Current Air Traffic Management Research Articles

Commercial spaceflight: Regulatory framework assessment and safety perspectives

Recent years are witnessing the rapid technological development in airspace domain, actually paving the way to the development of a commercial space market. Until the recent past, space operations have been essentially performed by research centers or military agencies, in usually segregated areas to ensure third parties’ safety, governed by launch base regulations and organized in an unscheduled manner. However, with the entry of private companies into the space domain, a new market niche is being created: that of commercial space transportation. For example, a promising area is the one related to operations performed by commercial suborbital flights, whether aimed at space tourism or simply transporting things and/or passengers from one point to another on the Earth's surface. The traffic volumes are supposed to increase in next years and segregating airspace does not represent a sustainable solution for the future.The present paper will first assess the state of the art of the regulatory framework currently applicable to operators in order to obtain authorization to perform space missions for commercial use, then propose a comparison between the United State of America and European regulatory frameworks. Main challenges related to regulatory aspects will be identified and perspectives on possible higher airspace operations integration in the medium-long term will be derived. Finally, safety considerations deriving from a seamless accommodation of higher airspace operations in current Air Traffic Management will be derived for the medium-long term. In conclusion, this work reveals that neither the United States nor Europe has formally approved a legal framework establishing certification procedures for sub-orbital space transport systems. Currently, the US legislation is the most applicable as it has comprehensive rules to allow operators to obtain flight authorization ensuring compliance with requirements through a compliance matrix periodically updated.

Holistic Approach for Aircraft Trajectory Optimization Using Optimal Control

This paper deals with an optimal control approach for commercial aircraft trajectory planning, focusing on the vertical path and the minimization of the fuel burned. The main contribution is the optimization of the whole trajectory, also called the mission, without prior separation into different flight phases (climb, cruise, and descent), contrary to traditional approaches that consider the flight phases sequentially. The proposed optimal control problem (OCP) is formulated and then solved using a direct collocation method. Initial results yield optimal trajectories with a gradual climb during the cruise (climb cruise), which correspond to theoretical trajectories that minimize fuel consumption. Furthermore, a penalization is introduced to ensure vertical profiles featuring horizontal cruise levels on so-called flight levels, compliant with current air traffic management regulations. The use of direct methods to address this OCP induces large nonlinear optimization problems that are solved using an interior point method. This methodology is likely to lead to poor local optima, but a simple multistart heuristic shows that the solutions found for standard problems appear to be globally optimal. Such an approach does not need to impose a priori the cruise flight levels and is suitable for commercial aircraft flight planning purposes. It leads to fuel saving and subsequently to important improvements against environmental impact by reducing emissions.

ATC Human Factors Involved in RPAS Contingency Management in Non-Segregated Airspace

Objectives: The overall approach towards Remotely Piloted Aerial System integration into a non-segregated airspace is that the unmanned vehicles should be able to fit into the current air traffic management system, thus meeting all the technical and regulatory requirements to be treated similar to any other airspace user. Such a requirement implies that unmanned aircraft operations should behave as close as possible to manned aviation or at least generate the most negligible possible negative impact on the system. From the air traffic management point of view, this implies that air traffic controllers should be capable of effectively handling different types of RPAS operating in a nominal state but also when suffering a potential contingency. This paper aims to analyse how air traffic controllers involved in managing unmanned aircraft integration into non-segregated airspace are impacted when an unmanned vehicle suffers a contingency. Participants: Six air traffic controllers were the test subjects, complemented by one RPAS pilot and several pseudo-pilots controlling the simulated manned traffic. The project collected real-time simulation data to develop specific indicators to determine how the controllers’ workload increases while managing complex traffic scenarios, including a single RPAS. Study Method: We conducted exhaustive traffic flight simulations, recreating complex airspace scenarios, including various RPAS types and mission-oriented trajectories. The involved RPAS were subjected to two of the most relevant contingencies: loss of the command-and-control link and engine failure. The experiments were evaluated in different operational scenarios, including using autonomous communication technologies to help air traffic controllers track the RPAS operation. Findings: The results indicate that the air traffic controller’s perception and workload are not affected beyond reason by the introduction of an unmanned aircraft as a new element into the non-segregated airspace, even when that aircraft suffers a contingency. The flight-intent technology increases situational awareness, leading to more efficient and safe airspace management. Additional simulations may need to be performed to evaluate the impact on airspace capacity, safety, and workload when various unmanned vehicles are simultaneously inserted.

