Air Traffic Management Automation Research Articles

“In automation we trust” - Australian air traffic controller perspectives of increasing automation in air traffic management

This study investigates the views of Australian Air Traffic Controllers (ATCOs) on increasing levels of automation in Air Traffic Managements Systems (ATMS). An online survey of current and former Australian ATCOs was conducted to identify what tools are considered useful and to what extent automation should be used within ATMS, as well as how increasing automation is expected to impact ATCOs situational awareness. The results highlighted that automation tools that supported and assisted the controller were more likely to be accepted by ATCOs. Automation tools that assumed/replaced the decision making and authority of the ATCO, had lower levels of acceptance by controllers. Increased automation (electronic strips) was considered to have both a positive and negative effect on ATCO situational awareness dependant on the type of role performed by the controller. When transitioning to systems with increased automation, the lack of system understanding/training, skill degradation and the changing role of controllers were considered the three biggest safety risks. By considering this research, the aviation industry can focus on the introduction of automation tools that can best assist ATCOs. Additionally, this study provides invaluable research from ATCOs to inform Air Navigation Service Providers (ANSPs) when implementing more automated ATMS.

An analysis and enhanced proposal of atmospheric boundary layer wind modelling techniques for automation of air traffic management

The air traffic management automation imposes stringent requirements on the weather models, in such a way that they should be able to provide reliable short-time forecasts in digital formats in almost real time. The atmospheric boundary layer is one of the regions where aircraft operation and coordination are critical and therefore atmospheric model performance is also vital. This paper presents conventional and innovative techniques to improve the accuracy in the forecasting of winds in the lower atmospheric layer, proposing mechanisms to develop better models including deterministic and stochastic simulations. Accuracy is improved by optimizing the grid, assimilating observations in cycling simulations and managing a number of ensemble members. An operation-driven post-processing stage helps to incorporate detailed terrain definitions and real-time observations without re-running the model. The improvements are checked against mesoscale weather simulations at different scales and a dedicated flight campaign. The results show good performance of the model without sensitively increasing the required throughput.

Brain-Computer Interface-Based Adaptive Automation to Prevent Out-Of-The-Loop Phenomenon in Air Traffic Controllers Dealing With Highly Automated Systems.

Increasing the level of automation in air traffic management is seen as a measure to increase the performance of the service to satisfy the predicted future demand. This is expected to result in new roles for the human operator: he will mainly monitor highly automated systems and seldom intervene. Therefore, air traffic controllers (ATCos) would often work in a supervisory or control mode rather than in a direct operating mode. However, it has been demonstrated how human operators in such a role are affected by human performance issues, known as Out-Of-The-Loop (OOTL) phenomenon, consisting in lack of attention, loss of situational awareness and de-skilling. A countermeasure to this phenomenon has been identified in the adaptive automation (AA), i.e., a system able to allocate the operative tasks to the machine or to the operator depending on their needs. In this context, psychophysiological measures have been highlighted as powerful tool to provide a reliable, unobtrusive and real-time assessment of the ATCo’s mental state to be used as control logic for AA-based systems. In this paper, it is presented the so-called “Vigilance and Attention Controller”, a system based on electroencephalography (EEG) and eye-tracking (ET) techniques, aimed to assess in real time the vigilance level of an ATCo dealing with a highly automated human–machine interface and to use this measure to adapt the level of automation of the interface itself. The system has been tested on 14 professional ATCos performing two highly realistic scenarios, one with the system disabled and one with the system enabled. The results confirmed that (i) long high automated tasks induce vigilance decreasing and OOTL-related phenomena; (ii) EEG measures are sensitive to these kinds of mental impairments; and (iii) AA was able to counteract this negative effect by keeping the ATCo more involved within the operative task. The results were confirmed by EEG and ET measures as well as by performance and subjective ones, providing a clear example of potential applications and related benefits of AA.

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.

Research on Collision Avoidance in Terminal Area Based on RNP and 3D Paths

We describes an operational concept in this paper, it enables increased airspace and airport capacity by using the Flight Management System (FMS), Required Navigation Performance capabilities (RNP) and air traffic management automation tools. This concept can be applied to en route and terminal operation. It realizes ground to air communication by using of voice and data chain. This paper analyzes several key performance parameters which affect arrival management process. This concept models the arrivals by using the performance modeling approach. The results of the modeling proves several factors that influence the delivery accuracy and delay in the arrival process ,these factors include the path and speed discretization, wind, trajectory prediction and navigation performance.

