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Journal articles on the topic 'Air traffic data'
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Desimoni, Federico, Sergio Ilarri, Laura Po, Federica Rollo, and Raquel Trillo-Lado. "Semantic Traffic Sensor Data: The TRAFAIR Experience." Applied Sciences 10, no. 17 (August 25, 2020): 5882. http://dx.doi.org/10.3390/app10175882.
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Modern cities face pressing problems with transportation systems including, but not limited to, traffic congestion, safety, health, and pollution. To tackle them, public administrations have implemented roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. In the case of traffic sensor data not only the real-time data are essential, but also historical values need to be preserved and published. When real-time and historical data of smart cities become available, everyone can join an evidence-based debate on the city’s future evolution. The TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project seeks to understand how traffic affects urban air quality. The project develops a platform to provide real-time and predicted values on air quality in several cities in Europe, encompassing tasks such as the deployment of low-cost air quality sensors, data collection and integration, modeling and prediction, the publication of open data, and the development of applications for end-users and public administrations. This paper explicitly focuses on the modeling and semantic annotation of traffic data. We present the tools and techniques used in the project and validate our strategies for data modeling and its semantic enrichment over two cities: Modena (Italy) and Zaragoza (Spain). An experimental evaluation shows that our approach to publish Linked Data is effective.
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Manvelidze, A. B. "Air lines network modelling algorithm." Strategic decisions and risk management, no. 6 (February 13, 2018): 22–29. http://dx.doi.org/10.17747/2078-8886-2017-6-22-29.
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This analysis is dedicated to find out methods for setting of route networks where new aircraft can be effectively put into service. The conception of this analysis is based on the idea of so called connectivity principle for airports connected by passenger traffic with each other.For the passenger traffic analysis the author took passenger traffic data by federal districts starting from the Far East. Then consequently the data for Siberian, Ural, Wolga, Northwestern, Central, Southern and North Caucasian federal districts were analyzed. Passenger traffic to the Crimea was treated separately. Detailed specifications of passenger traffics were provided in order to determine the connections between airports both within federal districts and beyond them and with neighboring areas in western direction. Query of routes was done based on limitations for non-stop flight range and on minimum and maximum (for significant traffics) flight frequencies.The analysis approach lets us concentrate attention on those airlines which at best fit for putting into service of chosen aircraft. Also this method permits to determine the routes with currently insufficient or low traffics but where there’s a definite growth potential. When analysis data are combined with traffic data and tariffs, then it becomes possible to determine the most profitable routes for introduction of new aircraft. Traffic volume, actual figures and forecast, consolidated characteristics of chosen airlines, list of airlines for further studies of efficiency and competitiveness of introduced aircraft are determined.
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Olive, Xavier. "traffic, a toolbox for processing and analysing air traffic data." Journal of Open Source Software 4, no. 39 (July 5, 2019): 1518. http://dx.doi.org/10.21105/joss.01518.
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Asirvadam, Tina Vimala, Sonali Rao S, and Balachander T. "Predicting Air Traffic Density in an Air Traffic Control Sector." ECS Transactions 107, no. 1 (April 24, 2022): 5037–45. http://dx.doi.org/10.1149/10701.5037ecst.
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Air traffic over Indian skies continues to increase rapidly and due to this increased demand, efforts must be made to efficiently balance demand with capacity. Air traffic flow management is a concept that allows for better demand and capacity management. It helps airlines plan routes and schedule flights. The ability to estimate the volume of air traffic is hence a critical element in flow management. Determining traffic in an ATC sector necessitates a thorough examination of various hidden parameters. The prediction is carried out using machine learning algorithms, Recurrent Neural Network, and Long Short Term Memory that examine the data and find a pattern which then anticipates the traffic in the sector at any given moment in the near future. Given the real-time data and experimental findings from this study, it is clear that Long Short Term Memory provides a clearer indicator of the study's goal.
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Duley, Jacqueline A., Scott M. Galster, and Raja Parasuraman. "Information Manager for Determining Data Presentation Preferences in Future Enroute Air Traffic Management." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 1 (October 1998): 47–51. http://dx.doi.org/10.1177/154193129804200112.
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One proposed vision of the future National Airspace System (NAS) involves a change in philosophy from that of air traffic control to one of air traffic management, i.e. Free Flight. In order to accommodate this philosophy change, new technologies will be implemented to assist the air traffic manager (today's air traffic controller) in decision making. When enhancing the system we must also consider the interface between the air traffic manager and this new system and its corresponding new philosophy. To better determine the design of such an interface we must first understand the information needs of the air traffic manager. The present study investigated the information requirements of 58 enroute air traffic controllers. The controllers provided their preferences in presentation frequency as well as the importance of the information to be displayed. The results reveal the potential for adaptive automation as a form of information management.