Evaluation of a Decision-Based Invocation Strategy for Adaptive Support for Air Traffic Control

Air traffic controller workload is a limiting factor in the current air traffic management system. Adaptive support systems have the potential to balance controller workload and gain acceptance as they provide support during times of need. Challenges in the design of adaptive support systems are to decide when and how to trigger support. The goal of this study is to gain empirical insights into these challenges through a human-in-the-loop experiment, featuring a simplified air traffic control environment in which a novel triggering mechanism uses the quality of the controller's decisions to determine when support is needed. The designed system seeks to prevent high workload conditions by providing resolution advisories when the controller exceeds a threshold of “self-complicating” decisions. Results indicate that the new system is indeed capable of increasing the efficiency and safety compared to full manual control without intervention. More adaptive support, however, increased the frustration of participants, decreased acceptance, and did not result in improved workload ratings. These findings suggest that, unless we can better infer human intent in complex work environments, adaptive support at the level of decision-making is problematic. A potentially more fruitful direction is to provide support at the level of information integration, with full decision-making authority with the human.

Comparison of various temporal air traffic flow management models in critical scenarios

Overloads (i.e., critical imbalances between traffic demand and capacity) are currently resolved in the European air transportation network by activating air traffic flow management regulations. Flights subject to regulations are delayed on the ground by the computer assisted slot allocation system, which uses a first-planned, first-served principle to allocate the delays. In the last decades, many researchers have proposed alternative models based on more or less complex optimisation techniques, which could effectively resolve overloads with less delay. Despite the fact that these models were very promising, changing the current operational system and procedures - which trust is supported by a successful working history dating back to 1995–may not be realistic in the short term. This paper examines the gradual transition from current air traffic flow management to a futuristic model in which flights are assigned delays with massive cherry-picking measures that minimise the total delay in the network, without necessarily adhering to the first-planned, first-served rule. A reference model with greedy regulations representative of current operations is compared to a model where the Network Manager optimises regulations using hyper-heuristics, a model based on massive cherry-picking measures, and hybrid models that consider regulations to resolve major overloads and cherry-picking measures only for residual overloads. These models are compared in critical scenarios with major capacity issues caused by adverse weather conditions. Results suggest that hybrid models could be a viable option for reducing delays with minor changes in the current air traffic flow management paradigm.

A Deep Unsupervised Learning Approach for Airspace Complexity Evaluation

Airspace complexity is a critical metric in current Air Traffic Management systems for indicating the security degree of airspace operations. Airspace complexity can be affected by many coupling factors in a complicated and nonlinear way, making it extremely difficult to be evaluated. In recent years, machine learning has been proved as a promising approach and achieved significant results in evaluating airspace complexity. However, existing machine learning based approaches require a large number of airspace operational data labeled by experts. Due to the high cost in labeling the operational data and the dynamical nature of the airspace operating environment, such data are often limited and may not be suitable for the changing airspace situation. In light of these, we propose a novel unsupervised learning approach for airspace complexity evaluation based on a deep neural network trained by unlabeled samples. We introduce a new loss function to better address the characteristics pertaining to airspace complexity data, including dimension coupling, category imbalance, and overlapped boundaries. Due to these characteristics, the generalization ability of existing unsupervised models is adversely impacted. The proposed approach is validated through extensive experiments based on the real-world data of six sectors in Southwestern China airspace. Experimental results show that our deep unsupervised model outperforms the state-of-the-art methods in terms of airspace complexity evaluation accuracy.