Digital meteorological service (DMET) in support of trajectory optimization and ATM automation

An improvement is required in the meteorological support for the future Air Traffic Management (ATM) System. New concepts of weather services must be tailored to enable a safer and more efficient aviation: better accuracy, increased data availability, real time support, digital service and shared information are some of the foundational elements underlying trajectory optimization, automation of operations, and fuel & time cost-reductions. A Digital Meteorological Service (DMET) is cornerstone in a net-centric service-oriented ATM system architecture where available data, air-ground connectivity and modern computational resources are taken advantage of to attain a 4D predictive model specifically designed for real-time support to aircraft operations. The effort presented here consists on the development of a prototype DMET service that computes atmospheric data from several sources to produce predicted 4D atmosphere scenarios regularly available to subscribers. By using many data sources –such as forecasts from global and mesoscale weather models, in-situ observations and the introduction of local airborne parameters, a well-tailored forecast product is developed. It consists of a 4D grid of pressure, temperature and wind data fields that are valid into an airspace cube of about 150 × 150 × 20 km, within a time interval of 2.5 hours. On top of this model, minimum time, minimum consumption and other interesting weather-based optimization functions are covered, all being processed in parallel for a future migration to a supercomputing centre.

Defining the drivers for accepting decision making automation in air traffic management

Air Traffic Management (ATM) operators are under increasing pressure to improve the efficiency of their operation to cater for forecasted increases in air traffic movements. One solution involves increasing the utilisation of automation within the ATM system. The success of this approach is contingent on Air Traffic Control Operators' (ATCOs) willingness to accept increased levels of automation. The main aim of the present research was to examine the drivers underpinning ATCOs' willingness to accept increased utilisation of automation within their role. Two fictitious scenarios involving the application of two new automated decision-making tools were created. The results of an online survey revealed traditional predictors of automation acceptance such as age, trust and job satisfaction explain between 4 and 7% of the variance. Furthermore, these predictors varied depending on the purpose in which the automation was to be employed. These results are discussed from an applied and theoretical perspective. Statement of Relevance: Efficiency improvements in ATM are required to cater for forecasted increases in air traffic movements. One solution is to increase the utilisation of automation within Air Traffic Control. The present research examines the drivers underpinning air traffic controllers' willingness to accept increased levels of automation in their role.

Role of avionics in trajectory-based operations

Air Traffic Management automation systems are being developed and fielded to assist controllers in handling more aircraft and larger airspace per controller. Many of these systems are time-based and built upon predicting the aircraft trajectories as accurately as possible. Trajectories of multiple aircraft are strategically deconflicted by modifying appropriate trajectories and issuing corresponding clearances to the aircraft. However, disturbances and modeling errors will cause aircraft to deviate from their predicted trajectories and controllers will need to take action to keep trajectories free from conflict. The associated increase in workload will reduce the usefulness of these automation systems. On-board avionics can help improve the accuracy of the trajectory prediction system in three ways: (1) sharing aircraft state information to improve the performance of the ground trajectory prediction system, (2) sharing airborne prediction results and allowable minimum and maximum arrival times at key route waypoints, and, finally, (3) by applying feedback control onboard the aircraft to autonomously correct for disturbances encountered in flight. This presents an analysis of trajectory dispersion with and without airborne time of arrival control, presents an operational concept for air/ground trajectory negotiation, discusses integration with airborne merging and spacing algorithms, and raises concerns about challenges in implementing this integrated solution.

Operational Evaluation of Traffic Management Advisor Using Statistical Performance Metrics and Simulation Approach

The Traffic Management Advisor (TMA) is an air traffic management automation tool designed to allow more aircraft to land during the peak arrival periods by increasing the airspace capacity and minimizing delay via better scheduling, spacing, sequencing, and runway allocation of arrival traffic. This paper evaluates the TMA’s operational performance at George Bush Intercontinental airport in Houston over three daily selected rush-hour periods in the pre- and post-TMA deployments, using both the conventional and newly proposed performance metrics. The performance metrics used for the statistical analysis include: flight distances flown during transition from en route to terminal airspace, runway arrival distributions, and airport arrival traffic distributions. The results obtained from the analysis show that TMA improves the characteristics of arrival air traffic by better runway balancing, improved airport arrival throughput, and more evenly distributed airport arrivals. In addition to the statistical analysis, a model is developed to simulate aircraft transit between arrival arcs and meter fixes, queuing, and runway arrivals during a selected rush hour period in the post-TMA era.

