Air Traffic Control Research Articles

Enhancing air traffic control: A transparent deep reinforcement learning framework for autonomous conflict resolution

Rising traffic demands, advancements in automation, and communication breakthroughs are opening new design frontiers for future air traffic controllers (ATCs). This article introduces a deep reinforcement learning (DRL) controller to support conflict resolution in autonomous free flight. While DRL has made significant strides in this domain, there is scant focus in existing research on the explainability and safety of DRL controllers, especially their robustness against adversarial attacks. To tackle these concerns, we have engineered a fully transparent DRL framework that: (i) separates the intertwined Q-value learning model into distinct modules for safety-awareness and efficiency (target attainment); and (ii) incorporates data from nearby intruders directly, thereby obviating the need for central control. Our simulated experiments demonstrate that this bifurcation of safety-awareness and efficiency not only enhances performance in free flight control tasks but also substantially boosts practical explainability. Moreover, the safety-oriented Q-learning component offers detailed insights into environmental risk factors. To assess resilience against adversarial attacks, we present a novel attack strategy that induces both safety-centric and efficiency-centric disruptions. This adversary aims to degrade safety/efficiency by targeting the agent at select time intervals. Our experimental results reveal that this targeted approach can provoke as many collisions as a uniform attack strategy — that is, attacking at every opportunity — while engaging the agent four times less frequently, shedding light on the potential and limitations of DRL in future ATC system designs. The source code is available to the public at https://github.com/WLeiiiii/Gym-ATC-Attack-Project.

Prediction and Control of Broadband Noise Associated with Advanced Air Mobility—A Review

This review presents an overview of advanced air mobility broadband noise (BBN) prediction and control techniques, highlighting significant advancements in various prediction models. Methods such as the semi-empirical Brooks–Pope–Marcolini (BPM) model, analytical Amiet model, and time-domain models based on the FW-H equation have been extensively studied. Machine learning (ML) shows promise in BBN prediction but requires extensive data training and application to noise source mechanisms. Passive control methods, such as leading and trailing edge serrations and blade tip designs, have been partially successful but often compromise the aerodynamic performance. Active control methods, like suction and blowing control, trim adjustments, and dielectric barrier discharge (DBD) plasma actuators, show great potential, with the latter two being particularly effective for reducing BBN in thin propeller structures. Overall, while progress has been made in understanding and predicting BBN, further research is needed to refine these methods and develop comprehensive noise control strategies. These advancements hold significant promise for effective and efficient noise mitigation in future AAM vehicles.

Adverse Cardiovascular Effects of Nicotine Delivered by Chronic Electronic Cigarettes or Standard Cigarettes Captured by Cardiovascular Intrinsic Frequencies.

Electronic cigarettes have gained popularity as a nicotine delivery system, which has been recommended by some as an aid to help people quit traditional smoking. The potential long-term effects of vaping on the cardiovascular system, as well as how their effects compare with those from standard cigarettes, are not well understood. The intrinsic frequency (IF) method is a systems approach for analysis of left ventricle and arterial function. Recent clinical studies have demonstrated the diagnostic and prognostic value of IF. Here, we aim to determine whether the novel IF metrics derived from carotid pressure waveforms can detect effects of nicotine (delivered by chronic exposure to electronic cigarette vapor or traditional cigarette smoke) on the cardiovascular system. One hundred seventeen healthy adult male and female rats were exposed to purified air (control), electronic cigarette vapor without nicotine, electronic cigarette vapor with nicotine, and traditional nicotine-rich cigarette smoke, after which hemodynamics were comprehensively evaluated. IF metrics were computed from invasive carotid pressure waveforms. Standard cigarettes significantly increased the first IF (indicating left ventricle contractile dysfunction). Electronic cigarettes with nicotine significantly reduced the second IF (indicating adverse effects on vascular function). No significant difference was seen in the IF metrics between controls and electronic cigarettes without nicotine. Exposure to electronic cigarettes with nicotine significantly increased the total IF variation (suggesting adverse effects on left ventricle-arterial coupling and its optimal state), when compared with electronic cigarettes without nicotine. Our IF results suggest that nicotine-containing electronic cigarettes adversely affect vascular function and left ventricle-arterial coupling, whereas standard cigarettes have an adverse effect on left ventricle function.

