Air Traffic Management System Research Articles

Global Experience in the Use of Unmanned Aviation Technologies in Public Administration: a Review

TUnmanned Aerial Systems (UAS), despite their relative novelty, are already an integral component of the general aviation structure, and, based on a number of complex and sophisticated solutions, including those related to artificial intelligence, are part of the spectrum of high technologies. UAS find application not only in the sphere of commerce, but also in the realisation of specific tasks of public administration, such as territory management, healthcare, emergency prevention and elimination, ensuring environmental safety and law and order, nature management. The purpose of the study, the results of which are presented in this publication, is to assess the current state and potential of the use of UAS in these areas based on a review of literature sources on the practice of their application in order to solve the tasks of public administration in different countries of the world. The main conclusion drawn from the analysis and characterising the general scientific novelty of the study is that, despite a significant number of specific examples, the breadth of UAS use range can be characterised as imaginary. The main and the only really significant application is various types of aerial survey in the interests of state control and supervision bodies. In the course of the work, a number of promising directions for the use of UAS have been identified. It is also noted that their wider implementation in the practice of public administration is hindered by the lack and/or imperfection of the relevant legal framework, typical for most legislative systems of the world, and postulates the need to actively address these issues in relation to the classification and certification of UAS, requirements for their operators and software, the procedure and rules of operation, the integration of unmanned aircraft (UAS) into the existing air traffic management system.

Short-term multi-step-ahead sector-based traffic flow prediction based on the attention-enhanced graph convolutional LSTM network (AGC-LSTM)

AbstractAccurate sector-based air traffic flow predictions are essential for ensuring the safety and efficiency of the air traffic management (ATM) system. However, due to the inherent spatial and temporal dependencies of air traffic flow, it is still a challenging problem. To solve this problem, some methods are proposed considering the relationship between sectors, while the complicated spatiotemporal dynamics and interdependencies between traffic flow of route segments related to the sector are not taken into account. To address this challenge, the attention-enhanced graph convolutional long short-term memory network (AGC-LSTM) model is applied to improve the short-term sector-based traffic flow prediction, in which spatial structures of route segments related to the sector are considered for the first time. Specifically, the graph convolutional networks (GCN)-LSTM network model was employed to capture spatiotemporal dependencies of the flight data, and the attention mechanism is designed to concentrate on the informative features from key nodes at each layer of the AGC-LSTM model. The proposed model is evaluated through a case study of the typical enroute sector in the central–southern region of China. The prediction results show that MAE reduces by 14.4% compared to the best performing GCN-LSTM model among the other five models. Furthermore, the study involves comparative analyses to assess the influence of route segment range, input and output sequence lengths, and time granularities on prediction performance. This study helps air traffic managers predict flight situations more accurately and avoid implementing overly conservative or excessively aggressive flow management measures for the sectors.

Preliminary Impact Assessment of the Ad Hoc Separation Minima: A New Separation Mode

A major challenge for the Air Traffic Management system is the need to boost airspace capacity, which is near saturation in some situations. Separation minima are one of the factors related to airspace capacity, and the SESAR program promotes research into advanced separation modes. Ad Hoc separation, a novel separation mode, involves applying different pairwise separation minima in the same volume of airspace depending on a set of factors, such as encounter geometry, aircraft models, and flight level, among others. This research examines the impact of implementing this concept in different en-route scenarios. The goal is to determine whether applying this concept proves advantageous or, conversely, results in an increase in the complexity of the system without significant benefits in the key performance areas of capacity, environment, and cost-efficiency. Fast Time Simulations are conducted in RAMS software, with the concept being implemented in the LECMZMU, LECMTLU, and LECMDGU sectors of the Madrid ACC. The results reveal favorable capacity outcomes with increases of around 2% and the LECMZMU sector exhibits the most significant environmental and cost-efficiency benefits. Furthermore, implementing the Ad Hoc concept in a larger scenario could yield even greater environmental and cost-efficiency benefits.