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Dudás, Gábor, Lajos Boros, Viktor Pál, and Péter Pernyész. "Mapping cost distance using air traffic data." Journal of Maps 12, no. 4 (July 3, 2015): 695–700. http://dx.doi.org/10.1080/17445647.2015.1061463.
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Awan, Faraz Malik, Roberto Minerva, and Noel Crespi. "Improving Road Traffic Forecasting Using Air Pollution and Atmospheric Data: Experiments Based on LSTM Recurrent Neural Networks." Sensors 20, no. 13 (July 4, 2020): 3749. http://dx.doi.org/10.3390/s20133749.
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Traffic flow forecasting is one of the most important use cases related to smart cities. In addition to assisting traffic management authorities, traffic forecasting can help drivers to choose the best path to their destinations. Accurate traffic forecasting is a basic requirement for traffic management. We propose a traffic forecasting approach that utilizes air pollution and atmospheric parameters. Air pollution levels are often associated with traffic intensity, and much work is already available in which air pollution has been predicted using road traffic. However, to the best of our knowledge, an attempt to improve forecasting road traffic using air pollution and atmospheric parameters is not yet available in the literature. In our preliminary experiments, we found out the relation between traffic intensity, air pollution, and atmospheric parameters. Therefore, we believe that addition of air pollutants and atmospheric parameters can improve the traffic forecasting. Our method uses air pollution gases, including C O , N O , N O 2 , N O x , and O 3 . We chose these gases because they are associated with road traffic. Some atmospheric parameters, including pressure, temperature, wind direction, and wind speed have also been considered, as these parameters can play an important role in the dispersion of the above-mentioned gases. Data related to traffic flow, air pollution, and the atmosphere were collected from the open data portal of Madrid, Spain. The long short-term memory (LSTM) recurrent neural network (RNN) was used in this paper to perform traffic forecasting.
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Kharchenko, Volodymur, Ivan Ostroumov, Nataliia Kuzmenko, and Arkadiy Larionov. "Airplane positioning using airborne collision avoidance system data." E3S Web of Conferences 164 (2020): 03050. http://dx.doi.org/10.1051/e3sconf/202016403050.
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Mid-air collision is an important problem of modern air transport system. Development of Airborne Collision Avoidance System (ACAS) is grounded on safety criteria in order to support air traffic capacity and equipment. In research, we study the possibility and performance of airplane positioning by data accumulated in ACAS. ACAS surveillance equipment supports accurate range and poor angular measurements of airspace user’s data. An approach is based on a fusion of surveillance data with airplanes locations obtained from decoded Automatic Depended Surveillance-Broadcast messages. Performance of positioning approach is considered in more detail. An error of positioning in the horizontal plane is estimated in relation with uncertainty of airspace users’ location. Numerical demonstration with a live air traffic data indicates poor positioning accuracy in comparison with primary positioning system on-board of airplane and accuracy dependence from geometry and capacity of air traffic.
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Majumdar, Arnab, Washington Y. Ochieng, Gérard McAuley, Jean Michel Lenzi, and Catalin Lepadatu. "The Factors Affecting Airspace Capacity in Europe: A Cross-Sectional Time-Series Analysis Using Simulated Controller Workload Data." Journal of Navigation 57, no. 3 (August 24, 2004): 385–405. http://dx.doi.org/10.1017/s0373463304002863.
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Air traffic in Europe is increasing at a rapid rate and traffic patterns no longer display pronounced daily peaks but instead exhibit peak spreading. Airspace capacity planning can no longer be for the peak period but must consider the whole day. En route airspace capacity in the high density European air traffic network is determined by controller workload. Controller workload is primarily affected by the features of the air traffic and ATC sector. This paper considers the air traffic and ATC sector factors that affect controller workload throughout the whole day. A simulation study using the widely used Reorganized ATC Mathematical Simulator (RAMS) model of air traffic controller workload is conducted for the Central European Air Traffic Services (CEATS) Upper Area Control Centre region of Europe. A cross-sectional time series analysis of the simulation output is conducted with corrections for temporal autocorrelation in the data. The results indicate that a subset of traffic and sector variables and their parameter estimates can be used to predict controller workload in any sector of the CEATS region in any given hour.
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Dekoninck, Luc, and Marcel Severijnen. "Correlating Traffic Data, Spectral Noise and Air Pollution Measurements: Retrospective Analysis of Simultaneous Measurements near a Highway in The Netherlands." Atmosphere 13, no. 5 (May 5, 2022): 740. http://dx.doi.org/10.3390/atmos13050740.