Runway assignment optimisation model for Istanbul Airport considering multiple parallel runway operations

Abstract The aviation industry has rapidly developed in recent years. Due to the increased number of flight operations, managing air traffic has become essential. The air traffic management system aims to reduce the air traffic control workload and use existing resources more efficiently. This study proposed a new mixed integer linear programming model to minimise the total fuel consumption during taxi operations for the runway assignment problem, comparing the actual Istanbul Airport runway assignment data. The average taxi times are calculated using the 30,000-flight operations data for each arrival and departure taxi route. Also, 47 different aircraft types are obtained using the data for the fuel consumption calculation. The International Civil. Aviation Organisation (IACO) aircraft engine emissions databank provides the fuel consumption values for each aircraft according to engine type. This approach allows our model to calculate more realistic fuel consumption for taxi operations, as each aircraft engine type has a different fuel consumption value. The proposed model is implemented at Istanbul Airport, the busiest airport in Turkey, where multiple parallel runway operations are applied. The results showed that the proposed model reduced total fuel consumption for taxi operations between 6.6% and 14.4% compared to the actual Istanbul Airport runway assignment data.

Investigation of Aircraft Conflict Resolution Trajectories under Uncertainties.

As air traffic intensity increases and stochastic uncertainties, such as wind direction and speed, continue to impact air traffic controllers' workload significantly, airlines are increasingly pressured to reduce costs by flying via straighter/more direct trajectories. Due to these changes, it is important to search for new means/solutions for aircraft conflict resolution to ensure the required level of safety and rational flight trajectory. Such a solution could be the implementation of Dubin's method of flight trajectories. This paper aims to propose and deeply analyze a new mathematical model for two-aircraft conflict resolution where the Dubins method is applied in a dynamic conflict scenario. In this model, at a certain moment, the flight trajectory of one aircraft follows a path similar to a moving circle's tangential line. Upon that, the conflict detection and resolution (CDR) model considers wind uncertainty. The proposed CDR method could be applied when uncertainty such as wind direction and speed are inconstant (stochastic) throughout the simulation.

In Situ and Rapid Toxicity Assessment of Air Pollution by Self-Assembly Passive Colonization Hydrogel.

Air pollution is a leading environmental health risk factor, and in situ toxicity assessment is urgently needed. Bacteria-based bioassays offer cost-effective and rapid toxicity assessments. However, the application of these bioassays for air toxicity assessment has been challenging, due to the instability of bacterial survival and functionality when directly exposed to air pollutants. Here, we developed an approach employing self-assembly passive colonization hydrogel (SAPCH) for in situ air toxicity assessment. The SAPCH features a core-shell structure, enabling the quantitatively immobilization of bacteria on its shell while continuously provides nutrients from its core. An antimicrobial polyelectrolyte layer between the core and shell confines bacteria to the air-liquid interface, synchronizing bacterial survival with exposure to air pollutants. The SAPCH immobilized a battery of natural and recombinant luminescent bacteria, enabling simultaneous detection of various toxicological endpoints (cytotoxicity, genotoxicity and oxidative stress) of air pollutants within 2 h. Its sensitivity was 3-5 orders of magnitude greater than that of traditional liquid-phase toxicity testing, and successfully evaluating the toxicity of volatile organic compounds and combustion smoke. This study presents a method for in situ, rapid, and economical toxicity assessment of air pollution, making a significant contribution to future air quality monitoring and control.

A translational study evaluating a ruggedized portable oxygen concentrator versus an oxygen cylinder in simulated polytrauma intubation of swine.

Portable oxygen concentrators (POCs) are medical devices that use filters to selectively remove nitrogen from ambient air to produce concentrated, medical-grade oxygen. This is the first study to evaluate a ruggedized POC's performance during simulated polytrauma intubation. Twenty-seven swine were intubated and anesthetized with ketamine. At T=0, animals were extubated, received a chest wall injury, a tibia fracture, and 20% total blood volume controlled hemorrhage was initiated. At T=10 min, the swine were pre-oxygenated using a bag-valve mask connected to one of three randomized oxygen sources: (1) a ruggedized POC, (2) a M-15 oxygen cylinder, or (3) room air (control). At T=12 min, animals were re-intubated to simulate polytrauma intubation and connected to the test oxygen source for the remainder of the experiment. Surviving animals entered a 2-h period where partial pressure of oxygen (PaO2), oxygen saturation (SpO2), and regional oxygen saturation (rSO2) were monitored. Groups were compared using analysis of variance (ANOVA), Fisher's exact, log-rank analysis, or mixed-effects model as appropriate. All animals survived except one in the POC group. Mixed-effects models revealed differences between groups with regards to PaO2 (p<0.0001) and SpO2 (p=0.006). Based on post hoc analysis, oxygen cylinder PaO2 was superior to both POC and control, but there were no differences between POC and control PaO2. There were statistically and clinically significant differences in SpO2 during periods of pre-oxygenation (T=10‒12 min), intubation (T=12‒14 min), and immediately after intubation (T=14‒20 min). The POC battery was consumed in 43±13 min. In our swine model, a single, ruggedized POC provided inferior amounts of oxygen supplementation compared to an oxygen cylinder and performed no better than room air.