Complexity optimal air traffic assignment in multi-layer transport network for Urban Air Mobility operations

Large numbers of Urban Air Mobility (UAM) vehicles are expected to operate in urban airspace in the near future, exceeding the capacities of current airspace and Air Traffic Management (ATM) systems. This paper presents an air traffic assignment framework for 3D air transport networks in urban airspace to enable UAM operations at future demand levels. The individual vehicle dynamics are aggregated to describe the overall flow feature in this macroscopic model. Firstly, UAM operations are modeled as flows and structured in a three-dimensional two-way air transport network. Then, a complexity optimal air traffic assignment in urban airspace is formulated as an optimization problem. Based upon the Linear Dynamical System (LDS), a novel complexity metric is defined as objective function, which takes into account dynamic flow structure, congestion, and operational efficiency. A two-phase approach combining Simulated Annealing (SA) and Dafermos’ Algorithm (DA) is introduced to efficiently solve this problem. To validate the proposed model, a case study of an air transport network in Singapore’s urban airspace with two different demands is conducted. Comparative studies are carried out between the proposed algorithm and other widely used traffic assignment algorithms. The results show that the proposed approach is capable of assigning flows in an efficient and effective manner, reducing the complexity of the air transport network significantly. The results also show that optimizing the flow pattern reduces total complexity by 90.44%±0.53% and 92.12%±0.35% with 95% confidence interval, respectively in two scenarios. The framework may be useful for Air Navigation Service Providers (ANSP) in strategic planning for UAM operations and urban airspace design.

A Safety-Aware Real-Time Air Traffic Flow Management Model Under Demand and Capacity Uncertainties

Inherent uncertainties of the air transportation system (ATS) can induce unexpected anomalies in its operations such as deviations in flight schedules, sudden imbalances of demands and capacities, etc.. Current air traffic flow management (ATFM) models rarely consider both demand and capacity uncertainties in their algorithms, and generally focus on minimizing the flight delays under deterministic constraints. Thus, to bridge this gap, we propose a framework for en-route ATFM while scrutinizing uncertainties in en-route capacity and demand and their imbalance, via a chance constraint based probabilistic approach. The proposed framework plays a key role in ensuring the safety of the overall ATS in terms of maintaining the safety separation between flights and constraining the capacity of the sectors as well. Moreover, flight level assignments scheme is proposed based on the Base of Aircraft Data (BADA) of the European Organization for the Safety of Air Navigation (EUROCONTROL) with the objective of minimizing the fuel consumption. The model further minimizes the overall expected delay of the system using the control actions of ground holding, speed control, rerouting, and flight cancellations. At the implementation stage, two phases of ATFM as pre-tactical and tactical are considered, in which the former focuses on generating optimal trajectories and the latter focuses on real-time updates of flight plans. The computational complexity is reduced by shrinking the feasibility region and decomposing the problem into maximum weighted independent sets. The experimental results of realistic large-scale problems demonstrate the effectiveness and computational feasibility of our ATFM framework.

Traffic conflict reduction based on distributed stochastic task allocation

AbstractThe aim of this paper is to provide preliminary results on a traffic coordination framework based on stochastic task allocation. General trends and the predicted advent of personal aerial vehicles increase traffic rapidly, but current air traffic management methods admittedly cannot scale appropriately. A hierarchical system is proposed to overcome the problem, the middle layer of which is elaborated in this paper. This layer aims to enable stochastic control of traffic behaviour using a single parameter, which is achieved by applying distributed stochastic task allocation. The task allocation algorithm is used to allocate speeds to vehicles in a scalable way. By regulating the speed distribution of vehicles the conflict rates remain manageable. Multi-agent simulation results show that it is possible to control ensemble dynamics and together with that traffic safety and throughput via a single parameter. Using transient simulations the dynamic performance of the system is analysed. It is shown that the traffic conflict reduction problem can be transformed into a control design problem. The performance of a simple controller is also evaluated. It was shown that by applying the controller, quicker transients can be achieved for the mean speed of the system.