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Road traffic simultaneously emits noise and air pollution. This relation is primarily assessed by comparing A-weighted noise levels (LAeq) and various air pollutants. However, despite the common local traffic source, LAeq and the various sets of air pollution show a lower correlation than expected. Prior work, using simultaneous mobile noise and air pollution measurements, shows that the spectral content of the noise explains the complex and highly nonlinear relation between noise and air pollution significantly better. The spectral content distinguishes between traffic volume and traffic dynamics, two relevant modifiers explaining both the variability in noise and air pollution emissions of the local traffic flow. In May 2011, the environmental agency in the Netherlands performed noise and air pollutant measurements near a major highway and included spectral noise. In the resulting report, the analysis of the traffic, the noise and a wide set of air pollutants only showed a strong correlation between noise and NO. In this work, this dataset is re-evaluated using the noise-related covariates, engine noise and cruising noise, defined in prior work. The modeling approach proves valid for most of the measured air pollutants except for the large PM fractions. Conclusion: the prior established methodology explains the complex interaction between traffic dynamics, noise emission and air pollution emissions for a wide variety of air pollutants. The applicability of the ‘noise-as-a-traffic-proxy’ approach is extended.
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Hasabi, Rafif, Robert Kurniawan, Sugiarto Sugiarto, Ribut Nurul Tri Wahyuni, and Erna Nurmawati. "Urban traffic congestion and its association with gas station density: insights from Google Maps data." Indonesian Journal of Electrical Engineering and Computer Science 35, no. 3 (September 1, 2024): 1618. http://dx.doi.org/10.11591/ijeecs.v35.i3.pp1618-1626.
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Analyzing air pollution caused by traffic conditions requires appropriate indicators. Currently, air pollution indicators are approximated by the number of vehicles and gas station density. However, this approach cannot provide information at a smaller level. This study aims to identify traffic congestion distribution from Google Maps data as an alternative air pollution indicator at smaller level using map digitization method. In addition, this study examines its relationship with the existing indicator called gas station density. The results show that the digitization method can map the traffic congestion distribution where most areas in West, North, and Central Jakarta are classified as high traffic. In addition, this study found that there is a strong and significant relationship of 0.58277 between traffic congestion distribution and gas station density. Thus, traffic congestion distribution and gas station density data from Google Maps can be used as an indicator of traffic-related air pollution, especially land transportation. Furthermore, this research is expected to serve as a basis for the government in determining mitigation strategies related to traffic congestion and the resulting emissions.
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Jurinić, Tea, Biljana Juričić, Bruno Antulov-Fantulin, and Kristina Samardžić. "Defining Terminal Airspace Air Traffic Complexity Indicators Based on Air Traffic Controller Tasks." Aerospace 11, no. 5 (May 6, 2024): 367. http://dx.doi.org/10.3390/aerospace11050367.
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This paper focuses on terminal air traffic complexity indicators. By thorough analysis of previous research, the benefits and limitations of the existing terminal complexity models are identified. According to these findings, a new approach for determining terminal air traffic complexity indicators is proposed which assumes that terminal complexity could be determined based on approach air traffic controller (ATCO) tasks. The comprehensive list of general approach ATCO tasks was defined using a literature review and observation of training exercises, forming the basis for subsequent expert group workshops which enabled the acquisition of ATCOs’ knowledge data. Through these workshops, new approach ATCO tasks were additionally identified, and terminal complexity indicators were defined with airspace and traffic parameters. These new tasks and indicators present a novelty in this field of research since they incorporate ATCOs’ knowledge as the data input and consider various traffic scenarios, all types of traffic, weather conditions, and off-nominal situations.
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Ribas, Valdenilson Ribeiro, Hugo André de Lima Martins, Gutemberg Guerra Amorim, Renata de Melo Guerra Ribas, Cláudia Ângela Vilela de Almeida, Valéria Ribeiro Ribas, Carlos Augusto Carvalho de Vasconcelos, Murilo Duarte Costa Lima, Everton Botelho Sougey, and Raul Manhães de Castro. "Air traffic control activity increases attention capacity in air traffic controllers." Dementia & Neuropsychologia 4, no. 3 (September 2010): 250–55. http://dx.doi.org/10.1590/s1980-57642010dn40300015.