How Teaching Air Traffic Control College Students About Stress Improves Stress Management

The modern, fast-paced lifestyle intertwined with intricate technological advancements can significantly contribute to stress levels, which can impede decision making and adversely affect action tasks. For Air Traffic Control (ATC) professionals, stress management (SM) skills are increasingly recognized as essential for success. The intent of this study was to evaluate the effectiveness of SM technique training to enhance knowledge about stress and to promote the use of SM techniques. Thirty-one participants from an aeronautical university were assigned to either an experimental group receiving SM training or a control group. A questionnaire assessing SM knowledge and use of SM techniques was administered pre-training, immediately after training, and several weeks after training. Participants in the experimental group showed an increase in SM knowledge and a willingness to use SM techniques, particularly rational self-talk, even weeks after the training. Thus, SM training can improve stress awareness for ATC students, potentially enhancing aviation safety.

Cellular responses following ex vivo lung exposure to the nerve agent VX – Potential for additional treatment targets?

Following inhalation exposure to organophosphorus nerve agents, symptoms rapidly develop and severe respiratory symptoms, such as bronchorrhea and bronchoconstriction are the leading causes of lethality. Nerve agent-induced lung injury is little investigated and the standard treatment for symptomatic relief targets the enzyme acetylcholinesterase and muscarinic acetylcholine and GABAergic receptors. In the present study, cellular responses in lung tissue during the acute (40 min) and extended phase (24 h) following severe exposure to the nerve agent VX have been investigated using an ex vivo rat precision-cut lung slice model including electrostimulation to induce a cholinergic response. Changes in protein amount, cell viability, together with, inflammatory and oxidative stress markers have been determined in both the lung tissue and incubation medium.During the acute phase, VX caused significantly increased airway contraction and decreased airway relaxation. Five micromolar of VX did not affect the sample protein levels and cell viability in lung tissue. Among seven markers of cellular responses investigated in the lung tissue, increased levels of heme oxygenase-1 and matrix metalloproteinase-9 together with decreased levels of glutathione in the incubation medium were observed in the acute phase following VX-exposure compared to electrostimulation only. No difference in cellular response was observed following VX-exposure for 24 h compared to the air control. In comparison, LPS-exposure resulted in time-dependent changes in all markers of inflammation and oxidative response.In conclusion, the present study demonstrated VX-specific patterns of oxidative responses in the lung, as well as, signs of inflammatory response and remodelling of extracellular matrix. These potential mechanisms of tissue injury should be further investigated for their potential as additional therapeutic targets during the acute phase of intoxication.

Aerosolization ocular surface microorganisms accumulation effect during non-contact tonometer measurements

PurposeThis study aimed to verify that aerosolization ocular surface microorganisms (AOSMs) accumulated during non-contact tonometry (NCT) measurements.MethodsA total of 508 participants (740 eyes) were enrolled in the study. In Experiment 1, before NCT was performed on each eye, the air was disinfected, and environment air control samples were collected via Air ideal® 3P (Bio Merieux). During NCT measurements, microbial aerosol samples were collected once from each eye. In Experiment 2, we collected initial blank control samples and then repeated Experiment 1. Finally, in Experiment 3, after the background microbial aerosol investigation, we cumulatively sampled AOSMs from each 10 participants then culture once, without any interventions to interrupt the accumulation. The collected samples were incubated and identified using matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry (MALDI-TOF-MS).ResultsPathogenic Aerococcus viridans and other microorganisms from human eyes can spread and accumulate in the air during NCT measurements. The species and quantity of AOSMs produced by NCT measurements can demonstrate an accumulation effect.ConclusionAOSMs generated during NCT measurements are highly likely to spread and accumulate in the air, thereby may increase the risk of exposure to and transmission of bio-aerosols.

