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With the rapid expansion of transportation demand, the number of global flights has rapidly increased, which also poses challenges to air traffic management (ATM). Considering that the radar system in ATM can no longer meet the requirements of flight safety, a very promising next-generation air traffic control technology—Automatic Dependent Surveillance Broadcast (ADS-B) technology has been introduced. However, in the event of on-board equipment failure and local area signal interference, the ADS-B's signal will disappear or be interrupted. This sudden situation can pose a danger to aviation safety. To solve this problem, this article proposes a bidirectional long short-term memory (Bi-LSTM) network prediction method combining historical ADS-B data to short-term predict the trajectory of aircraft, which can improve aviation safety in busy airspace. Firstly, the problem of frequent dynamic modeling of different types of aircraft was solved by utilizing historical ADS-B data as the data source. Secondly, the data cleansing method is proposed for ADS-B raw data. Furthermore, considering that the spatial trajectory of the aircraft is a complex time series with continuity and interactivity, a bidirectional LSTM based aircraft trajectory prediction framework is proposed to further improve prediction accuracy. Finally, a trajectory with frequent changes was selected for prediction, and compared with 7 prediction methods. The results showed that the proposed method had high prediction accuracy, thus also improving the aviation safety of the aircraft. [ABSTRACT FROM AUTHOR]

The primary concern of an air traffic controller is to ensure the safety and fluidity of ever-increasing air traffic. This requires effective training through practical work supervised by instructors. Based on certain rules called separation rules, the trainee must find a solution to a traffic configuration defined by flight plans (FPL) initially containing a number of conflicts. This solution will then be compared to the one proposed by the instructor. The purpose of this article is to replace the instructor with a Geographical Information System (GIS) solution combined with a genetic algorithm which, from a set of FPLs, will find the best solution to ensure on the one hand the safety of the aircraft but also minimizing the distance and the changes to be made. The application will use the GAMA platform, very suitable for this and a set of tests composed of actual exercises will be performed to validate the work. [ABSTRACT FROM AUTHOR]

The popularity of air transportation, both for personal and commercial uses, has been growing in recent years. As a result, the traffic volume in the airspace is constantly increasing, which leads to the higher chances of conflicts among aircraft. In air traffic management, conflict detection and resolution are challenging and stressful tasks due to the highly dynamic nature of aircraft flight plans as well as the interdependency among pilots' decisions. Therefore, reliable and comprehensive decision-making techniques are necessary to deal with such conflicts in the airspace in a timely manner. In this regard, innovative technological developments are essential to assist decision-makers. In this paper, we propose a semi-decentralized, three-stage algorithm based on game theory to resolve potential conflicts among multiple aircraft traveling in a 3D shared airspace. The result from the algorithm shows that deviation costs are highly sensitive to the level of congestion in the airspace. The proposed algorithm provides useful information for air traffic control and pilots to enhance their coordination and facilitate decision-making procedures in scenarios with single and multiple conflicts during both nominal and deviated-from-nominal situations. [ABSTRACT FROM AUTHOR]