Quasi-Stochastic Departure Metering Model Considering Non-Deterministic Taxi Time, Standard Instrument Departure Track Time, and a New Delay–Conflict Relationship

This paper presents a quasi-stochastic mixed integer programming model to determine the optimal flight departure schedule and sequence at airports. The proposed formulation addresses two key gaps in the existing departure metering strategies: (i) the variability and effects of the standard instrument departure (SID) procedure and (ii) the prospect of en route conflicts because of departure delays. The variability and effects of the SID procedure are captured through a non-deterministic parameter defined as the SID track time. The probability of en route conflicts because of departure delay is estimated based on a new delay–conflict relationship. Data used for implementation and validation of the model was collected from operations on Runway 7 of Chennai International Airport, India. Overall results indicate that the proposed departure metering model can act as a pre-emptive departure delay strategy framework that takes care of the SID procedure and en route conflict possibility with no harm to the runway throughput. The implications of this work hint toward better management of the airport operations and the performance of the overall air traffic management system.

Strengthening Aviation Cybersecurity with Security Operations Centres

Even though cybersecurity is a top priority for the aviation industry, research indicates that there are still many challenges to address. Modern aviation systems encompass cloud computing, OT, IoT, mobile devices, and traditional IT infrastructure. The network complexity has expanded the attack surface, leading to an increase in security incidents. Due to this complexity, detecting security incidents on time is challenging. Research indicates that it may take up to 196 days to detect an incident and another 56 days to address it, highlighting the urgency of improving security response. In this regard, establishing Security Operations Centres (SOCs) in the aviation sector must be addressed. SOCs can be instrumental in reducing the time it takes to detect and respond to security incidents. They provide visibility into threats, aid investigations, and enhance forensic efforts, enabling proactive threat mitigation. Research has been carried out on SOC implementations for specific domains like IoT, mobile devices, and higher education, neglecting aviation systems. Aviation systems such as Air Traffic Management (ATM) face unique security vulnerabilities, including signal modification, jamming, flooding, data and command injection, GPS spoofing, and blocking attacks, primarily due to their reliance on wireless technology. Most of these wireless technologies do not use encryption or authentication because they were designed to maximise performance. Insufficient funding also negatively affects ATM systems, resulting in the wide use of legacy ATM systems and a shortage of skilled personnel. ATM systems are considered critical infrastructure frequently targeted by well-resourced threat actors, including terrorists and nation-state actors, necessitating higher protection levels. This paper motivates the development of a customised SOC implementation framework for ATM systems to enhance aviation security by increasing visibility into threats and facilitating timely remediation.

Survey of IP-based air-to-ground data link communication technologies

The main purpose of an air traffic management system is to provide air traffic services to an aircraft moving within the controlled airspace. Very high frequency (VHF) radio in continental regions, as well as high frequency (HF) radio and satellite communications in remote areas, are used today as the primary way of delivering air traffic services. The technical limitations and constraints associated with the current technology, such as line-of-sight requirement, vulnerability to interference, and limited coverage, cause degraded voice quality and discontinuity in service. At the same time, voice-based communication may affect flight safety due to poor language skills, call sign confusion, and failure to use standard phraseology. For this reason, text-based communication over a VHF data link (VDL) has been proposed as an alternative. However, it is predicted that VDL will be insufficient to support increasing air traffic and intensive data exchanges due to its lack of mobility support and limited resources to ensure service continuity. This paper surveys next-generation data link technologies based on the current state of the "industry standard" for aeronautical communication. These include Aeronautical Mobile Airport Communication System (AeroMACS), L-band Digital Aeronautical Communications System (LDACS), and Airborne New Advanced Satellite Techniques & Technologies in a System Integrated Approach (ANASTASIA). The paper also surveys IP-based text communication solutions over these next-generation data links. We analyze the efficiency of the proposed solutions with regard to service continuity and aeronautical application requirements. We conclude the survey by identifying open problems and future trends.

An agent-based model for technology adoption in Air Traffic Management

Technology adoption depends not only on the development of new technologies, but also on the existence of regulations able to foster the implementation of such technologies. To facilitate the exploration of different policy options aimed at accelerating the adoption of new Air Traffic Management (ATM) technologies, an agent-based model that represents the behaviour of the European ATM system has been developed. This model includes representations of the main stakeholders in the ATM ecosystem: regulatory bodies, technology providers, labour unions and technology adopters, including Air Navigation Service Providers (ANSPs), airlines and airports. New ATM technologies, policies imposed, behavioural biases (e.g., loss aversion) and exogenous variables (e.g., fuel price) drive the actions of the agents, leading to the emergent global behaviour of the system. A calibration and validation process involving historical data, gaming experiments and participatory simulations was performed. The model was used to evaluate various policies that included economic incentives and penalties in two scenarios: one based on past events and another focused on the future. The results allow us to analyse which individual stakeholders benefit the most from each policy and to identify the mechanisms that emerge and drive the path of technology adoption, finding that a combination of economic incentives and penalties provides promising economical and operational results.