Operational Requirements Analysis for Electric Vertical Takeoff and Landing Vehicle in the Brazilian Regulatory Framework

Air passenger transport is expected to change, in the next years, the urban air mobility (UAM) environment. New technologies are enabling the introduction of a new concept of aircraft, referred to as electric vertical takeoff and landing vehicle (eVTOL), with vertical take-off and landing capability, distributed electric propulsion system and low noise level compared to helicopters. This article presents an analysis of the Brazilian Civil Aviation Regulations (RBAC) No. 91 and 135, which address the minimum requirements for commercial operations of commuter and on-demand public passenger transport with airplanes with up to 19 seats. The objective of this article is to identify the technical and regulatory barriers to initiating the eVTOL operation in Brazil and to validate the current operational air traffic rules. After the analysis of the operational requirements and the current Air Traffic Management (ATM) infrastructure for helicopter operation, the minimum required and recommended navigation, communication and surveillance equipment are identified, as well as the main operational limitations for the operation of this type of aircraft in transporting passengers. This analysis is just the beginning of a broader study and there are many challenges to support an increased eVTOL operations.

Uncertainty quantification and reduction in aircraft trajectory prediction using Bayesian-Entropy information fusion

Eliminating accidents while maintaining the integrity of the National Airspace System is one of the central objectives of the Next Generation Air Transportation System. This paper presents a Bayesian framework for accurate trajectory and accident prediction in National Airspace System using a high-fidelity trajectory simulation platform. Various uncertainties in aircraft trajectory prediction due to pilot behavior and weather effects are included as random variables in the simulations. Bayesian-Entropy method fuses available observation data (e.g., positioning system) with existing physical constraints (e.g. runway location) to update these simulation parameters. The posterior distributions of parameters are used to predict the probability of an adverse incident and time-remaining to incident. The proposed Bayesian updating scheme offers a flexible and rigorous way for adverse incident diagnostics and prognostics in current and future Air Traffic Management. Two realistic examples are given to show that it is possible to derive advance warning using the proposed methodology. The approach integrates data from a simulation model, with real-time traffic data streams and available physical constraints, using the Bayesian-Entropy information fusion methodology. This advance warning will allow the pilots/controllers to take actions to mitigate adverse incident in the National Airspace System.

Integration of Network Scheduling Using Accrued Delay Across Vehicle Connectivity

Current air traffic management processes lack integration among elements of the airspace system such as airport and airspace resources, often due to disconnected and inconsistent use of information, models, and metrics. This integration is hindered further by the separation between the traffic management problem, which has focused on a gate-to-gate flight model, and the management of connecting vehicles, crews, and passengers between flights. To help induce such integration, an accrued delay metric is used to continuously measure the delay that a flight has accumulated during the flight and inherited from previous flights through the turnaround at airports. The authors presented previously an application of this metric to mitigate the delay propagation between management initiatives during a flight. In this paper, the authors extend this metric to mitigate delay propagation through vehicle turnaround. It is first shown through a historical data analysis that this delay propagation is a significant source of delay for airline operators and that schedule padding hides some of it. Then, accrued delay along a vehicle trip is shown to mitigate some of this propagation across the network. Through an abstract, closed, three-node network example, using accrued delay is shown to help implicitly coordinate the distributed scheduling among the nodes. These nodes may represent a set of airports or a set of vertiports in an urban air mobility environment. It is shown that prioritizing flights that have accrued high delay at previous nodes significantly reduces the variance of flight delay.

A two-level hierarchical framework for air traffic flow management

The new initiatives of air traffic management (ATM) imposed by EUROCONTROL and EU Commission aim to eliminate the drawbacks of the current ATM system in Europe. Triggered by the imperative need for...