We provide evidence for a power law relationship between the subjective one-dimensional Instantaneous Self Assessment workload measure (five-level ISA-WL scale) and the radio communication of air traffic controllers (ATCOs) as an objective task load variable. It corresponds to Stevens' classical psychophysics relationship between physical stimulus and subjective response, with characteristic power law exponent γ of the order of 1. The theoretical model was validated in a human-in-the loop air traffic control simulation experiment with traffic flow as environmental stimulus that correlates positively with ATCOs frequency and duration of radio calls (task load, RC-TL) and their reported ISA-WL. The theoretical predictions together with nonlinear regression-based model parameter estimates expand previously published results that quantified the formal logistic relationship between the subjective ISA measure and simulated air traffic flow (Fürstenau et al. in Theor Issues Ergon Sci 21(6): 684–708, 2020). The present analysis refers to a psychophysics approach to mental workload suggested by (Gopher and Braune in Hum Factors 26(5): 519–532, 1984) that was recently used by (Bachelder and Godfroy-Cooper in Pilot workload esimation: synthesis of spectral requirements analysis and Weber's law, SCL Tech, San Diego, 2019) for pilot workload estimation, with a corresponding power law exponent in the typical range of Stevens' exponents. Based on the hypothesis of cognitive resource limitation, we derived the power law by combination of the two logistic models for ISA-WL and communication TL characteristics, respectively. Despite large inter-individual variance, the theoretically predicted logistic and power law parameter values exhibit surprisingly close agreement with the regression-based estimates (for averages across participants). Significant differences between logistic ISA-WL and RC-TL scaling parameters and the corresponding Stevens exponents as ratio of these parameters quantify the TL/WL dissociation with regard to traffic flow. The sensitivity with regard to work conditions of the logistic WL-scaling parameter as well as the power law exponent was revealed by traffic scenarios with a non-nominal event: WL sensitivity increased significantly for traffic flow larger than a critical value. Initial analysis of a simultaneously measured new neurophysiological (EEG) load index (dual frequency head maps, DFHM, (Radüntz in Front Physiol 8: 1–15, 2017)) provided evidence for the power law to be applicable to the DFHM load measure as well. [ABSTRACT FROM AUTHOR]

An accurate recognition method of the air traffic flow pattern is proposed based on historical flight trajectory data to understand the spatial distribution of air traffic flow and improve the airspace utilization in the terminal area. Due to the high dimensionality of flight trajectory data, we establish a trajectory similarity model based on the geodesic distance and use an improved spectral clustering algorithm to classify the flight trajectory sample data. An improved algorithm based on the minimum spanning tree is presented to extract the skeleton similarity between the tracks and obtain the model of the prevalent traffic flow. The experimental results show that the method can accurately divide 1070 flight paths into 5 categories and extract 7 prevalent traffic flows, exhibiting strong robustness to abnormal trajectories and noise. [ABSTRACT FROM AUTHOR]

In the document of the Radio Technical Commission for Aeronautics (RTCA) [1], a methodology has been developed for the flight safety level assessment when using a promising automatic dependent surveillance system in broadcast mode (ADS-B) intended for certification of an air traffic control system. As the analysis presented in the article has shown, this technique is based on an erroneous hypothesis, the use of which leads to underestimated requirements for the ADS-B certified system. The example considered in the article shows that the rejection of this erroneous hypothesis can lead to tightening the requirements by an order of magnitude. To obtain correct results, the article proposes an easy-to-compute modification of the technique that is devoid of this, generally speaking, serious drawback. The use of the proposed technique is illustrated by an example. [ABSTRACT FROM AUTHOR]

Stress is a word used to describe human reactions to emotionally, cognitively and physically challenging experiences. A hallmark of the stress response is the activation of the autonomic nervous system, resulting in the "fight-freeze-flight" response to a threat from a dangerous situation. Consequently, the capability to objectively assess and track a controller's stress level while dealing with air traffic control (ATC) activities would make it possible to better tailor the work shift and maintain high safety levels, as well as to preserve the operator's health. In this regard, sixteen controllers were asked to perform a realistic air traffic management (ATM) simulation during which subjective data (i.e. stress perception) and neurophysiological data (i.e. brain activity, heart rate, and galvanic skin response) were collected with the aim of accurately characterising the controller's stress level experienced in the various experimental conditions. In addition, external supervisors regularly evaluated the controllers in terms of manifested stress, safety, and efficiency throughout the ATM scenario. The results demonstrated 1) how the stressful events caused both supervisors and controllers to underestimate the experienced stress level, 2) the advantage of taking into account both cognitive and hormonal processes in order to define a reliable stress index, and 3) the importance of the points in time at which stress is measured owing to the potential transient effect once the stressful events have ceased. [ABSTRACT FROM AUTHOR]