Optimal Attack Path Planning based on Reinforcement Learning and Cyber Threat Knowledge Graph Combining the ATT&CK for Air Traffic Management System

Optimal Attack Path Planning based on Reinforcement Learning and Cyber Threat Knowledge Graph Combining the ATT&CK for Air Traffic Management System

Airspace Congestion, flow Relations, and 4-D fundamental Diagrams for advanced urban air mobility

This paper develops theoretical macroscopic air traffic flow models that relate vehicle density and spacing to traffic flow (throughput) measures under different operational parameters for unstructured airspace in the Advanced Air Mobility (AAM) context. Recognizing the role of conflicts in air traffic flow, we relate vehicle density to the frequency of conflict occurrence in airspace using a gas-kinetic analogy. The number of conflicts is then related to vehicle speeds using an average speed loss per conflict. The effects of the speed reductions are coupled with density to explore the fundamental diagram between flow rate and density. The theoretical models are tested and validated with simulated results for a number of parameter levels. The models can be applied for quick predictions of future traffic flow conditions, which will be especially useful for operators or air traffic flow management systems. The theoretical and simulated findings also provide operational and policy insights for AAM operators, planners, and modelers. Notable insights include the critical role of aircraft density in air traffic flow and the variable impact of that density on traffic flow behavior. AAM operators and planners will need to closely manage the airspace density to avoid large numbers of conflicts simultaneously and maintain acceptable travel times and throughputs. Key operational parameters such as aircraft spacing requirements and maximum aircraft speeds were also found to have significant impacts on traffic flow behavior, and offer policy avenues for managing air traffic.

Quasi-stochastic optimization model for time-based arrival scheduling considering Standard Terminal Arrival (STAR) track time and a new delay-conflict relationship

This paper presents a quasi-stochastic mixed integer programming model to determine the optimal arrival schedule of flights in the Terminal Area (TMA). The proposed formulation addresses two key aspects of TMA operations: (i) the variability induced due to the Standard Terminal Arrival (STAR) descent procedure and (ii) the risk of merging conflicts due to scheduling delays. The variability arising from the STAR procedure is captured through a non-deterministic parameter defined as the track time. The risk of conflicts at merging points is quantified using the expected number of conflicts, estimated based on a new delay-conflict relationship. The optimization model is also extended for a multiple-runway structure. The Chennai International Airport TMA is taken as an experimental setup to validate the model. Performance assessment reveals that the observed throughput aligns with the throughput based on the optimal scheduling. Moreover, the number of conflicts is reduced by 100% after implementing the scheduling model. Research outcomes exhibit the potential to obtain practical arrival schedules with limiting controller workload. Implications of this work hint towards better stability and performance of the TMA and the overall Air Traffic Management (ATM) system.

An Efficient Trajectory Negotiation and Verification Method Based on Spatiotemporal Pattern Mining

In trajectory-based operations, trajectory negotiation and verification are conducive to using airspace resources fairly, reducing flight delay, and ensuring flight safety. However, most of the current methods are based on route negotiation, making it difficult to accommodate airspace user-initiated trajectory requests and dynamic flight environments. Therefore, this paper develops a framework for trajectory negotiation and verification and describes the trajectory prediction, negotiation, and verification processes based on a four-dimensional trajectory. Secondly, users predict flight trajectories based on aircraft performance and flight plans and submit them as requested flight trajectories to the air traffic management (ATM) system for negotiation in the airspace. Then, a spatiotemporal weighted pattern mining algorithm is proposed, which accurately identifies flight combinations that violate the minimum flight separation constraint from four-dimensional flight trajectories proposed by users, as well as flight combinations with close flight intervals and long flight delays in the airspace. Finally, the experimental results demonstrate that the algorithm efficiently verifies the user-proposed flight trajectory and promptly identifies flight conflicts during the trajectory negotiation and verification processes. The algorithm then analyzes the flight trajectories of aircrafts by applying various constraints based on the specific traffic environment; the flight combinations which satisfy constraints can be identified. Then, based on the results identified by the algorithm, the air traffic management system can negotiate with users to adjust the flight trajectory, so as to reduce flight delay and ensure flight safety.

