Airspace Configuration Research Articles

Dynamic airspace configuration by genetic algorithm

Abstract With the continuous air traffic growth and limits of resources, there is a need for reducing the congestion of the airspace systems. Nowadays, several projects are launched, aimed at modernizing the global air transportation system and air traffic management. In recent years, special interest has been paid to the solution of the dynamic airspace configuration problem. Airspace sector configurations need to be dynamically adjusted to provide maximum efficiency and flexibility in response to changing weather and traffic conditions. The main objective of this work is to automatically adapt the airspace configurations according to the evolution of traffic. In order to reach this objective, the airspace is considered to be divided into predefined 3D airspace blocks which have to be grouped or ungrouped depending on the traffic situation. The airspace structure is represented as a graph and each airspace configuration is created using a graph partitioning technique. We optimize airspace configurations using a genetic algorithm. The developed algorithm generates a sequence of sector configurations for one day of operation with the minimized controller workload. The overall methodology is implemented and successfully tested with air traffic data taken for one day and for several different airspace control areas of Europe.

Sectorization and Configuration Transition in Airspace Design

Current airspace is sectorized according to some predefined rules that are not flexible. To facilitate utilizing the airspace more efficiently, methods to design sectors need to be promoted. In this paper, we propose an undirected graph cut-based approach that employs a memetic local search-embedded constrained evolution algorithm, NSGA-II, to generate nondominated airspace configurations. We also propose a new concave hull-based method to automatically depict sector boundaries. In addition, we also study the configuration transition problem. We define the similarity of the two different configurations and calculate their similarity with a bisection diagram and a minimum cost flow algorithm. We build a forward network to represent configuration transitions across several consecutive time periods and use multiobjective dynamic programming to determine a series of nondominated configuration links from the first period to the end. We test our approaches by simulation in high-altitude airspace controlled by Beijing Area Control Center. The results show that our sectorization method outperforms the current configuration in practice, providing a lower sector number, lower intersector flow, more balanced workload distribution among the different sectors, and no constraint violations, so that the proposed approach shows its significant potential as practical applications for dynamic airspace configuration.

Dynamic airspace configuration method based on a weighted graph model

This paper proposes a new method for dynamic airspace configuration based on a weighted graph model. The method begins with the construction of an undirected graph for the given airspace, where the vertices represent those key points such as airports, waypoints, and the edges represent those air routes. Those vertices are used as the sites of Voronoi diagram, which divides the airspace into units called as cells. Then, aircraft counts of both each cell and of each air-route are computed. Thus, by assigning both the vertices and the edges with those aircraft counts, a weighted graph model comes into being. Accordingly the airspace configuration problem is described as a weighted graph partitioning problem. Then, the problem is solved by a graph partitioning algorithm, which is a mixture of general weighted graph cuts algorithm, an optimal dynamic load balancing algorithm and a heuristic algorithm. After the cuts algorithm partitions the model into sub-graphs, the load balancing algorithm together with the heuristic algorithm transfers aircraft counts to balance workload among sub-graphs. Lastly, airspace configuration is completed by determining the sector boundaries. The simulation result shows that the designed sectors satisfy not only workload balancing condition, but also the constraints such as convexity, connectivity, as well as minimum distance constraint.

Design and Evaluation of a Dynamic Sectorization Algorithm for Terminal Airspace

Given its static and rigid structure, the current National Airspace System lacks the ability to cope efficiently with the increasingly severe demand–capacity imbalances expected to develop over the coming years. To better accommodate the flexibility desired for future flight operations and to alleviate the demand–capacity imbalances, research initiatives have been conducted under the dynamic airspace configuration concept. Although most past dynamic airspace configuration researchers have focused on en route airspace, this paper investigates terminal airspace operations. A dynamic sectorization algorithm for terminal airspace is developed, which combines a -means clustering-based vertical sectorization algorithm, an integer-programming-based horizontal sectorization algorithm, and an -shapes-based airspace sectorization algorithm. This dynamic sectorization algorithm is validated with real traffic data from several major international airports in the United States and simulated traffic data with projected future air routes and traffic patterns. Performance evaluation demonstrates that the algorithm can improve the efficiency of terminal airspace utilization and reduce traffic complexity.

Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations

Air traffic controller supervisors configure available sector, operating position, and workstation resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two example problem instances. The algorithm produces configuration-schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest-path problem. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Furthermore, some operationally-meaningful metrics are computed with the results of simulations of the algorithm for various values of this parameter. Two example problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. The results demonstrate how the algorithm suggests advisories that appropriately use changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes.

