Congested airports benefit from parallel-point merge systems (P-PMSs) for efficient arrival route control. However, the decline in air traffic due to COVID-19 has curtailed its optimal utilisation, especially with the reduced need for long sequencing legs. As air traffic is poised to rebound, the evident volatility seen during and post COVID-19, as well as the daily fluctuations between peak and off-peak hours, underscore the importance of the dynamic utilisation of sequencing legs in P-PMSs. EUROCONTROL proposes various leg configurations to manage fluctuating traffics, ensuring both efficiency and safety. First, we proposed two additional leg configurations for the Istanbul Airport, offering continuous descent with the engines operating at idle thrust during leg flights; partially overlapped and fully dissociated. While they offer an alternative for controllers during low to medium traffic scenarios, current long and fully overlapped parallel legs may be used in high traffic due to the volatility of traffic density throughout a day. Therefore, we suggest an approach that provides dynamic utilisation of these configurations. We first modeled and analysed the configurations for various traffic numbers and scenarios. Then, we introduced a new stochastic matheuristic model that considers the configuration changes throughout the day and provides feasible and robust sequences applicable to all configurations by combining the benefits of mathematical models with the adaptability and speed of heuristic methods. Several test problems were evaluated using the terminal manoeuvering area structure of Istanbul Airport as a case study. The results indicate that by changing configurations, an average of 35 kg in fuel savings per aircraft can be achieved. The results also show that the proposed approach outperforms traditional stochastic mathematical models and the first-come first-serve (FCFS) strategy, ensuring efficient air traffic management in terms of fuel and delay with robust sequencing by eliminating the need for re-sequencing during configuration changes.

The aviation industry has rapidly developed in recent years. Due to the increased number of flight operations, managing air traffic has become essential. The air traffic management system aims to reduce the air traffic control workload and use existing resources more efficiently. This study proposed a new mixed integer linear programming model to minimise the total fuel consumption during taxi operations for the runway assignment problem, comparing the actual Istanbul Airport runway assignment data. The average taxi times are calculated using the 30,000-flight operations data for each arrival and departure taxi route. Also, 47 different aircraft types are obtained using the data for the fuel consumption calculation. The International Civil. Aviation Organisation (IACO) aircraft engine emissions databank provides the fuel consumption values for each aircraft according to engine type. This approach allows our model to calculate more realistic fuel consumption for taxi operations, as each aircraft engine type has a different fuel consumption value. The proposed model is implemented at Istanbul Airport, the busiest airport in Turkey, where multiple parallel runway operations are applied. The results showed that the proposed model reduced total fuel consumption for taxi operations between 6.6% and 14.4% compared to the actual Istanbul Airport runway assignment data.

The Istanbul metroplex airspace, home to Atatürk (LTBA), Sabiha Gökçen (LTFJ), and Istanbul (LTFM) international airports, is a critical hub for international travel, trade and commerce between Europe and Asia. The high air traffic volume and the proximity of multiple airports make air traffic management (ATM) a significant challenge. To better manage this complex air traffic, it is necessary to conduct detailed analyses of the capacities of these airports and surrounding airspace. In this study, Monte Carlo simulation is used to determine the ultimate and practical capacities of the airport and surrounding airspace and compare them to identify any differences or limitations. The traffic mix, runway occupancy time and traffic distribution at airspace entry points are randomised variables that directly impact airport and airspace capacities and delays. The study aims to determine the current capacities of the runways and routes in the metroplex airspace and project the future capacities with the addition of new facilities. The results demonstrated that the actual bottleneck could be experienced in airspace, rather than runways, which was the focus of the previous literature. Thus, this study will provide valuable insights for stakeholders in the aviation industry to effectively manage air traffic in the metroplex airspace and meet the growing demand.

Free route airspace (FRA) are increasingly widespread in European countries. A step further, cross-border FRA aims to implement FRA in a seamless,defragmented airspace in Europe. This study aims to bring a different perspective by extending the scope of cross-border FRA applications beyond socioeconomic status (SES) countries. In the study, analyses were made using fast-time simulation outputs for one of the busiest days of Turkish airspace in 2022. The simulation models of four cases were created and compared in such a way that airspaces of Türkiye, South East Europe free route airspace (SEEFRA) countries and Ukraine combined under different border operations above FL285. Flight trajectories were assessed in terms of flight distance, fuel economy and environmental impact within the aforementioned airspaces. The participation of Turkish airspace in the cross-border region and opening of Ukrainian airspace are examined. Concluded, among all, cross-border FRA implemented through all aforementioned regions (Case 4) may constitute the best benefit for flight trajectories and related variables.