Practical implementation of 4D-trajectories in air traffic management: system requirements and time windows monitoring

PurposeThe current air traffic management (ATM) operational approach is changing; “time” is now integrated as an additional fourth dimension on trajectories. This notion will impose on aircraft the compliance of accurate arrival times over designated checkpoints (CPs), called time windows (TWs). This paper aims to clarify the basic requirements and foundations for the practical implementation of this functional framework.Design/methodology/approachThis paper reviews the operational deployment of 4D trajectories, by defining its relationship with other concepts and systems of the future ATM and communications, navigation and surveillance (CNS) context. This allows to establish the main tools that should be considered to ease the application of the 4D-trajectories approach. This paper appraises how 4D trajectories must be managed and planned (negotiation, synchronization, modification and verification processes). Then, based on the evolution of a simulated 4D trajectory, the necessary corrective measures by evaluating the degradation tolerances and conditions are described and introduced.FindingsThe proposed TWs model can control the time tolerance within less than 100 s along the passing CPs of a generic trajectory, which is in line with the expected future ATM time-performance requirements.Originality/valueThe main contribution of this work is the provision of a holistic vision of the systems and concepts that will be necessary to implement the new 4D-trajectory concept efficiently, thus enhancing performance. It also proposes tolerance windows for trajectory degradation, to understand both when an update is necessary and what are the conditions required for pilots and air traffic controllers to provide this update.

An Interactive Conflict Solver for Learning Air Traffic Conflict Resolutions

The increasing demand in air transportation is pushing the current air traffic management system to its limits in the airspace capacity and workload of air traffic controllers (ATCOs). ATCOs are in an urgent need of assistant tools to aid them in dealing with increased traffic, specifically in resolving potential conflict. Because current automated conflict resolutions are not in conformance with the thinking or preferences of individual ATCOs, consequently, they are unlikely accepted by the ATCOs. In this work, an artificial intelligence (AI) system is built as a digital assistant to support ATCOs in resolving potential conflicts. Our system consists of two core components: an intelligent interactive conflict solver (iCS) to acquire ATCOs’ demonstrations, and an AI agent. The AI agent is based on reinforcement learning to suggest conflict resolutions. It is observed that providing the AI agent with the human resolutions, which are acquired and characterized by our intelligent interactive conflicts solver, not only improves the agent’s performance but also gives it the capability to suggest more humanlike resolutions. That could help to increase the ATCOs’ acceptance rate of the agent’s suggested resolutions. Our system could be further developed as personalized digital assistants of ATCOs to maintain their workloads manageable when they have to deal with sectors with increased traffic.

Traffic management for drones flying in the city

Air Traffic Management (ATM) is designed based on the notion of a pilot navigating an aircraft from within the aircraft. Increasing demand for Unmanned Aircraft Systems (UAS) usage and its safe integration into segregated/non-segregated airspace, on the other hand, have raised a question on the adoption of the current ATM for the UAS Traffic Management (UTM). The Procedures for Air Navigation Services-Air Traffic Management (PAN-ATM) and Procedures for Air Navigation Services - aircraft operations (PAN-OPS) rules are both developed for manned flight operations. Therefore, this work (i) defines the UTM system and describes its envisioned functionalities; (ii) performs an exploratory research to identify the distinctions between a manned and an unmanned flight operation and consequently the possible challenges to implement UTM with regard to the ATM; (iii) discusses potential Communication, Navigation and Surveillance (CNS) technologies to support the UTM system; and (iv) proposes an architectural framework for UTM based on the findings. It is important to highlight that this work is developed based on the assumption that the UAS will operate in the class G airspace (500 ft and below) in urban areas where the UAS are exposed to various obstacles such as static objects: high-rise buildings, trees, lamp posts, over-ground rail tracks and dynamic objects: cranes.