Turn-Constrained Route Planning for Avoiding Hazardous Weather

We investigate the problem of algorithmically synthesizing turn-constrained routes that minimize exposure to hazardous weather. Such a problem is suitable to air traffic management automation and aircraft flight management systems. Our algorithm synthesizes routes that aircraft may follow from a specified start to finish location. Example applications include synthesizing routes (1) from airport metering fix locations to runway final approach fixes, and (2) from sector boundary crossing locations to airport metering fix locations. The algorithm takes into account aircraft dynamics limits on velocity and acceleration, pilot and controller workload considerations (e.g., the number of turn maneuvers), and other constraints (e.g., utilizing arrival vs. departure corridors or avoiding special use airspace regions). The solution approach is based on searching in an appropriate discretization of a geometric model of the airspace using a dynamic programming algorithm for optimal paths having a bounded number of turns. Examples are given for Dallas Ft. Worth Airport.

Airborne Technology for Distributed Air Traffic Management

Worldwide air traffic levels are growing at a rate expected to double the current traffic level by the year 2020. The current technology Air Traffic Control systems are already stretched to their limit and are prone to large delays during the peak summer travel season. There is doubt that the current systems can be scaled up to meet the expected demand levels. Many Air Traffic Management (ATM) automation systems have been proposed to increase the capability of controllers, and some are finding their way into operation. While ATM automation systems will help in handling more traffic, it is still doubtful that they can grow to meet the doubling in traffic levels foreseen. This paper presents an introduction to Distributed ATM – using the capability of airborne electronic systems to further relieve the controller workload. An overview of avionics capabilities is presented, followed by a detailed description of five specific examples of airborne capability that can be used to increase airspace capacity, as listed below. (1) An onboard method to accurately control an aircraft to cross a waypoint in the terminal area at a required time of arrival (RTA). (2) A trajectory negotiation process whereby the ground-based ATM system uses the 4D predicted trajectory computed by the aircraft, gives the aircraft RTA constraints to solve traffic conflicts, and contracts the aircraft to stay within a specified tolerance of the predicted 4D trajectory. (3) A formation flight system whereby multiple aircraft can be flown with reduced separation and controlled as a single aircraft. (4) An onboard alerting system for closely spaced parallel approaches that can increase the capacity of an airport in instrument meteorological conditions. (5) An onboard collision avoidance system that generates a conflict-free trajectory through complex airspace.

Neighboring Optimal Aircraft Guidance in Winds

The technique of Neighboring Optimal Control is extended to handle cases of parameter change in the system dynamic model. This extension is used to develop an algorithm for optimizing horizontal aircraft trajectories in general wind fields using time-varying linear feedback gains. The minimum-time problem for an airplane traveling horizontally between two points in a variable wind field (a type of Zermelo Problem) is used to illustrate how perturbations in system parameters can be accounted for by augmenting the dynamic model with additional bias states. For the special case of a constant wind shear in the cross-track direction, analytical and numerical results are derived for bias perturbations. Numerical simulations are presented to demonstrate the performance of the proposed state-augmentation technique. An additional example is used to demonstrate an algorithm to compute near-optimal trajectories in general wind fields. The algorithm is based on nondimensionalizing the neighboring optimal control solutions and using piecewise linearly varying wind and horizontal wind shear parameters. One proposed application of this technique is to the computation and real-time update of time-optimal trajectories in wind fields by onboard flight management systems and by ground-based air traffic management automation tools.

Accuracy of RUC-1 and RUC-2 Wind and Aircraft Trajectory Forecasts by Comparison with ACARS Observations

Abstract As part of an investigation into terminal airspace productivity sponsored by the NASA Ames Research Center, a study was performed at the Forecast Systems Laboratory to investigate sources of wind forecast error and to assess differences in wind forecast accuracy between the 60-km Rapid Update Cycle, version 1 (RUC-1), and the newer 40-km RUC-2. Improved knowledge of these errors is important for development of air traffic management automation tools under development at NASA Ames and elsewhere. This information is also useful for operational users of RUC forecast winds. To perform this study, commercial aircraft reports of wind reported through Aircraft Communications, Addressing, and Reporting System (ACARS) were collected in a region over the western and central United States for a 13-month period, along with RUC-1 and RUC-2 wind forecasts. Differences between forecasts and ACARS observations and estimates of ACARS wind observation error itself were both calculated. It was found that rms vector...

Automation in Air Traffic Management : Ratcliffe, S.Journal of Navigation, 1985, 38.3, 405–412

Automation in Air Traffic Management : Ratcliffe, S.Journal of Navigation, 1985, 38.3, 405–412

Automation in Air Traffic Management

By Air Traffic Management or ATM is meant the totality of the processes used, in the air and on the ground, to ensure safe and expeditious movement of all air traffic using controlled airspace. Computers are used on a large scale to support human planners in the management processes. Flight management computers in the aircraft, together with radar and flight-plan data processors on the ground, are conspicuous examples. Decision processes remain tasks for human controllers, although off-line computer models of traffic flow provide a background for the longer-term management decisions.