Behind the Scenes of NextGen: Describing the Impact of NextGen Operational Improvements on the Traffic Manager

In an effort to modernize the National Airspace System (NAS), the Federal Aviation Administration (FAA) has introduced the Next Generation Air Transportation System (NextGen). The introduction of new capabilities and operational improvements (OI) offers the potential for changes to the roles and responsibilities of the traffic management unit (TMU). Each change presents the opportunity to positively or adversely impact the overall safety of the NAS. This paper applies a proactive approach to identifying potential human performance hazards associated with NextGen TMU operations. The TMU performance hazards identified were primarily related to the potential for selecting inadequate airspace and airport configurations. The potential effects of these hazards will directly affect the NextGen controller and thus represent rich opportunities for researchers to mitigate potential issues in the early stages of system design.

Dynamic Airspace Configuration Using Approximate Dynamic Programming

On the basis of weather and high traffic, the Next Generation Air Transportation System envisions an airspace that is adaptable, flexible, controller friendly, and dynamic. Sector geometries, developed with average traffic patterns, have remained structurally static with occasional changes in geometry due to limited forming of sectors. Dynamic airspace configuration aims at migrating from a rigid to a more flexible airspace structure. Efficient management of airspace capacity is important to ensure safe and systematic operation of the U.S. National Airspace System and maximum benefit to stakeholders. The primary initiative is to strike a balance between airspace capacity and air traffic demand. Imbalances in capacity and demand are resolved by initiatives such as the ground delay program and rerouting, often resulting in systemwide delays. This paper, a proof of concept for the dynamic programming approach to dynamic airspace configuration by static forming of sectors, addresses static forming of sectors by partitioning airspace according to controller workload. The paper applies the dynamic programming technique to generate sectors in the Fort Worth, Texas, Air Route Traffic Control Center; compares it with current sectors; and lays a foundation for future work. Initial results of the dynamic programming methodology are promising in terms of sector shapes and the number of sectors that are comparable to current operations.

Graph-Based Algorithm for Dynamic Airspace Configuration

In this paper, a new algorithm for dynamic airspace configuration is developed based on graph theory. A graph model is first constructed that accurately represents the air-route structure and air traffic in the National Airspace System. The airspace configuration problem is then formulated as a graph-partitioning problem to balance the subgraph (sector) workload while satisfying the capacity constraint, which is efficiently solved by a spectral clustering method. Since the original spectral clustering method shows some undesirable properties, such as disconnected subgraphs and unbalanced partitions, an algorithm is proposed to refine the partitions. Lastly, using the partitioned graph as an input, a novel airspace sectorization algorithm is developed, based on the graph search method. The new sectors computed by the sectorization algorithm have smooth boundaries and good geometrical shapes, which satisfy the minimum distance requirement (i.e., the sector boundaries are at least a minimum distance away from the airports, waypoints, and main air routes). The performance of the proposed dynamic airspace configuration algorithm is validated through various air-traffic scenarios with real air-traffic data.

Forecasting workload and airspace configuration with neural networks and tree search methods

The aim of the research presented in this paper is to forecast air traffic controller workload and required airspace configuration changes with enough lead time and with a good degree of realism. For this purpose, tree search methods were combined with a neural network. The neural network takes relevant air traffic complexity metrics as input and provides a workload indication (high, normal, or low) for any given air traffic control (ATC) sector. It was trained on historical data, i.e. archived sector operations, considering that ATC sectors made up of several airspace modules are usually split into several smaller sectors when the workload is excessive, or merged with other sectors when the workload is low. The input metrics are computed from the sector geometry and from simulated or real aircraft trajectories. The tree search methods explore all possible combinations of elementary airspace modules in order to build an optimal airspace partition where the workload is balanced as well as possible across the ATC sectors. The results are compared both to the real airspace configurations and to the forecast made by flow management operators in a French en-route air traffic control centre.

Lexicographic optimisation for optimal departure aircraft trajectories

This paper presents a strategy for designing noise abatement procedures, aimed at reducing the exposure to noise of the population living around the airports. Noise optimal departing routes are computed for a specific aircraft type and for a given scenario (airport and airspace configuration, local geography, etc.). Hence, a non-linear multi-objective optimal control problem is formally identified and detailed. Lexicographic optimisation is presented as an alternative optimisation technique to the common used weighting methods. This approach establishes a hierarchical order among all the optimisation objectives instead of giving them a specific (and most of the time, arbitrary) weight. In this work, the optimisation criteria are chosen as the maximum perceived noise levels at different sensitive locations as well as some criteria associated with the operation of the aircraft. A practical example is given, in a hypothetical scenario, showing how the proposed optimisation technique may help aircraft procedure designers when dealing with departing routes.