Global air traffic demand has shown rapid growth for the last three decades. This growth led to more delays and congestion within terminal manoeuvring areas (TMAs) around major airports. The efficient use of airport capacities through the careful planning of air traffic flows is imperative to overcome these problems. In this study, a mixed-integer nonlinear programming (MINLP) model with a multi-objective approach was developed to solve the aircraft sequencing and scheduling problem for mixed runway operations within the TMAs. The model contains fuel cost functions based on airspeed, altitude, bank angle, and the aerodynamic characteristics of the aircraft. The optimisation problem was solved by using the $\varepsilon$-constraint method where total delay and total fuel functions were simultaneously optimised. We tested the model with different scenarios generated based on the real traffic data of Istanbul Sabiha Gökçen Airport. The results revealed that the average total delay and average total fuel were reduced by 26.4% and 6.7%, respectively.

With the increase of air transportation, some crossing waypoints (CWPs) are becoming bottlenecks in the operation of air traffic networks. This paper presents a CWP operation optimisation framework based on a two-stage optimisation method. First, we considered the interests of airlines and air traffic controllers and established a flight-level dynamic allocation model for the CWP to minimise the flight-level deviation and the number of flight conflicts. A multi-objective, self-adaptive differential evolution-local search hybrid algorithm was used to solve the model in a parallel computing manner. Subsequently, a flight conflict resolution algorithm based on the Monte-Carlo tree search was designed for flight conflicts that existed after the optimisation. Finally, based on real operation data, four experimental scenarios were constructed, and the air traffic operation simulation system was used for experimental validation. For daily traffic and 1.2 times peak traffic scenarios, the average flight-level deviation reduction rates after optimisation were 53% and 39%, and the successful flight conflict resolution rates reached 89% and 75%, respectively. The experimental results showed that this optimisation framework can effectively balance the number of flight conflicts with the efficiency of flight-level usage and directly improve the capacity of the CWP, which can be used as a reference for air traffic control auxiliary decision support systems.

In some small airports, a parallel taxiway is not built due to space restrictions or financial issues; hence, the runway itself is often used as a taxiway in this type of airport. After touch down, aircraft move to the U-turn area at the end of the runway and turn 180 degrees, then move back to the desired point, such as a gate or the apron, using the runway. The runway is blocked to other arrivals and departures during this process. This process, called backtrack or back-taxi, can result in high delays for both arrivals and departures. Runway occupancy times (ROTs) vary depending on numerous conditions, including pilot performance, weather conditions, aircraft type, etc. Although there are speed restrictions and procedures announced in advance, the actual performance can be uncertain. In addition, most aircraft can make a U-turn as soon as they sufficiently reduce their speed before they reach the U-turn area especially if they are already delayed. These situations bring enormous uncertainties for traffic management at such an airport. Controllers may need help to sequence aircraft, particularly in busy traffic. In this study, a stochastic mathematical model is developed to sequence arrival/departure operations at such an airport considering the ROT uncertainties of arrivals. The objective function of the developed model is determined as the minimisation of the total delay. ROT data was obtained by observing radar tracks of 120 arriving flights. Reasonable ROT scenarios with various probabilities to represent ROT uncertainties were integrated into the mathematical modeling. In addition, two different sequencing approaches are presented as well as the first come first serve (FCFS) approach. As a result, the proposed stochastic approach provides robust sequences applicable for all ROT scenarios with significant delay savings up to an average of 18.4% and 39.5% compared to deterministic and FCFS approaches, respectively.

This study proposes a new operational concept of the Point Merge System, called Multi-Arrival Route Point Merge System (MAR-PMS), which is an air traffic control method used to sequence aircraft arrivals in a given terminal control area. The proposed concept enables the additional arrival routes that have an angular difference to each sequencing leg. Furthermore, a time-indexed 0-1 linear programming model is formulated. The obtained results are validated in a real time simulation. The comparison results of PMS and MAR-PMS show that the average reduction of 19% of total flight time, 23% of total flight distance, and 19% in total fuel burned and reduction in CO2 emissions in favor of a proposed concept.