A Review on Radar-Based Human Detection Techniques.

Radar systems are diverse and used in industries such as air traffic control, weather monitoring, and military and maritime applications. Within the scope of this study, we focus on using radar for human detection and recognition. This study evaluated the general state of micro-Doppler radar-based human recognition technology, the related literature, and state-of-the-art methods. This study aims to provide guidelines for new research in this area. This comprehensive study provides researchers with a thorough review of the existing literature. It gives a taxonomy of the literature and classifies the existing literature by the radar types used, the focus of the research, targeted use cases, and the security concerns raised by the authors. This paper serves as a repository for numerous studies that have been listed, critically evaluated, and systematically classified.

The potential impact of AI innovations on US occupations.

An occupation is comprised of interconnected tasks, and it is these tasks, not occupations themselves, that are affected by Artificial Intelligence (AI). To evaluate how tasks may be impacted, previous approaches utilized manual annotations or coarse-grained matching. Leveraging recent advancements in machine learning, we replace coarse-grained matching with more precise deep learning approaches. Introducing the AI Impact measure, we employ Deep Learning Natural Language Processing to automatically identify AI patents that may impact various occupational tasks at scale. Our methodology relies on a comprehensive dataset of 17,879 task descriptions and quantifies AI's potential impact through analysis of 24,758 AI patents filed with the United States Patent and Trademark Office between 2015 and 2022. Our results reveal that some occupations will potentially be impacted, and that impact is intricately linked to specific skills. These include not only routine tasks (codified as a series of steps), as previously thought but also nonroutine ones (e.g. diagnosing health conditions, programming computers, and tracking flight routes). However, AI's impact on labor is limited by the fact that some of the occupations affected are augmented rather than replaced (e.g. neurologists, software engineers, air traffic controllers), and the sectors affected are experiencing labor shortages (e.g. IT, Healthcare, Transport).

Algorithms of Cross-Domain Redundancy Management for Resilient of Dual-Priority Critical Communication Systems

The paper presents models for managing cross-domain redundancy to enhance the reliability of two priority communication channels within critical infrastructure systems. Employing Markov chain models, the paper analyzes the impact of two distinct redundancy management strategies: a unified reserve pool and a separate pool approach with cross-domain resource sharing. The study introduces reliability improvement factors to quantify system performance, exploring their dependency on the number of additional redundant elements, their inherent reliability, and the chosen strategy for managing cross-domain redundancy. An air traffic control system serves as a case study of the application of the proposed management algorithms. Results indicate that the integration of resources from different priority domains significantly improves communication reliability. The findings may be useful for the design and operation of secure communication networks.

Creation of a novel microburst alarm for Air Traffic Control using a signal design framework

In this study, we used a previously validated alarm design framework to design and test a new microburst alarm for air traffic controllers. MethodsTwo air traffic controllers participated in a detailed structured interview, describing aspects of the current alarm that worked well and identifying features that should be changed. They then chose the properties most important to the design of this specific alarm. This information was used to develop a prototype microburst alarm while making iterative changes. A short interview asking about those properties was then conducted with sixty-two controllers at a national conference. ResultsWe developed an effective microburst alarm using the Signal Design Framework. Informativeness, Distinguishability, Saliency, Disruptiveness, Exclusivity, and Recognizability were improved by adding an electronically accelerated verbal component (‘Microburst!’) to the beginning and midway through the alert. The tonal component, volume, and timing of the prototype alarm were similar to that of the original alarm. During the alarm testing phase, most controllers agreed that the prototype would work well in both Air Traffic Control Tower and TRACON environments. Controllers agreed that incorporating an audible ‘Microburst!’ helped to direct their attention to the source of the alarm, especially in facilities where this alarm is uncommon. Controllers also spoke favorably of the length, pitch, oscillation, and timbre of the auditory component. ConclusionsWe used a validated framework to develop a new alarm that would work well for controllers in their environment. The framework facilitated design, iterative testing, and large-scale evaluation.