Efficiency assessment in European air traffic management—A fundamental analysis of data, models, and methods

The European air traffic management system is characterized by its dynamic and diverse nature. To effectively address future challenges, it is crucial to enhance efficiency and resilience within the system. As an integral part of the air traffic system, air navigation services operate as natural monopolies and are subject to regulatory measures. While operational and academic studies regularly address performance benchmarking, no comparative analysis is currently evaluates the different approaches. This paper introduces a fundamental analysis for evaluating the technical efficiency of air traffic control at the air navigation service provider (ANSP) level. Our research encompasses the development of an economic model, the application of various analytical methods, and the careful selection of units for evaluation. Our findings demonstrate that the standard Data Envelopment Analysis (DEA) method is highly effective. Additionally, we emphasize that not all ANSPs shall be included in the analysis, and we caution against incorporating monetary inputs and outputs in the model.

Development of the Single European Sky

The objective of the research is to present the development of the Single European Sky initiative and to outline its importance for the European economy and the European aviation industry. The paper reviews in detail the concept of the Single European Sky, the economic factors that have led to its formation and the European regulatory framework comprised of a set of EU-wide rules on Air Traffic Management (ATM) safety, on the provision of ATM services, on airspace management and on interoperability within the network, as well as financial support to the technological modernization programme (the SESAR project). It presents the rulemaking activity of the European Commission to deal with the inefficiency of the European ATM System due to the fragmented character of international airspace, fragmented into smaller air traffic control centres divided by the national boundaries, effectively limiting integration, interoperability, and economies of scale, and leading to induced delays, excessive air-traffic control costs and uneconomical flight trajectories. The applied research methodology includes content analysis, analysis of statistical data, historical data, conclusions, and generalizations. The hypothesis is that the strategic goals of the Single European Sky initiative and its implementation are beneficial for the competitiveness of the European aviation industry, and the common rules and the introduction of a harmonized legislative framework will contribute to improving the efficiencies of ATM while accounting for the interests and singularities of all stakeholders in the European aviation value chain.

Strategic Deconfliction of Unmanned Aircraft Based on Hexagonal Tessellation and Integer Programming

Unmanned aircraft systems service suppliers adhere to interoperability standards that require unmanned aircraft operators to submit an operational intent, which describes the planned flight path in four-dimensional space. To ensure fairness, the central database follows a first-come, first-served approach, accepting new operational intents as long as they do not conflict with any active ones. However, creating a viable operational intent is challenging due to moving obstacles. This paper introduces an innovative optimization-based procedure to automate the intent filing process. It utilizes a stacked hexagonal tessellation to model the airspace, offering adjustable granularity. Path finding is accomplished using integer programming on the hex grid. The integer program is solved on a grid canvas that includes only necessary cells, striking a balance between computational efficiency and optimality. Simulation experiments demonstrate the procedure’s effectiveness in generating feasible trajectories, even in scenarios with dense, omnidirectional air traffic. This procedure has the potential to become the foundational software core for low-altitude air traffic management systems, providing strategic deconfliction and constraint management services.

Integrating Electric Vertical Takeoff and Landing Aircraft into Public Airspace: A Scenario Study

The successful deployment of Advanced Air Mobility (AAM) requires the safe integration of electric vertical takeoff and landing (eVTOL) aircraft in non-segregated airspace. However, a lack of practical deployment demonstrations can slow the regulatory progress. This study presents a practical deployment framework for the integration of eVTOL aircraft into public airspace, in accordance with the Federal Aviation Administration (FAA) special airworthiness criteria. This study focused on a corporate use case to provide a comprehensive scenario for enhancing intra-company mobility. The scenario supports early implementation and demonstration goals by removing reliance on air traffic management systems or air traffic controller separation services. The practical deployment framework included facility selection, route planning, terrain mapping, collision avoidance, aircraft selection, infrastructure requirements, vertiport placement, electric chargers, ground handling, operational staff, and cost estimates. Planners can use the framework as a template to inform the implementation of real-world AAM services using eVTOL aircraft.

