Future Air Traffic Management System Research Articles

On the Possibilities of Efficient Air Traffic Monitoring through Complex Network Clustering Based Airspace Sub-Sectorization: A Multi-Objective Discrete Particle Swarm Optimization Approach

This study models the airspace sub-sectorization problem as a multi-objective complex network clustering problem. A decomposition-based discrete particle swarm optimization (DPSO) algorithm is then used to solve the problem, followed by applying the minimum bounding geometry method to design convex and compact boundaries. An Indian airspace sector was considered to validate the proposed framework. The waypoints and routes within the sector were represented as a network graph, and discretized traffic loads were randomly allotted to the vertices to guide the DPSO. The maximum number of generations or iterations was set as the termination criteria. The proposed approach generates clusters that result in all sub-sectors having a medium traffic load, ensuring equity that is difficult to achieve. This framework offers enough flexibility to avoid several strict constraints, thereby reducing the problem’s complexity. Moreover, the proposed framework improves the adaptability of sub-sectors to network evolution and traffic conditions, recognizing the hierarchical characteristics of air transport networks. The present research also motivates several research opportunities and possibilities for future air traffic management systems.

Airborne Separation Assistance during Landing - An Approach for Automation

Self-spacing and Required-Time-of-Arrival (RTA) concepts are now being developed to support future Air Traffic Management (ATM) systems. Among many types of separation methods, distance based separation assumes importance form safety point of view. The present study is an attempt to analyze approach proposed by EUROCAE and extend the same for development of guidance laws in the form of acceleration commands instead of speed commands. Objective is to realize an effective implementation of the guidance laws in the Thrust Management Function of onboard Flight Management System. Simulation studies are presented involving actual flight responses for the lead aircraft during terminal phase.

Evaluation of Extended Projected Profiles impact on vertical trajectory prediction

The future Air Traffic Management System (ATM) is based on the concept of Trajectory Based Operations (TBO), in which all stakeholders have access to a consistent and synchronised view of flight trajectories. In the TBO framework, the trajectory prediction plays a key role. Inaccuracy of current trajectory predictors caused by the lack of a common understanding of stakeholders’ intents can be reduced by the sharing of information by airspace users. A step towards a shared information network is the Extended Projected Profile (EPP), downlinked from airborne to ground via automatic dependent surveillance contract (ADS-C). In summary, it contains the flight intent from the Flight Management System (FMS) and other information. This paper explores the EPP messages and the possible performance enhancement they introduce in the predictions of the top of descent (TOD) and the descent vertical profile. 1

Hyperheuristic Approach Based on Reinforcement Learning for Air Traffic Complexity Mitigation

Airspace capacity has become a critical resource for air transportation. Complexity in traffic patterns is a structural problem, whereby airspace capacity is sometimes saturated before the number of aircraft has reached the capacity threshold. This paper addresses a strategic planning problem with an efficient optimization approach that minimizes traffic complexity based on linear dynamical systems in order to improve the traffic structure. Traffic structuring techniques comprise departure time adjustment, en route trajectory deviation, and flight-level allocation. The resolution approach relies on the hyperheuristic framework based on reinforcement learning to improve the searching strategy during the optimization process. The proposed methodology is implemented and tested with a full day of traffic in the French airspace. Numerical results show that the proposed approach can reduce air traffic complexity by 92.8%. The performance of the proposed algorithm is then compared with two different algorithms, including the random search and the standard simulated annealing. The proposed algorithm provides better results in terms of air traffic complexity and the number of modified trajectories. Further analysis of the proposed model was conducted by considering time uncertainties. This approach can be an innovative solution for capacity management in the future air traffic management system.

Efficiency-Thoroughness Trade-Off Characteristics of Air Traffic Controllers During Tower Operations

Air traffic demand has been growing for years and many countries are trying to solve this situation by modernizing their national airspace through advanced automation. Those projects aim to provide a greater level of efficiency while ensuring a safe flow of air traffic. However, human air traffic controllers have been coping with difficult situations and unexpected events by flexibly balancing efficiency and thoroughness throughout their operations. In this study, we conducted an experiment using a simulator depicting air traffic control tower operations and analyzed the trade-off decisions made by humans under varying situations. By doing so, we proposed a model with the aim of applying the results to future air traffic management systems. This could allow those autonomous systems to make decisions that are similar to those of human preferences, which could lead to a proactive management of safety and a higher level of automation acceptance.