Feasibility of Integrating Automated Separation Assurance with Controller-Managed Aircraft Operations in the Same Airspace

This study used a human-in-the-loop simulation to examine the feasibility of mixed equipage operations in an automated separation assurance environment under higher traffic densities. The study involved two aircraft equipage alternatives—with and without data link—and four traffic conditions. In all traffic conditions, the unequipped traffic count was increased linearly throughout the scenario from approximately 5–20 aircraft. The first condition consisted solely of this unequipped traffic, while the remaining three conditions included a constant number of equipped aircraft operating within the same airspace: 15 equipped aircraft in the second condition, 30 in the third condition, and 45 in the fourth condition. If traffic load became excessive during any run, participants were instructed to refuse sector entry to inbound unequipped aircraft until sector load became manageable. Results showed a progressively higher number of unequipped aircraft turned away under the second, third, and fourth scenario conditions. Controller self-reported workload also increased progressively with the increasing level of equipped aircraft. Participants rated the mixed operations concept as acceptable, with some qualifications about procedures and information displays. These results showed that mixed operations might be feasible in the same airspace if unequipped aircraft count is held to a workable level. This level will decrease with increasing complexity. The results imply that an integrated airspace configuration is feasible to a limit. The results also indicate that the conflict detection and resolution automation, equipage, and traffic density are important factors that must be considered in airspace configuration.

Describing Airspace Complexity: Airspace Response to Disturbances

In ongoing efforts to balance air traffic demand and airspace capacity, airspace complexity stands as a fundamental research problem.This paper proposes a newnotion of airspace complexity by capturing howdifficult a given traffic situation is in terms of the control activity required to accommodate disturbances such as the entrance of another aircraft into the airspace. A complexity map is introduced that offers a graphical view of the control activity required to accept a new aircraft as a function of its essential parameters. The proposed method is illustrated with examples related to traffic flow management and dynamic airspace configuration.

Airspace Configuration Concepts for the Next Generation Air Transportation System

Future airspace should adapt to changes in traffic demand, equipage, and weather. In order to achieve this capability, future airspace configuration must be flexible, adaptable, and able to accommodate new airspace elements such as highways-in-the-sky and generic sectors. This paper presents mid-term and long-term concepts for airspace configuration. These concepts were developed based on literature reviews, field observations, discussions with subject matter experts, and research workshops. The mid-term airspace configuration concept includes high altitude airspace where user-preferred routes will be predominant and low altitude airspace divided into regions for super density metroplex areas and conventionally structured low altitude airspace. The long-term airspace configuration includes four primary regions: airspace for automated separation assurance, high altitude flexible airspace, super density metroplex operations low-altitude airspace, and structured low-altitude airspace. These preliminary concepts are being matured using simulations and benefits assessments.

Investigating complexity factors in UK air traffic management

As air traffic volume continues to expand, the primary controller task of maintaining aircraft separation becomes more difficult and also more complex. Increased complexity of traffic can result in human performance problems for the controller, and may result in errors, all of which can contribute to incidents wherein there is a loss of separation between aircraft. However, air traffic complexity is not easy to understand or model, with U.K. airspace configurations and traffic patterns differing for each airspace sector, and traffic patterns changing throughout the day. This study, therefore, aimed to determine those factors that increase complexity for the controller. This was achieved by using an expert judgment process, with 4 independent controller groups, to elicit the top 12 factors contributing to complexity. This factor listing was corroborated by analysis of 1 year's sample of U.K. aircraft proximity incident reports.

Airspace configuration at different transpulmonary pressures in normal and paraquat-induced lung injury in rats.

The aim of this study is to evaluate histoarchitecture of airspaces at different positive transpulmonary pressures, both during inflation and deflation of excised normal and paraquat-damaged rat lungs. Freshly excised lungs were placed in a plethysmograph connected to a graded pipette. Immediately after the achievement of the desired pressure level (5, 15, 25 cm H2O during inflation, and 15 and 5 cm H2O during deflation), the tracheal cannula was occluded and lungs were quick-frozen by immersion in liquid nitrogen, and fixed using Carnoy's solution. Sections representing the central and peripheral areas of the lungs were sampled and processed for paraffin embedding and stained with hematoxylin-eosin. By means of stereological techniques, surface-to-volume ratio (S/V) and the fraction of large-volume gas-exchanging airspaces (LVGEAS) were determined. We observed in paraquat-treated animals evidence of alveolar instability close to the resting volume. Structural unevenness was minimized by massive recruitment followed by alveolar pressurization. In conclusion, this work demonstrates that morphological evidence of uneven distribution of inspired air may be partially reversed by applying larger alveolar pressures. These larger pressures applied at the end-expiration in vivo (positive end-expiratory pressure, PEEP) can minimize the distortion of lung microarchitecture during ventilation.

The effect of airspace loading by controlled air traffic on the air traffic control system

The purpose of this paper is to examine briefly the amount of traffic which air controllers can manage with varying levels of automation. It is shown that automated aids to the controller expand his capacity to handle traffic by a factor of 2-3. The use of area navigation and rerouting can increase his traffic handling capacity by another factor of 2-3. Application of both techniques will be necessary eventually to control the traffic forecasted for the 1990's. The contents of this paper are based in part upon a study performed for the DOTATC Advisory Committee entitled "New York airspace loading and configuration" [1].