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Abstract Air traffic controllers simultaneously develop complex and multiple tasks in the course of their activities. In this context, concern is raised over the high level of attention needed by these professionals which can ultimately be affected by stress and fatigue. Objectives: The objective of this study was to assess attention level in air traffic controllers (ATCo). Methods: 45 flight protection professionals were evaluated, comprising 30 ATCo, subdivided into ATCo with ten or more years in the profession (ATCo³10, n=15) and ATCo with less than ten years in the profession (ATCo <10, n=15) and 15 aeronautical information services operators (AIS), subdivided into AIS with ten years or more in the profession (AIS³10, n=8) and AIS with less than ten years in the profession (AIS <10, n=7), who were included as the control group. The digit symbol, d2 (the individual marks the letter d on a specific form containing 14 lines with 47 letters in each, maintaining focus on letter d followed by two dashes), forward digit span, backward digit span and PASAT (paced auditory serial addition test) attention tests were used. Kruskal-Wallis was used and data expressed as Median (Minimum and Maximum) with p<0.05. Results: The ATCo³10 presented greater focus of attention, sustained attention, mental manipulation and resistance to interference capacity compared to the AIS³10. Comparison of ATCo³10 to the AIS<10 showed they presented only greater resistance to interference, and when compared to the ATCo<10 presented lower focus. Conclusions: The air traffic control activity after ten years may be associated with a high level of attention.
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Xiang, Zheng, Wei Jun Pan, and Yu Tang. "Application of Controller Pilot Data Link Communication in the Training for Air Traffic Controller." Advanced Materials Research 616-618 (December 2012): 2162–65. http://dx.doi.org/10.4028/www.scientific.net/amr.616-618.2162.
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The application of Controller Pilot Data Link Communication (CPDLC) in the training for air traffic controller is investigated. CPDLC is a data link application that allows for the direct exchange of text-based messages between a controller and a pilot. It greatly improves communication capabilities compared to traditional voice communication, in terms of reducing communication errors and pilot workload, improving the efficiency of airspace management and providing economic benefits. As traffic volume in the airspace becomes saturated, it is necessary to adopt CPDLC as the primary communication method and air traffic controllers should be trained accordingly. In the presented work, the features of CPDLC are introduced as well as the structure of CPDLC system is illustrated, and a novel framework for training air traffic controller with CPDLC system is proposed. It is seen that air traffic controller can be trained with lower workload, fewer mistakes and more flexibility using CPDLC system.
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Aggoune-Mtalaa, Wassila, and Mohamed Laib. "Analyzing Air Pollution and Traffic Data in Urban Areas in Luxembourg." Smart Cities 6, no. 2 (March 12, 2023): 929–43. http://dx.doi.org/10.3390/smartcities6020045.
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Monitoring air quality is gaining popularity in the research community since it can help policymakers make the right decisions for mitigating the negative effects of the ever-increasing pollution in cities. One of the significant sources of air pollution in urban areas is road transport. Assessing and understanding the relationship between urban traffic and local pollutants is crucial to maintaining sustainable urban mobility. This paper presents an exploratory data analysis of air pollution and traffic in some cities in Luxembourg. Furthermore, we studied the link that several pollutants have with other parameters, such as temperature and humidity. The paper also focuses on traffic and offers more insights for sustainable urban mobility.
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Gomez Depoorter, Dirk, and Wolfgang Kellerer. "Designing the Air–Ground Data Links for Future Air Traffic Control Communications." IEEE Transactions on Aerospace and Electronic Systems 55, no. 1 (February 2019): 135–46. http://dx.doi.org/10.1109/taes.2018.2849178.
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Zhang, Zhaoyue, An Zhang, Cong Sun, Shuaida Xiang, and Shanmei Li. "Data-Driven Analysis of the Chaotic Characteristics of Air Traffic Flow." Journal of Advanced Transportation 2020 (September 18, 2020): 1–17. http://dx.doi.org/10.1155/2020/8830731.
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Understanding the chaos of air traffic flow is significant to the achievement of advanced air traffic management, and trajectory data are the basic material for studying the chaotic characteristics. However, at present, there are two main obstacles to this task, namely, large amounts of noise in the measured data and the tedium of existing data processing methods. This paper improves the incorrect trajectory processing method based on ADS-B trajectory data and proposes a method by which to quickly extract the traffic flow through a certain waypoint. Currently, the commonly used theoretical analysis tools for nonlinear complex systems include the classical nonlinear dynamics analysis method and the newly developed complex network-based analysis method. The latter is currently in an exploratory stage because it has just been introduced into the study of air traffic flow. From these two perspectives, the chaotic characteristics of air traffic flow are studied in the present work. From the perspective of nonlinear dynamics, the improved C-C method is used to calculate the reliability parameters, namely, the time delay τ and embedding dimension m, of phase-space reconstruction, and the maximum Lyapunov index is calculated by using the small data volume method to prove the existence of chaos in the system. From the perspective of complex networks, the construction of a visibility graph and horizontal visibility graph is used to prove the existence of chaos in the system, and the goodness-of-fit parameters of the degree distributions of two fitting methods under different time scales are evaluated, which provides support for the air traffic flow theory.