Innovative time-based separation procedures for civil RPAS integration

Purpose This paper aims to suggest feasible solutions to overcome the problem of unmanned aerial vehicles integration within the existing airspace. Design/methodology/approach It envisages innovative time-based separation procedures that will enhance the integration in the future air traffic management (ATM) system of next generation of large remotely piloted aircraft system (RPAS). 4D navigation and dynamic mobile area concepts, both proposed in the framework of Single European Sky ATM Research program, are brought together to hypothesize innovative time-based separation procedures aiming at promoting integration of RPAS in the future ATM system. Findings Benefits of proposed procedures, mainly evaluated in terms of volume reduction of segregated airspace, are quantitatively analyzed on the basis of realistic operational scenarios focusing on monitoring activities in both nominal and emergency conditions. Eventually, the major limits of time-based separation for RPAS are investigated. Practical implications The implementation of the envisaged procedures will be a key enabler in RPAS integration in future ATM integration. Originality/value In the current ATM scenario, separation of RPAS from air traffic is ensured by segregating a large amount of airspace areas with fixed dimensions, dramatically limiting the activities of these vehicles.

4D-trajectory time windows: definition and uncertainty management

PurposeThe 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.Design/methodology/approach4D 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.FindingsThe 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).Practical implicationsThe 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.Originality/valueThe 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.

Potential safety occurrences as indicators of air traffic management safety performance: A network based simulation model

This paper presents a Network Based Simulation Model developed with the objective of assessing novel safety performance indicators of the future Air Traffic Management system. A set of seven safety performance indicators is proposed based on Potential Safety Occurrences. Developed model contains three modules: separation violation detection module, TCAS activation module and risk of conflict assessment module. It was tested with planned flight trajectories crossing French and FABEC airspace during 24 h, covering several ATM improvement scenarios and different traffic demand levels. Results show capabilities to calculate certain safety performance indicators and to provide valuable safety feedback to traffic and airspace planners. Also, benefits of different ATM improvements to ATM safety performance have been estimated.

Flight trajectory data analytics for characterization of air traffic flows: A comparative analysis of terminal area operations between New York, Hong Kong and Sao Paulo

Future Air Traffic Management systems can benefit from innovative approaches that leverage the increasing availability of operational data to facilitate the development of new performance assessment and decision-support capabilities. This paper presents a data analytics framework for high-fidelity characterization of air traffic flows from large-scale flight tracking data. Machine learning methods are used to exploit spatiotemporal patterns in aircraft movement towards the identification of trajectory patterns and traffic flow patterns. The outcomes and potential impacts of this framework are demonstrated with a comparative analysis of terminal area operations in three representative multi-airport (metroplex) systems of the global air transportation system: New York, Hong Kong and Sao Paulo. As a descriptive tool for systematic analysis of the flow behavior, the framework allows for cross-metroplex comparisons of terminal airspace design, utilization and traffic performance. Novel quantitative metrics are created to summarize metroplex efficiency, capacity and predictability. The results reveal several structural, operational and performance differences between the multi-airport systems analyzed. Our findings show that New York presents the most complex airspace design, with considerably higher number of routes and interactions between them, as well as more dynamic changes in the terminal area flow structure during the day, in part driven by the presence of flow dependencies. Interestingly, it exhibits the best levels of traffic flow efficiency on average, both spatially and temporally, yet the highest variability in metroplex configuration performance, with more pronounced performance degradation during inclement weather.

Automated optimal flight planning based on the aircraft intent description language

The future air traffic management system is to be built around the notion of trajectory-based operations. It will rely on automated tools related to trajectory prediction in order to define, share, revise, negotiate and update the trajectory of the aircraft before and during the flight, in some case, in near real time. This paper illustrates how existing standards on trajectory description such as the aircraft intent description language can be enhanced including optimisation capabilities based on numerical optimal control. The Aircraft Intent Description Language is a formal language that has been created in order to describe aircraft intent information in a rigorous, unambiguous and flexible manner. It has been implemented in a platform for a modular design of the trajectory generation process. A case study is presented to explore its effectiveness and identify the requirements and needs to generate optimised aircraft intents with higher automation and flexibility. Preliminary results show the suitability of numerical optimal control to design optimised aircraft intents based on the aircraft intent description language.