A path forward to better space security: Finding new solutions to space debris, space situational awareness and space traffic management

This article addresses the growing problems of space debris elevating the increased risk of orbital collisions as well as the difficulty of accurate space situational awareness, especially with regard to smaller space debris. These problems of space situational awareness (SSA) and space traffic management (STM) will become more acute as perhaps as many as twenty thousand new satellites are deployed in low Earth orbit (LEO) as part of new large scale constellations. This problem will grow as these LEO satellites need to be replaced within a cycle of perhaps every five to seven years . Many believe that there is now a need for space traffic management (STM) capabilities to cope with all these issues. There are no specific agreements, however, on how space traffic management might be systematically accomplished at the international level. The good news is that the Working Group on the Long Term Sustainability of Outer Space Activities (LTSOSA) and COPUOS agreed to 21 new guidelines relating to the longer term sustainability of space and which help to establish a foundation for future efforts to create a process that could aid future space traffic control processes. Several key guidelines which were discussed extensively within the Working Group which could have aided the future prospects for traffic management, however, were not agreed before the Working Group adjourned in June 2018.This article also highlights the problem of space traffic management in near-space or ‘protospace’. These concerns grow as there is more activity in the stratosphere due to deployment of high altitude platform systems, more launches through the stratospher to deploy satellite constellation, more de-orbit operations, and perhaps increased operation of spaceplanes and hypersonic transportation in these upper altitude areas not covered by current commercial air traffic management and control. This article not only addresses these types of issues in terms of safety concerns and increased risks, but also suggests new and innovative ways that these concerns might be addressed through regulatory reforms and codification of best practices. These proposals thus outline new ways forward and suggest reforms that could supplement the efforts of the UN Committee on the Peaceful Uses of Outer Space (COPUOS) in its efforts to address these safety and security concerns.

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.

Аналіз використання архітектури підприємства для модернізації систем організації повітряного руху

Мета: у зв’язку зі зростаючою потребою в повітряному транспорті та браком поточної пропускної здатності систем організації повітряного руху (ОрПР) для майбутніх потреб авіатранспорту, є потреба у трансформації поточних систем ОрПР. Будь-яка зміна у складній систем такій як система організації повітряного руху може мати вплив на різних учасників організації повітряного руху, продуктивність системи та її безпеку. Саме тому, є необхідність в засобі для оцінки та передбачення впливу зміни та планування її впровадження в найбільш ефективний спосіб. Методи: архітектура підприємства надає засоби для формування цілісного уявлення про складну систему таку як система організації повітряного руху дозволяючи оцінити вплив змін так допомогти їх впровадити. Результати: можна побачити що архітектура підприємства використовується різними агенціями, організаціями та підприємствами по всьому світі для кращого управління та планування їх діяльності. Така ж методологія може бути застосована в системі організації повітряного руху для її трансформації, щоб задовільнити зростаючу потребу в повітряному транспорті. З виконаного дослідження, можна побачити, що архітектура підприємства використовується в дослідницьких програмах Сполучених Штатів Америки та Європи задля планування трансформації їх систем організації повітряного руху та забезпечення плавного та швидкого впровадження результатів дослідницьких програм. Обговорення: в той час як архітектура підприємства дозволяє отримати цілісне уявлення про стан підприємства, впровадження її може бути викликом. Широке коло експертів є необхідним для опису підприємства з різних перспектив (бізнес-перспективи, операційної та технологічної перспектив, тощо), що робить процес доволі трудомістким. Але існує велика кількість структур для архітектури підприємства та методів розробки архітектури, що сприяють більш плавному та швидкому впровадженню архітектури підприємства.

Air traffic management based on 4D-trajectories: requirements and practical implementation

The current Air Traffic Management (ATM) functional approach is changing: ‘time’ is now integrated as an additional fourth dimension on trajectories. This notion will impose on aircraft the compliance of accurately arrival times over designated checkpoints, called Time Windows (TWs). In this context, we review the operational concept of 4D-trajectories, by initially developing an analysis of basic requirements for their implementation in the Communications, Navigation and Surveillance (CNS) systems and then by investigating their management in the future ATM context. We focus on defining the relationships between 4D-trajectories and other concepts and systems of the future ATM framework, and the needs that it will require for its application, detailing the main tools, programs and ATM/CNS systems that must be deployed. We appraise how 4D-trajectories must be managed and planned (negotiation, synchronization, modification and verification processes). Then, based on the degradation of a 4D-trajectory, we define and introduce the necessary corrective measures by evaluating the degradation tolerances and conditions.