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Han, Shah, and Lee. "Holographic Mixed Reality System for Air Traffic Control and Management." Applied Sciences 9, no. 16 (August 15, 2019): 3370. http://dx.doi.org/10.3390/app9163370.
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Based on a long-term prediction by the International Civil Aviation Organization indicating steady increases in air traffic demand throughout the world, the workloads of air traffic controllers are expected to continuously increase. Air traffic control and management (ATC/M) includes the processing of various unstructured composite data along with the real-time visualization of aircraft data. To prepare for future air traffic, research and development intended to effectively present various complex navigation data to air traffic controllers is necessary. This paper presents a mixed reality-based air traffic control system for the improvement of and support for air traffic controllers’ workflow using mixed reality technology that is effective for the delivery of information such as complex navigation data. The existing control systems involve difficulties in information access and interpretation. Therefore, taking notice of the necessity for the integration of air traffic control systems, this study presents the mixed reality (MR) system, which is a new approach, that enables the control of air traffic in interactive environments. This system is provided in a form usable in actual operational environments with a head-mounted see-through display installed with a controller to enable more structured work support. In addition, since this system can be controlled first-hand by air traffic controllers, it provides a new experience through improved work efficiency and productivity.
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Zhang, Yan, and Jun Zhang. "A Hybrid Model of Neural Network and Grey Theory for Air Traffic Passenger Volume Forecasting." Key Engineering Materials 439-440 (June 2010): 818–22. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.818.
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Chinese air traffic passenger volumes have experienced phenomenal growth during the past years. The air traffic volume prediction plays a key role in air traffic flow management system. This paper develops a hybrid model of Neural and Grey Theory for air traffic passenger volume forecasting. The Grey theory is adopted to fit the air traffic data patterns and make the data a higher regularity, and Radical basis function is combined to raise the forecasting accuracy. The model is tested with the Chinese civil aviation passenger volume data from 1998 to 2007 and the result shows that the model is feasible for practical implementations.
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WENDT, JAN A., and DARIUSZ JACEK OLSZEWSKI-STRZYŻOWSKI. "Changes in air tourism to Tunisia in 2009–2018." Baltic Journal of Health and Physical Activity 12, Special Issue 1 (November 30, 2020): 158–66. http://dx.doi.org/10.29359/bjhpa.12.spec.iss1.17.
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Background: T he subject of this study is an analysis of the changes of tourist air traffic in Tunisia between 2009 and 2018. During this time, Tunisia saw political changes and worldwide-reported coverage of terrorist attacks on tourists (2014–2015). The aim of this study was to attempt to determine the extent to which the Tunisian Revolution and terrorist attacks have had a negative impact on the decline in the tourist traffic, and to assess the rate of return of the tourist traffic and income in this sector to the levels from before the Revolution. Material and methods: The main source of statistical data for Tunisian airports are documents List of the busiest airports in Africa and Trafic Mondial / World Traffic, and data collected from individual airports for the relevant years. The main problem in the analysis and correlation was the access to reliable data on the volume of tourist traffic, and in the case of some airports, data presenting the volume of passenger traffic. Data from the Statistical Office of Tunisia were used to identify and analyse changes in revenues. Results: Data for 2009–2018 clearly show a decrease in the number of all passengers arriving in Tunisia by air travel. Conclusions: R esearch suggests that the decline in the number of tourists as a result of political changes and terrorist attacks has been characterised by different dynamics. Political events have a lower impact on the decrease in the number of tourists and have an effect over a longer period. It seems that after a period of a twofold decrease in the number of tourists – firstly, because of the revolution, and secondly, because of attacks after 2016, Tunisia has entered a period of prosperity in tourism, as evidenced by data for 2017–2018. However, after the record-breaking year 2019, the first quarter of 2020 began under the sign of the Coronavirus pandemic, and tourism around the world is facing a period of stagnation.
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Ulfah, Nurul, and Elisabeth Endang Prokosawati. "Analisis Stress Kerja Petugas Air Traffic Controller Terhadap Tingkat Keselamatan Penerbangan di Bandar udara Sultan Muhammad salahuddin Bima, Nusa Tenggara Barat." Reslaj : Religion Education Social Laa Roiba Journal 4, no. 5 (March 7, 2022): 1291–97. http://dx.doi.org/10.47467/reslaj.v4i5.1109.