A Novel Performance Framework and Methodology to Analyze the Impact of 4D Trajectory Based Operations in the Future Air Traffic Management System

The introduction of new Air Traffic Management (ATM) concepts such as Trajectory Based Operations (TBO) may produce a significant impact in all performance areas, that is, safety, capacity, flight efficiency, and others. The performance framework in use today has been tailored to the operational needs of the current ATM system and must evolve to fulfill the new needs and challenges brought by the TBO content. This paper presents a novel performance assessment framework and methodology adapted to the TBO concept. This framework can assess the key performance areas (KPAs) of safety, capacity, and flight efficiency; equity and fairness are also considered in this research, in line with recent ATM trends. A case study is presented to show the applicability of the framework and to illustrate how some of the complex interdependencies among KPAs can be captured with the proposed approach. This case study explores the TBO concept of “strategic 4D trajectory deconfliction,” where the early separation tasks of 4D trajectories at multisector level are assessed. The framework presented in this paper could potentially support the target-setting and performance requirements identification that should be fulfilled in the future ATM system to ensure determined levels of performance.

Robust Aircraft Trajectory Planning Under Wind Uncertainty Using Optimal Control

Uncertainty in aircraft trajectory planning and prediction generates major challenges for the future air traffic management system. Therefore, understanding and managing uncertainty will be necessary to realize improvements in air traffic capacity, safety, efficiency, and environmental impact. Meteorology (in particular, winds) represents one of the most relevant sources of uncertainty. In the present work, a framework based on optimal control is introduced to address the problem of robust and efficient trajectory planning under wind forecast uncertainty, which is modeled with probabilistic forecasts generated by ensemble prediction systems. The proposed methodology is applied to a flight planning scenario under a free-routing operational paradigm and employed to compute trajectories for different sets of user preferences, exploring the trade-off between average flight cost and predictability. Results show how the impact of wind forecast uncertainty in trajectory predictability at a pretactical planning horizon can be not only quantified, but also reduced through the application of the proposed approach.

Toward a Single European Sky

To meet rising traffic projections over the next 20 years, Eurocontrol must develop Europe's first uniform air traffic control standards. This case illustrates the usefulness of management science methods for obtaining agreement and commitment among stakeholders. Excerpt UVA-QA-0736 March 26, 2010 Toward a Single European Sky On the journey toward an integrated air traffic management system in Europe by 2020, the key date was January 24, 2007. On that day, the Single European Sky Air Traffic Management Research (SESAR) program held a stakeholder forum in Geneva to encourage the entire air transport community to commit to performance targets for future European air traffic management (ATM) systems. For the first time in European air traffic management history, the SESAR consortium brought together all major stakeholders in European aviation, including airspace users, air navigation service providers (ANSPs), airport operators, safety regulators, military organizations, and research centers. In all, the forum comprised 76 people representing 30 stakeholder groups. Eurocontrol The primary objective of Eurocontrol, Europe's air traffic management (ATM) organization, was the development of a seamless, pan-European ATM system. Eurocontrol developed, coordinated, and planned the implementation of European ATM strategies and their associated operational plans in collaboration with national authorities, air navigation service providers (ANSP), civil and military airspace users, airports, manufacturers, professional organizations, and relevant European institutions. Eurocontrol's core activities spanned the entire range of gate-to-gate air navigation service operations, from strategic and tactical-flow management to controller training, from regional control of airspace to the development of leading-edge technologies and procedures. In 2007, Eurocontrol had 38 member states and was headquartered in Brussels, Belgium. The agency had approximately 2,400 staff located in seven European countries and reported to the transport and defense ministers in the European Commission. . . .

An aircraft noise prediction model considering meteorological effects on noise propagation developed for air traffic optimization

With the growing transportation demand, the volume of air traffic is already approaching and will soon exceed the capacity limit posed by current air traffic control. Japan Aerospace Exploration Agency (JAXA) has conducted a research project called DREAMS, aiming to develop technologies for future air traffic management system. One of the research topics examined by the project is noise abatement flight technology. It optimizes approach paths considering the meteorological effects on noise propagation. Its key element is an aircraft noise prediction model which can take into account the effect of meteorological conditions on noise propagation. The effect is computed by Green’s Function-Parabolic Equation method and verified by field experiment using an elevated sound source. Aircraft noise is measured around approach flight path for overall verification, and the results show the average and the standard deviations of the prediction error are -0.66 dB and 1.55 dB, respectively. The presentation provides an...