Two-Stage Multicriteria Decision-Making Framework for Aircraft Conflict Resolution

In this study, a two-stage multicriteria decision-making framework for aircraft conflict resolution in the air traffic management system is proposed. Aircraft conflict resolution has been commonly solved based on single-objective optimization. However, the existing approach may not provide a satisfactory solution to all stakeholders involved in the air traffic management system. Therefore, in the first stage of the proposed algorithm, a new conflict resolution strategy is presented based on multiobjective optimization in which multiple-objective functions are optimized simultaneously. Each objective function is designed to take into account the interests of various stakeholders, and the augmented epsilon-constraint method is applied to determine Pareto optimal solutions. In the second stage, the best compromise solution among the Pareto optimal solutions is determined based on the technique for order performance by similarity to the ideal solution. The numerical simulation results show that the proposed algorithm provides a better solution from the perspective of mitigating the competing interests among stakeholders than the existing approach based on single-objective optimization.

Ionospheric Effect on Global Navigation Satellite System Performance - A Review

Satellite-based Communication, Navigation, Surveillance and Air Traffic Management (CNS/ATM) systems have been adopted by the international aviation community to meet the challenges of continuously rising global air traffic. Global Navigation Satellite System (GNSS) has been prescribed for the provision of navigation services to the air traffic. Performance of GNSS depends upon many factors including refraction and scintillation effects of ionosphere on the satellite signals. Severity of this effect depends largely upon the geographical location of the navigation receiver, the time of the day, the month of the year and the year on the 11-year solar cycle. This paper studies ionosphere mechanism and discusses its effect on the performance of GNSS. The paper also predicts the performance during solar cycle maximum expected in 2013-2014 [Jensen, Anna B.O., Mitchell, Cathryn 2011]. It touches upon the preparations going on to face the adverse effects of increased solar activity during the cycle maximum and recommends coordination/cooperation between various relevant organizations/institutions in the processes of data collection and development of a model.

TCFLTformer: TextCNN-Flat-Lattice Transformer for Entity Recognition of Air Traffic Management Cyber Threat Knowledge Graphs

With the development of the air traffic management system (ATM), the cyber threat for ATM is becoming more and more serious. The recognition of ATM cyber threat entities is an important task, which can help ATM security experts quickly and accurately recognize threat entities, providing data support for the later construction of knowledge graphs, and ensuring the security and stability of ATM. The entity recognition methods are mainly based on traditional machine learning in a period of time; however, the methods have problems such as low recall and low accuracy. Moreover, in recent years, the rise of deep learning technology has provided new ideas and methods for ATM cyber threat entity recognition. Alternatively, in the convolutional neural network (CNN), the convolution operation can efficiently extract the local features, while it is difficult to capture the global representation information. In Transformer, the attention mechanism can capture feature dependencies over long distances, while it usually ignores the details of local features. To solve these problems, a TextCNN-Flat-Lattice Transformer (TCFLTformer) with CNN-Transformer hybrid architecture is proposed for ATM cyber threat entity recognition, in which a relative positional embedding (RPE) is designed to encode position text content information, and a multibranch prediction head (MBPH) is utilized to enhance deep feature learning. TCFLTformer first uses CNN to carry out convolution and pooling operations on the text to extract local features and then uses a Flat-Lattice Transformer to learn temporal and relative positional characteristics of the text to obtain the final annotation results. Experimental results show that this method has achieved better results in the task of ATM cyber threat entity recognition, and it has high practical value and theoretical contribution. Besides, the proposed method expands the research field of ATM cyber threat entity recognition, and the research results can also provide references for other text classification and sequence annotation tasks.

Runway Capacity Studies for Major Indian Airports

The two principal measures of performance of Air Traffic management (ATM) systems are Capacity and Delay. Significant growth in Indian air traffic is causing congestions and hence delays in the en-route airspace and at airports. The main reason for the delay at airports is insufficient capacity in terms of facilities such as runways, taxiways or gates to accommodate peak period demands. The delays at airports would cause inconvenience to the passengers, airliners and the airport authorities. The airport runway capacity information will be useful to manage demand and minimize the delay. Prediction of runway capacity aids in developing strategies for efficient air traffic management. This paper presents the airport runway capacity studies carried out using Time Space diagrams for major Indian Airports.

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.