This study investigates a new aircraft flight trajectory optimisation method, derived from the Non-dominated Sorting Genetic Algorithm II method used for multi-objective optimisations. The new method determines, in parallel, a set of optimal flight plan solutions for a flight. Each solution is optimal (requires minimum fuel) for a Required Time of Arrival constraint from a set of candidate time constraints selected for the final waypoint of the flight section under optimisation. The set of candidate time constraints is chosen so that their bounds are contiguous, i.e. they completely cover a selected time domain. The proposed flight trajectory optimisation method may be applied in future operational paradigms, such as Trajectory-Based Operations/free flight, where aircraft do not need to follow predetermined routes. The intended application of the proposed method is to support Decision Makers in the planning phase when there is a time constraint or a preferred crossing time at the final point of the flight section under optimisation. The Decision Makers can select, from the set of optimal flight plans, the one that best fits their criteria (minimum fuel burn or observes a selected time constraint). If the Air Traffic Management system rejects the flight plan, then they can choose the next best solution from the set without having to perform another optimisation. The method applies for optimisations performed on lateral and/or vertical flight plan components. Seven proposed method variants were evaluated, and ten test runs were performed for each variant. For five variants, the worst results yielded a fuel burn less than 90kg (0.14%) over the ‘global’ optimum. The worst variant yielded a maximum of 321kg (0.56%) over the ‘global’ optimum.

Recent research on Flight-deck Interval Management (FIM), a modern technology for increasing safety and improving airspace and runway utilisation through self-spacing, has led to the development of a new rule-based logic for FIM, namely Interval Management – Speed Planning (IM-SP). In an initial benchmark study, IM-SP showed good spacing performance with a significant reduction in speed commands, a major area of concern with previous FIM logics, resulting in a lower burden on the flight crew during FIM operation. Nevertheless, there remains scope for improvement in other aspects, such as fuel burn. In this study, the internal cost function of IM-SP is further analysed and optimised using speed-constrained multi-objective particle swarm optimisation to improve the performance of IM-SP under the multiple objectives of FIM. The optimisation renders new settings that address the problem areas, improve the speed commands and enhance the overall quality of IM-SP. Two distinctive solutions, viz. a spacing performance optimised setting and a fuel burn optimised setting, are further analysed and discussed, and directions for follow-up research are explored.

Flight-deck Interval Management (FIM) is a modern airborne self-spacing technology that improves arrival route throughput and runway utilisation and increases hourly arrival capacity by up to four aircraft per hour and per runway, compared to conventional air traffic controller guided arrivals. The National Aeronautics and Space Administration (NASA) has been the leader in FIM research and formulated a logic that was put to an actual flight test in 2017. Despite the overall success of the project, operational deficiencies concerning the number of speed commands, which led to several recommendations for future research before operational implementation, were discovered. In this study, a new logic that implements a two-stage rule-based selection algorithm was developed to overcome those deficiencies. The proposed logic was compared to NASA’s logic on an arrival in Tokyo International Airport with multiple induced error patterns. The results indicate that the new logic significantly decreases the number of speed commands with only minor aggravations in spacing performance. The results that highlight the strengths and weaknesses of both concepts are discussed, and an outlook on and ideas for future research on FIM and the proposed logic are presented.

The general problem of determining cruise fuel burn is addressed by considering the variation of the product of engine overall efficiency and airframe lift-to-drag ratio, (ηoL/D), with Mach number and lift coefficient. This quantity is the aerothermodynamic determinant of fuel burn rate. Using a small amount of real aircraft data and exploiting normalisation, it is found that near universal relationships exist between the key variables. With this major simplification, an analytic, near exact solution is derived in which the aircraft-related input data are reduced to just three parameters, namely the optimum value of (ηoL/D) and the lift coefficient and Mach number combination at which it occurs. These are quantities that are either available from open information sources or can be estimated using established analytic methods. By introducing models of the take-off and climb and the descent and landing phases, the method is extended to provide accurate trip fuel estimates.

It is shown that there is an ideal flight level (IFL) at which the fuel consumption rate is a minimum for all speeds in the normal cruise operating range. Furthermore, the IFL at the end of cruise is approximately the same for all aircraft, whilst the IFL at the beginning of cruise depends, primarily, on the distance to be flown. There is little dependence on the size of the aircraft, or its take-off mass.

In the context of the ‘fuel-based’ assessment of operational inefficiency, the method is further developed to determine the sensitivity of the trip fuel requirement to changes in the operational parameters governed by air traffic management (ATM). The result is two simple equations. These are used to estimate the current ATM fuel burden. At the global level, this is about 20% with more than half being attributable to flights of less than 1,200 km.