Collocation Methods to Minimum-Fuel Trajectory Problems with Required Time of Arrival in ATM

In the future air traffic management system, the trajectory becomes the fundamental element of a new set of operating procedures collectively referred to as trajectory-based operations. Trajectory-based operations require the air traffic management to introduce profound innovations to enable the envisioned changes. Some of these include collaborative decision-making processes, better data and information management, and advanced decision support tools to aid human operators. In particular, fast and accurate computation of optimal trajectories could certainly contribute to enhance trajectory management within the future air traffic management. The trajectory optimization problem can be solved using optimal control methods. In this paper, the existing methods for solving optimal control problems focusing on direct collocation are discussed. In particular, pseudospectral collocation methods have shown to be numerically more accurate and computationally much faster than other direct methods. A very relevant problem arising in air traffic management is analyzed, that is the minimum-fuel trajectory with required time of arrival. Preliminary results illustrate the advantages of using pseudoespectral collocation methods for trajectory optimization in air traffic management; for the same order of numerical accuracy, they present computational times that are at least two orders of magnitude better than other collocation methods. For similar computational times, pseudospectral collocation methods achieve a numerical accuracy that is at least one order of magnitude better than other methods.

Coloured Petri net-based traffic collision avoidance system encounter model for the analysis of potential induced collisions

The Traffic Alert and Collision Avoidance System (TCAS) is a world-wide accepted last-resort means of reducing the probability and frequency of mid-air collisions between aircraft. Unfortunately, it is widely known that in congested airspace, the use of the TCAS may actually lead to induced collisions. Therefore, further research regarding TCAS logic is required. In this paper, an encounter model is formalised to identify all of the potential collision scenarios that can be induced by a resolution advisory that was generated previously by the TCAS without considering the downstream consequences in the surrounding traffic. The existing encounter models focus on checking and validating the potential collisions between trajectories of a specific scenario. In contrast, the innovative approach described in this paper concentrates on quantitative analysis of the different induced collision scenarios that could be reached for a given initial trajectory and a rough specification of the surrounding traffic. This approach provides valuable information at the operational level. Furthermore, the proposed encounter model can be used as a test-bed to evaluate future TCAS logic changes to mitigate potential induced collisions in hot spot volumes. In addition, the encounter model is described by means of the coloured Petri net (CPN) formalism. The resulting state space provides a deep understanding of the cause-and-effect relationship that each TCAS action proposed to avoid an actual collision with a potential new collision in the surrounding traffic. Quantitative simulation results are conducted to validate the proposed encounter model, and the resulting collision scenarios are summarised as valuable information for future Air Traffic Management (ATM) systems.

Airline-Driven Performance-Based Air Traffic Management: Game Theoretic Models and Multicriteria Evaluation

Defining air traffic management as the tools, procedures, and systems employed to ensure safe and efficient operation of air transportation systems, an important objective of future air traffic management systems is to support airline business objectives, subject to ensuring safety and security. Under the current model for designing air traffic management initiatives, the central authority overseeing and regulating air traffic management in a region makes trade-offs between specified performance criteria. The research presented in this paper aims instead to allow the airline community to set performance goals and thus make trade-offs between different performance criteria directly, before specific air traffic management strategies are determined. We propose several approaches for collecting inputs from airlines in a systematic way and for combining these airline inputs into implementable air traffic management initiatives. These include variants of averaging, voting, and ranking mechanisms. We also propose multiple criteria for evaluating the effectiveness of each approach, including Pareto optimality, airline profitability, system optimality, equity, and truthfulness of airline inputs. We apply a game-theoretic approach to examine the potential for strategic (gaming) behavior by airlines. We offer a broad evaluation of each approach, first by providing some theoretical insights, and then by simulating each of the approaches for a generic system using Monte Carlo methods, sampling values for input parameters from a wide range. We also provide an indication of how the approaches might perform in a real system by simulating ground delay programs at two airports in the New York City area. We first apply a simplified model that simulates the process of selecting only planned end times of a ground delay program, using Monte Carlo methods. Next, we apply a more detailed model that simulates the process of selecting planned end times and reduced airport arrival rates. Finally, we characterize the effectiveness of each of the considered approaches on the proposed criteria and identify the most desirable approaches. We conclude that voting schemes, which score highly on all criteria (including airline profitability, system optimality, and equity), represent the most promising approaches (among those considered) to elicit airline preferences, thereby allowing the central authority to design air traffic management initiatives that optimize system performance while respecting the objectives of airlines.