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An air traffic controller (ATC) is one of the jobs with the highest job demands. The safety of the soul is a mental burden that must be borne by each air traffic controller officer. Sultan Muhammad Salahuddin Bima Airport is in charge of providing air traffic guidance services. Guide the pilot from the aircraft's start in the apron, taxi, takeoff, and landing. This study aims to find out if there is work Stresss felt by air traffic controller officers and to gauge the level of flight safety at Sultan Muhammad Salahuddin Bima Airport.
This research uses qualitative methods with descriptive qualitative research types. Data collection for this study was conducted at Perum LPPNPI AirNav Indonesia Bima Auxiliary Branch. The study used data from documentation, live observations, and interviews conducted with senior air traffic controllers and junior air traffic controllers. Data analysis techniques use data organizing, data management, data verification and interpretation, and inference.
The results of this study showed that there was work stress felt by the air traffic controller officer of Bima Auxiliary Branch. The distance between the Stresss felt in doing the work by the air traffic controller officer is very clearly visible. This is in view of the surrounding environmental conditions that are directly adjacent to the livelihood area of the surrounding population (pond). In addition, Sultan Salahuddin Bima Airport is undergoing reconstruction so that many shocks are felt while inside the tower due to heavy equipment and passing trucks. The results of this study also showed that the level of flight safety at Sultan Muhammad Salahuddin Bima Airport is relatively safe, considering the rare occurrence of accidents and serious incidents.
Keywords : air traffic controller, work Stress, flight safety, Sultan Muhammad Salahuddin Bima Airport.
Air Traffic Controller (ATC) merupakan salah satu pekerjaan yang memiliki tuntutan kerja tinggi. Tanggung jawab terhadap keselamatan jiwa merupakan beban mental tersendiri yang harus dipikul oleh tiap-tiap petugas Air Traffic Controller. Air Traffic Controller Bandar Udara Sultan Muhammad Salahuddin Bima bertugas memberikan pelayanan pemanduan lalu lintas udara. Memandu pilot mulai dari pesawat start di apron, taxi, take off sampai landing. Penelitian ini bertujuan untuk mengetahui apakah terdapat stress kerja yang dirasakan oleh petugas Air Traffic Controller dan untuk mengetahui tinggkat keselamatan penerbangan di Bandar Udara Sultan Muhammad Salahuddin Bima.
Penelitian ini menggunakan metode kualitatif dengan jenis penelitian kualitatif deskriptif. Pengumpulan data pada penelitian ini dilakukan di Perum LPPNPI AirNav Indonesia Cabang Pembantu Bima. Penelitian ini mengambil data dari dokumentasi, observasi secara langsung, dan wawancara yang dilakukan bersama Senior Air Traffic Controller dan Junior Air traffic Controller. Teknik analisis data menggunakan pengorganisasian data, pengelolaan data, verifikasi dan penafsiran data, dan pengambian kesimpulan.
Hasil dari penelitian ini menunjukkan bahwa terdapat stress kerja yang dirasakan oleh petugas Air Traffic Controller Cabang Pembantu Bima. Stress keja yang dirasakan dalam melakukan pekerjaan oleh petugas Air Traffic Controller sangat terlihat jelas. Hal ini ditinjau dari kondisi lingkungan sekitar yang berbatasan langsung dengan kawasan mata pencaharian penduduk sekitar (tambak) selain itu juga Bandara Sultan Salahuddin Bima sedang melakukan rekonstruksi sehingga banyak guncangan-guncangan yang dirasakan saat berada di dalam tower karena alat berat maupun truk yang lewat. Hasil penelitian ini juga menunjukkan bahwa tingkat keselamatan penerbangan di Bandar Udara Sultan Muhammad Salahuddin Bima tergolong aman, mengingat jarang terjadinya accident dan serious insident.
Kata Kunci : Air Traffic Controller, Stress kerja, keselamatan penerbangan, dan Bandar Udara Sultan Muhammad Salahuddin Bima.
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Forrester, David A., and Garfield C. Dean. "Improvement of Meteorological Data for Air Traffic Management Purposes." Air Traffic Control Quarterly 2, no. 2 (April 1994): 85–101. http://dx.doi.org/10.2514/atcq.2.2.85.
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Diao, Xudong, and Shan Lu. "Optimization Approach to Data-Driven Air Traffic Flow Management." Transportation Research Record: Journal of the Transportation Research Board 2676, no. 3 (October 23, 2021): 398–404. http://dx.doi.org/10.1177/03611981211051621.