The emission and contrail of flights at high altitude sector have a great impact on the environment. The paper establishes the multi-objective optimization method of high altitude sector operation based on environmental protection, which can reduce the impact of sector air traffic operation on the environment and enhance the operation efficiency of the high altitude sector. According to the operation characteristics of the sector, the aviation meteorological data of the sector are analyzed, and the forming conditions of the contrail are calculated. Considering the air traffic control rules and aircraft flight characteristics, a multi-objective optimization model of sector flight allocation strategy is established, and the influence of aviation meteorological conditions and different allocation strategy combinations on the optimal operation of sector is analyzed. To solve the multi-objective optimization model, the paper uses an evolutionary computation method in intelligence computing and takes non-dominated sorted genetic algorithm-II with elitist strategy (NSGA-II). Shanghai Area No.20 sector (ZSSSAR20) is selected as the case in this paper. Example verification reveals that taking number of contrails, fuel consumption and flight delays as the optimization targets, aircraft are more likely to rely on altitude deployment strategy so as to better reduce the impact of air traffic operation en route on environment, and improve sector operation efficiency en route. [ABSTRACT FROM AUTHOR]

Air traffic management is organized into filters in order to prevent tactical controllers from dealing with complex conflicting situations. In this article, we describe an experiment showing that a dynamic conflict display could improve human performance on complex conflict situations. Specifically, we designed a display tool that represents the conflicting portions of aircraft trajectories and the evolution of the conflict zone when the user adds a maneuver to an aircraft. The tool allows the user to dynamically check the potential conflicting zones with the computer mouse before making a maneuver decision. We tested its utility on a population of forty students: twenty air traffic controller (ATC) students at the end of their initial training and twenty engineering students with the same background but no ATC training. They had to solve conflicts involving 2-5 aircraft with a basic display and with the dynamic visualization tool. Results show that in easy situations (2 aircraft), performance is similar with both displays. However, as the complexity of the situations grows (from 3 to 5 aircraft), the dynamic visualization tool enables users to solve the conflicts more efficiently. Using the tool leads to fewer unsolved conflicts and shorter delays. No significant differences are found between the two test groups except for delays: ATC students give maneuvers that generate less delays than engineering students. These results suggest that humans are better able to manage complex situations with the help of our conflict visualization tool. [ABSTRACT FROM AUTHOR]

The safe and efficient operation of air traffic is highly dependent on the performance of the Air Traffic Control Officer (ATCO). The ATCOs control the traffic within defined areas by monitoring the traffic and granting clearances. A key element in analyzing the ATCOs is their interaction with the environment through their workplace. Especially the influence of task load on their situation awareness (SA) and applied control strategy provides information on the quality of the workplace. As task load increases, controllers are able to maintain performance by using different management or compensation strategies. This article supports the evaluation of ATCO’s workplaces by focusing on whether probe techniques for assessing SA are applicable for tower control operation and for measuring the influences of increased task load on the control strategy. An experiment with nine ATCOs was conducted in a simulated real-time air traffic control environment. Different measurements for SA were applied and compared regarding their efficiency and validity. The manipulation of task load and visibility influenced the SA and control strategy at the same time. Performance metrics were selected in advance to evaluate the participant’s efficiency. SA was measured with a probe technique and an offline self-assessment method. Findings suggest that probe techniques increase the insight into the understanding of SA in comparison to self-assessment and that they are applicable to the air traffic control environment. Control strategies were derived from the information-gathering process via the eye-movement behavior and connected to task load. The results imply that SA is part of the individual performance and that increasing demand through task load is handled with an adaptation of the control strategy. [ABSTRACT FROM AUTHOR]

In order to address the rapidly increasing load of air traffic operations, innovative algorithms and software systems must be developed for the next generation air traffic control. Extensive verification of such novel algorithms is key for their adoption by industry. Separation assurance algorithms aim at predicting if two aircraft will get closer to each other than a minimum safe distance; if loss of separation is predicted, they also propose a change of course for the aircraft to resolve this potential conflict. In this paper, we report on our work towards developing an advanced testing framework for separation assurance. Our framework supports automated test case generation and testing, and defines test oracles that capture algorithm requirements. We discuss three different approaches to test-case generation, their application to a separation assurance prototype, and their respective strengths and weaknesses. We also present an approach for statistical analysis of the large numbers of test results obtained from our framework. [ABSTRACT FROM AUTHOR]