The long journey toward a higher level of automation in ATM as safety critical, sociotechnical and multi-Agent system

The main objective of this paper is to present our vision of the role of automation in future air traffic management (ATM) system. It also includes an analysis and state of the art on ATM and automation. The content is based on HALA! position paper, that looks beyond the framework defined by SESAR and NextGen for the near future, and analyses the feasibility of higher levels of automation in ATM in the far future, taking into account the relationship between humans, organizations, and machines and scoping the allocation of functions, roles, and tasks between them. Taking into consideration the proposed SESAR&NextGen paradigm shift (trajectory-based operations; proactive, more distributed and autonomous system) and studies developed in ATM automation in the past years, the vision goes toward a more ATM automation system operation questioning even the possibility of fully automated ATM system. The understanding of higher levels of automation in ATM considers the “overall system performance” as main driver for the resulting “optimal” ATM level of automation. Implementation of above programs will change the human role in the future ATM system. In this regard, the vision considers ATM as sociotechnical system and orchestrated organization, overcoming the former consequences of automation, where some “human errors” caused from automation were found, to this new vision where human motivation for their engagement in the ATM activities, will be promoted. New roles between humans, organizations, and between them and machines will be derived by considering ATM as a complex sociotechnical multi-agent system. Under this assumption, it will be essential: to maintain a high degree of autonomy among different ATM agents and, simultaneously, an optimized level of orchestration among them. Three interdependent criteria to support the always controversial decision about where to dynamically allocate the ATM essential functions/tasks are proposed; when is the “best time” to take an operational action, where is the “best place” having the best picture to take it and, finally, who will be the “best player” to implement the associated tasks. As a result, the paper advocates for a different role of automation devoted to support a temporal, institutional, and physical distributed ATM system. It is also pointed out that research in ATM automation should always take under consideration the adequate level of automation in the far future ATM system and should always ensure the safety and reliability of a highly automated ATM system. Finally considers the need to align the research efforts into two different main activities of improvement, devoted to: aircraft trajectory hierarchal, spatial, and temporal cohesion and trajectory management.

Information Security in Future Air Traffic Management Systems

The detection, identification, and evaluation of vulnerable areas mark the cornerstone of the analysis that is required to improve the security of both current and future air traffic management systems. These three functions evolved from the use of new technologies in the communication, navigation, and surveillance infrastructure and in the new generation of aircraft. This analysis includes the identification of the assets, which are understood to be things of value or things to protect from potential threats. In the future context, an infrastructure for information sharing will be deployed to enable robust data exchange among air traffic management stakeholders. Information will become a major asset to be protected. This paper aims at presenting the future air traffic management environment by analyzing the impact of intended attacks on flight and surveillance information and how the effects are propagated throughout the whole system. For illustration purposes, some potential scenarios are described in order to facilitate the identification of applicable countermeasures, which can ensure confidentiality, integrity, and accessibility of the data.

AeroMACS: A new perspective for mobile airport communications and services

Broadband wireless technologies are becoming more and more pervasive in several fields of application to supply new services and to satisfy operational constraints. Among them, this article deals with the use of WiMAX technology in future air traffic management system. This technology is expected to increase the safety and to allow the exchange of large volumes of data among heterogeneous users, including aircraft. In particular, Eurocontrol and ICAO identified a WiMAX-based technology for communications on the airport surface, named Aeronautical Mobile Airport Communication System (Aero- MACS). The scope of this article is to provide an overview of AeroMACS, with a description of its main features, requirements, PHY and MAC profile choices, and related network architecture. Finally, the article highlights some open issues for AeroMACS that represent critical aspects and require, at this time, additional investigation.