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An integer programming model for data-driven air traffic flow management that extends the state-of-the-art approach of Bertsimas and Patterson was developed. The major contribution of our model is that the structure of the route set is modified to improve the flexibility of rerouting operations. To improve the computational performance, we employed reformulation-linearization techniques to turn the model into a linear integer programming model, and we propose two sets of valid inequalities to speed up the computation process. The computational results indicated that the optimal strategies for flights can be efficiently obtained for large-scale instances.
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Klauza, Marcin, Piotr Czekalski, and Krzysztof Tokarz. "Air Traffic Data Integration using the Semantic Web Approach." Athens Journal of Τechnology & Engineering 2, no. 2 (May 31, 2015): 115–28. http://dx.doi.org/10.30958/ajte.2-2-4.
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Miura, Akira, Hiroyuki Morikawa, and Moriyuki Mizumachi. "Air traffic control data tables for conflict alert system." Electronics and Communications in Japan (Part I: Communications) 79, no. 6 (1996): 101–13. http://dx.doi.org/10.1002/ecja.4410790611.
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Cruz, André Luiz Macedo da. "THE TRANSFORMATION OF AIR TRAFFIC MANAGEMENT WITH BIG DATA." Revista ft 25, no. 93 (December 1, 2020): 58–59. http://dx.doi.org/10.69849/revistaft/cl10202012010958.
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Chmura, Wojciech, and Marek Malarski. "Operational Errors in Air Traffic." Journal of Konbin 6, no. 3 (January 1, 2008): 191–98. http://dx.doi.org/10.2478/v10040-008-0066-y.
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Operational Errors in Air Traffic The obligatory value representing the allowable number of events in air traffic (in particular accidents), calculated upon historical data known as Target Level of Safety - TLS, is at present valid only for accidents and equals 1,55*10-8 an accident per one flight hour. This value, unless the previously calculated TLS, would be reliable and this equation itself might be useful to monitor the current level of safety (CLS) by putting into it the current performance characteristics of a staff.
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Ratcliffe, S. "Automation in Air Traffic Management." Journal of Navigation 38, no. 3 (September 1985): 405–12. http://dx.doi.org/10.1017/s0373463300032768.
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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.
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Ozcan, Ismail Cagri. "The effect of air cargo traffic on regional job creation in Turkey." Journal of Transport Literature 8, no. 4 (October 2014): 146–63. http://dx.doi.org/10.1590/2238-1031.jtl.v8n4a6.
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While there is a large body of literature on air passenger traffic's impact on local employment, the interaction between air cargo traffic and local employment remains relatively untouched. This paper tries to fill in the gap by analyzing the impact of air cargo traffic on local employment in 20 Turkish provinces using Census 2000 data. The results of 2-stage least squares estimations show that air cargo traffic stimulates employment in finance, insurance, real estate and business services and increases the total number of administrative and managerial workers and the total number of clerical and related workers while it tends to reduce employment in agriculture, hunting, forestry and fishing activities and the total number of agricultural, animal husbandry, forestry workers, fishermen and hunters.
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Ren, Jie, Shiru Qu, Lili Wang, Yu Wang, Tingting Lu, and Lijing Ma. "Research on en route capacity evaluation model based on aircraft trajectory data." Electronic Research Archive 31, no. 3 (2023): 1673–90. http://dx.doi.org/10.3934/era.2023087.
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<abstract> <p>For the sake of refined assessment of airspace operation status, improvement of the en route air traffic management performance, and alleviation of the imbalance of demand-capacity and airspace congestion, an en route accessible capacity evaluation model (based on aircraft trajectory data) is proposed in this paper. Firstly, from the perspective of flux, the en route capacity is defined and expanded from a two-dimensional concept to a three-dimensional concept. Secondly, based on the indicators of spatial flow and instantaneous density, an evaluation model of en route capacity is given. Finally, a case study is performed to validate the applicability and feasibility of the model. Results show that the en route accessible capacity, instantaneous density, and spatial flow can describe the temporal and spatial distribution of air traffic flow more precisely, as compared to the conventional indicators, such as route capacity, density, and flow. The proposed model envisages three innovations: (ⅰ) the definition of airspace accessible capacity with reference to capacity of road traffic, (ⅱ) the computation model for flux-based airspace accessible capacity and en route accessible capacity, and (ⅲ) two indicators of en route characteristics named instantaneous density and spatial flow are introduced for evaluating the micro-state of the en route. Furthermore, because of the capacity depiction of the spatial and temporal distribution of air traffic congestion within an airspace unit, this model can also help air traffic controllers balance the distribution of traffic flow density, reduce the utilization rate of horizontal airspace, and resolve flight conflicts on air routes in advance.</p> </abstract>
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Li, Jiannan, Zhaoguo Wang, Bocong Yuan, Haixuan Liang, and Wenqi Liang. "The Episode of National Lockdown in the Pandemic: Air Traffic Restriction as the Control Strategy and Its Impact on Existing Cases and Recovery Rate of Novel Coronavirus Disease in Megacities of China." Disaster Medicine and Public Health Preparedness 14, no. 5 (August 12, 2020): e19-e23. http://dx.doi.org/10.1017/dmp.2020.294.
