professionals and academics was to transform the air transportation infrastructure into a multi-hub setting. Current air traffic of the country was modeled by means of simulation. Airport capacities and performances are simulated and analyzed under different scenarios considering a potential alternative hub along with the central one. Possible delays in both hubs are studied in case of moderately increasing traffic congestion.

As a result, decreased delay levels in the central hub are observed, whereas no delays are experienced in the potential one in all the scenarios.

This study, proposing to organize the national and international air traffic of the country while harmonizing the delay rates and increasing the passenger satisfaction, is to contribute significantly to the aviation sector companies, airliners and airport operators by shedding light on the imminent capacity issues air transportation industry is going to face.

The paper aims to present the findings of a research project “Human Factors in ‘Fast‐Time’ Simulation” which was supported by Central European Air Traffic Services – CEATS Research, Development and Simulation Centre (CRDS) EUROCONTROL.

With the aim of improving fast‐time simulations by developing new models related to the air traffic controller's decisions, a simple traffic situation was chosen. It is focused on a pair of aircraft where one aircraft is cruising while the second is requesting clearance for climbing to the same flight level and proceeding flight “in‐trail” whereby flight level is not occupied with other traffic.

In order to determine parameters important to the controllers while making a decision, pilot inquiry was realized in the EUROCONTROL CRDS. The results obtained were used for determining the content and form of the final interview. The model based on the final interview results is designed on the “black box” principle – for certain inputs, output is a two‐dimensional decision: YES/NO give the clearance to the aircraft to climb. The model coincides to a high degree with the real system, confirming its credibility.

The established model could improve fast‐time simulations. By defining all relevant traffic situations, developing rule bases for every day traffic situations will be possible. Those rule bases could cover mayor situations which controllers are often confronted with. Integration of the model into fast‐time simulators could improve the credibility of simulated air traffic to the real traffic system.

The paper deals with the various aspects of human factor modelling in aviation.

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.

Unmanned aerial vehicles (UAVs) are more affected by adverse wind conditions in especially landing. Therefore, they need to change the runway in use. In case of this change, to eliminate the uncertain maneuvers, there is a need for a special prescribed track. The purpose of this study is the construction of a prescribed track at a single runway to provide a facility to change the runway in use.

Two forms of prescribed tracks, as standard and alternate, were constructed for UAVs by taking into consideration the key parameters to design flight procedures. Both tracks were assessed in a real-time simulation method. Moreover, unmanned vehicle simulation was used for a validation process.

According to the real-time simulation results, 8.14 NM and 6.64 NM of flight distance and 5.43 min and 4.43 min of flight time for the standard and alternate prescribed tracks were found, respectively. The obtained results were in favor of the alternate prescribed track. Furthermore, the prescribed track was assessed and validated in both air traffic control and UAV simulations. The feedback of pilots and controllers was very positive for a prescribed track, as it provided them with foresight and time to take care in any situations.

The prescribed track in this paper may be applied by airspace designers and UAV users to perform safe and efficient landing in adverse wind conditions.

In this study, a prescribed track was constructed for UAVs. Quantitative results were achieved using a real-time simulation method in terms of flight distance and flight time. Additionally, validation of the prescribed track was achieved by unmanned air vehicle simulation.

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.

The surveillance equipment is one of the most important parts for current air traffic control systems. It provides aircraft position and other relevant information including flight parameters. However, the existing surveillance equipment has certain position errors between true and detected positions. Operators must understand and account for the characteristics on magnitude and frequency of the position errors in the surveillance systems because these errors can influence the safety of aircraft operation. This study aims to develop the simulation model for analysis of these surveillance position errors to improve the safety of aircrafts in airports.

This study investigates the characterization of the position errors observed in airport surface detection equipment of an airport ground surveillance system and proposes a practical method to numerically reproduce the characteristics of the errors.

The proposed approach represents position errors more accurately than an alternative simple approach. This study also discusses the application of the computational results in a microscopic simulation modeling environment.

The surveillance error is analyzed from the radar trajectory data, and a random generator is configured to implement these data. These data are used in the air transportation simulation through an application programing interface, which can be applied to the aircraft trajectory data in the simulation. Subsequently, additionally built environment data are used in the actual simulation to obtain the results from the simulation engine.

The presented surveillance error analysis and simulation with its implementation plan are expected to be useful for air transportation safety simulations.

The use of the 4D trajectory operational concept in the future air traffic management (ATM) system will require the aircraft to meet very accurately an arrival time over a designated checkpoint. To do this, time intervals known as time windows (TW) are defined. The purpose of this paper is to develop a methodology to characterise these TWs and to manage the uncertainty associated with the evolution of 4D trajectories.

4D trajectories are modelled using a point mass model and EUROCONTROL’s BADA methodology. The authors stochastically evaluate the variability of the parameters that influence 4D trajectories using Monte Carlo simulation. This enables the authors to delimit TWs for several checkpoints. Finally, the authors set out a causal model, based on a Bayesian network approach, to evaluate the impact of variations in fundamental parameters at the chosen checkpoints.

The initial results show that the proposed TW model limits the deviation in time to less than 27 s at the checkpoints of an en-route segment (300 NM).

The objective of new trajectory-based operations is to efficiently and strategically manage the expected increase in air traffic volumes and to apply tactical interventions as a last resort only. We need new tools to support 4D trajectory management functions such as strategic and collaborative planning. The authors propose a novel approach for to ensure aircraft punctuality.

The main contribution of the paper is the development of a model to deal with uncertainty and to increase predictability in 4D trajectories, which are key elements of the future airspace operational environment.

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.

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 study is to provide conflict-free operations in terminal manoeuvre areas (TMA) using the point merge system (PMS), airspeed reduction (ASR) and ground holding (GH) techniques. The objective is to minimize both total aircraft delay (TD) and the total number of the conflict resolution manoeuvres (CRM).

The mixed integer linear programming (MILP) is used for both single and multi-objective optimization approaches to solve aircraft sequencing and scheduling problem (ASSP). Compromise criterion and ε-constraint methods were included in the methodology. The results of the single objective optimization approach results were compared with baseline results, which were obtained using the first come first serve approach, in terms of the total number of the CRM, TD, the number of aircraft using PMS manoeuvres, ASR manoeuvres, GH manoeuvres, departure time updates and on-time performance.

The proposed single-objective optimization approach reduced both the CRM and TD considerably. For the traffic flow rates of 15, 20 and 25 aircraft, the improvement of CRM was 53.08%, 41.12% and 32.6%, the enhancement of TD was 54.2%, 48.8% and 31.06% and the average number of Pareto-optimal solutions were 1.26, 2.22 and 3.87, respectively. The multi-objective optimization approach also exposed the relationship between the TD and the total number of CRM.

The proposed mathematical model can be implemented considering the objectives of air traffic controllers and airlines operators. Also, the mathematical model is able to create conflict-free TMA operations and, therefore, it brings an opportunity for air traffic controllers to reduce frequency occupancy time.

The mathematical model presents the total number of CRM as an objective function in the ASSP using the MILP approach. The mathematical model integrates air traffic controllers’ and airline operators’ perspective together with new objective functions.