Finally, the method is used to estimate the fuel burn penalty associated with reducing contrail formation by simply avoiding those regions of the atmosphere that are supersaturated with respect to ice. If the aircraft is at the IFL when avoiding action is required, flying below the supersaturated region minimises the additional fuel use. Even when multiple evasive manoeuvres are needed, the additional trip fuel requirement is expected to be less than 0.5%.

A flow corridor is a new class of trajectory-based airspace that encloses groups of flights which fly along the same path in one direction and accept responsibility for separation from each other. A well-designed corridor could reduce the airspace complexity, decrease the workload of air traffic controllers and increase the airspace capacity. This paper analyses the impact of different self-separation parameters on capacity and conflicts of the flow corridor. Both the quantitative impact and interaction effects of pairs of parameters are evaluated using the combined discrete-continuous model and Monte Carlo simulation method. The simulation results show that although the initial separation is the dominating factor, the interactions between initial separation and separation buffer, minimum separation, extra switch buffer, extra threshold buffer and velocity difference threshold also have some significant impacts on the capacity and conflicts for the flow corridor.

Air Traffic Management (ATM) research generally focuses on achieving a safer, more effective and economical air traffic system. The current airspace system has become increasingly strained as the demand for air travel has steadily grown. Innovative, proactive and multi-disciplinary approaches to research are needed to solve flight congestion and delays as a consequence of this rapid growth. As a result of this growth, air traffic flow becomes more complex, especially in Terminal Airspaces (TMA) where climb and descent manoeuvres of departing and arriving flights take place around airports. As air traffic demand exceeds the capacity in a TMA, the resultant congestion leads to delays that spread all over the system. Therefore, the reduction of delays is critical for airspace designers to increase customer satisfaction and the perception of service quality. Numerous studies have been conducted to reduce delays within TMAs. This research focuses on defining the causes of delays quantitatively through statistical analysis. The first step was to create a fast-time simulation model of sample airspace for collecting delay data. After building up this model using the SIMMOD fast-time ATM simulation tool, simulation experiments were run to produce various traffic scenarios and to generate traffic delay data. The number of airports, entry points, fixes and flight operations in airspace and the probability of wide-body aircraft were considered as independent variables. The correlations between the considered variables were analysed, and the total delay data was modelled using a linear regression model. The findings of regression model present a statistical approach for airspace designers and air traffic flow planners.

The CNS/ATM concept envisages reliance on global satellite navigation systems to underpin future air traffic management that is able to cope with the ever-increasing demand for air travel without jeopardising safety and the environment. In order to benefit from GNSS, it is crucial that the navigation performance required of air navigation systems is derived and agreed, based on sound principles. Significant work has been undertaken to date and agreement reached on the navigation requirements for the phases of flight up to Category I (CAT-I) precision approach, and proposals are under discussion for CAT-III precision approach. This paper completes a typical flight profile by addressing airport surface movement, and proposing the requirements based on operational requirements for each airport category, to support operations in zero visibility conditions. The benefits of the approach taken in the derivation of the requirements are discussed relative to the existing navigation requirements.

European Air Traffic Management is extremely safe. The drawback to this safety record is that it is very difficult to estimate what the ‘underlying’ accident rate for mid-air collisions is now, or to detect any changes over time. The aim is to see if it possible to construct simple ATM safety indicators that correlate with this underlying accident rate. A perfect indicator would be simple to comprehend and capable of being calculated by a checklist process. This problem has been examined using a combination of analogies with simple ‘defensive’ systems with Markov process properties. An important concept is that of ‘system control’: the ability to determine the outcome against reasonably foreseen changes and variations of system parameters. The statistical distribution of future incidents has been analysed by focusing on an index – the Close Proximity Index (CPI) – of separation at the Closest Point of Approach. A promising indicator is ‘Incident Not Resolved by ATC’ (INRA) incidents in which the ground ATC defences have been ‘used up’. ATM Incidents can also be categorised in other ways. Two examples are reviewed: the risk-bearing category for Airproxes and ‘risk of collision/severity’ scores. The second is more promising conceptually, but the existing scoring system has not been demonstrated to have the properties necessary to derive risk estimates. The key question is: if someone says they know how to make a good estimate of the underlying accident rate, then how could this claim be tested? If it correlates very well with INRA, then what would be the argument for saying that it is a better indicator?