Cooperative Control of Air–Ground Swarms Under DoS Attacks via Cloud–Fog Computing

Cooperative Control of Air–Ground Swarms Under DoS Attacks via Cloud–Fog Computing

Analysis of Communication Effectiveness on Parking Stand Arrangements by the Apron Movement Control (AMC) Unit and Air Traffic Controller (ATC) of Halim Perdanakusuma International Airport

Analysis of Communication Effectiveness on Parking Stand Arrangements by the Apron Movement Control (AMC) Unit and Air Traffic Controller (ATC) of Halim Perdanakusuma International Airport

Peak Velocity Pressure of Air Traffic Control Towers: A Comparative Study

The aim of the study was to compare the structural resistance of air traffic control towers (ATCTs) in Europe over 100 feet (30.48 meters) in height by determining their peak velocity pressure. A comprehensive examination was conducted on the ATCTs of 64 airports across Europe, with a reference to the EN-1991-1-4 criteria. The findings revealed notable differences in wind speeds and peak velocity pressure values experienced by ATCTs located in diverse geographical regions of Europe. The Athens Airport ATCT recorded the highest peak velocity pressure at 2.52 kN/m², while the lowest value was recorded at Zagreb Airport ATCT at 0.89 kN/m². These differences play a crucial role in determining the structural resistance of ATCTs. ATCTs exposed to high peak velocity pressures should use stronger materials and incorporate aerodynamic designs. Considering the significant influence of geographical location on wind loads, these results provide important insights into the safety of existing and future ATCTs. It is recommended that these findings be extended by investigating ATCTs in different geographical regions and that structural design strategies against wind loads be more thoroughly investigated in future studies.

Increasing airspace capacity by improving ATCo’s efficiency through an innovative handover mechanism

The current lack of airspace capacity poses a major challenge to a sustainable and efficient air transport system, especially as future demand increases. Recent efforts to increase airspace capacity have focused on airspace sectorization. The digitization of Air Traffic Management (ATM) holds promise for overcoming current inefficiencies arising from the spatial fragmentation of airspace. While research has explored digitized ATM services to improve airspace capacity, there has been a notable gap in addressing spare capacity through enhancing synergies between adjacent sectors. This work proposes the application of an early handover (EHO) mechanism based on the spatio-temporal interdependencies among sectors and aircraft. Essentially, the mechanism involves alleviating overloaded sectors by redistributing peak demand to neighboring ones. This alleviation results in a reduction of the dedicated resources required to meet demand, facilitating the consolidation of sectors into larger units. Ultimately, this consolidation enhances airspace efficiency by minimizing the ATCo resources necessary for ATM. A simple and fast heuristic is proposed to select the aircraft for early handover to the air traffic controller of another sector, together with a specific schedule. A Colored Petri Net model is implemented to formalize the dynamic spatio-temporal interdependencies among adjacent sectors and to illustrate the EHO applicability using an academic exercise for illustration purposes. Afterwards, a simulation study based on real European airspace data is employed to illustrate and validate the mechanism. Finally, a discussion on the potential impacts of adopting the mechanism in real-life applications and lines of future research are provided.

Issues and Challenges Encountered By Air Traffic Controllers in the Philippines

Issues and Challenges Encountered By Air Traffic Controllers in the Philippines

A physical demands analysis to identify and delineate critical physical tasks for physically demanding US air force occupations.

Military physical fitness tests and standards often lack a scientific basis. Contrary to this traditional-historical precedent, US Air Force researchers use a "Two-Tier" health (Tier 1) and performance (Tier 2) approach to develop evidence-based criterion physical fitness tests, standards, and training. This study specifically and only addresses a physical demands analysis, the first step in a six-step process to develop Tier 2 occupationally specific, operationally relevant physical fitness tests and standards, and training guidance. This study conducted a physical demands analysis to identify and delineate occupationally specific, operationally relevant critical physical tasks for eight physically demanding US Air Force occupational specialties. A comprehensive five part physical demands analysis reviewed duty tasks, conducted focus groups, assessed incumbents, observed operational tasks, and interviewed senior leaders to detail critical physical tasks. The physical demands analysis delineated duty tasks to critical physical tasks for Special Tactics (556 to 40), Pararescue (981 to 50), Tactical Air Control (415 to 44), Special Operations Weather (586 to 50), Explosive Ordnance Disposal (1107 to 39), Security Forces (1286 to 25), Fire and Emergency Services (802 to 39), and Survival, Evasion, Resistance, and Escape (1099 to 25). The study approach proved efficacious for conducting a thorough physical demands analysis to identify and delineate occupationally specific, operationally relevant critical physical tasks for eight US Air Force physically demanding occupations. Critical physical tasks provide basis for the next overall research process step, developing physical task simulations to link to predictive physical fitness tests and training guidance.