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ABSTRACTObjective:The effectiveness of air traffic restriction in containing the spread of infectious diseases is full of controversy in prior literature. In January 2020, the Civil Aviation Administration of China (CAAC) announced air traffic restriction in response to the coronavirus disease (COVID-19) pandemic. This study’s aim is to empirically examine the policy effectiveness.Method:The data from 2 third-party platforms are used in this investigation. The COVID-19 data from the platform DXY and the air traffic data from Airsavvi are matched to each other. The robust panel regression with controlling city effect and time effect is conducted.Results:The curvilinear relations are found between the air traffic restriction and the existing cases, and the recovery rate (quadratic term = 9.006 and −0.967, respectively). As the strength of air traffic restriction is growing, the negative effect (-8.146) of air traffic restriction on the existing cases and the positive effect (0.961) of air traffic restriction on the recovery rate, respectively, begin decreasing.Conclusion:On the macro level, the air traffic restriction may help alleviate the growth of existing cases and help raise the recovery rate of COVID-19 in megacities of China, but both these effects will marginally recede as the restriction strength is intensifying.
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Berry, Peter. "North Atlantic air traffic control." Aeronautical Journal 94, no. 939 (November 1990): 318–23. http://dx.doi.org/10.1017/s0001924000023204.
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In 1989, more than 29 million passengers were flown across the North Atlantic Ocean in 167 000 scheduled and non-scheduled flights. At peak times during the Summer months, a trans-Atlantic flight was crossing the Shanwick Oceanic Control boundary every minute and more than 200 flights were reporting between 10 and 50 degrees West. Traffic counts exceeded 750 flights a day.The following account describes the more recent improvements to North Atlantic air traffic control, the early introduction of computers to the task, with their on-line data interchange between Oceanic Control Centres and the current computer supported services provided by the Shanwick and Gander Oceanic Area Control Centres.
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Cao, Yang, Hao Wu, Hongbin Wang, Duanyang Liu, and Shuqi Yan. "Potential Effect of Air Pollution on the Urban Traffic Vitality: A Case Study of Nanjing, China." Atmosphere 13, no. 10 (September 29, 2022): 1592. http://dx.doi.org/10.3390/atmos13101592.
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Studies on the vitality of urban residents’ daily commuting and air pollution are scarce. Based on the cell phone mobile signaling data, urban air quality observation data, and urban transportation infrastructure environment data of Nanjing in 2019, and through the panel regression model and the standard deviation ellipse analysis (SDE) to measure the impact of air pollution on residents’ daily traffic vitality, we construct the survey panel matrix data system with streets as spatial units. Through SDE and panel regression model analysis, we measured the restraining effect of air pollution on the traffic vitality. The scope of the traffic vitality area SDE was found to shrink as the air quality index (AQI) increases. The study found three main characteristics: (1) Under different transportation models and different location conditions, there are obvious differences in traffic vitality. The entire city presents a trend of “northeast-southwest” axial expansion in the spatial pattern of the traffic vitality. Compared with the urban core area, the traffic vitality of residents in the north-south areas of Nanjing’s periphery has declined significantly. (2) The inhibitory effect of air pollution on public traffic vitality and self-driving traffic vitality are differences. Approximately one-tenth of traffic activities may be inhibited by air pollution. The weakening of traffic vitality greatly reduces the city’s ability to attract and gather people, materials, and resources. (3) The inhibitory effect of air pollution on traffic vitality is heterogeneous under different transportation infrastructure environments. The higher the public transportation station density and public transportation frequency of the street, the more obvious the suppression effect of air pollution. The higher the parking density, station accessibility, road intersections density, and transportation facility diversity, the lower the suppression effect of air pollution. This study elucidates the relationship among air pollution, the transportation infrastructure environment, and the traffic vitality, and provides significant guidelines for optimizing the organization of elements in the transportation infrastructure environment, thereby mitigating the inhibitory effect of air pollution on traffic vitality.
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Susetyadi, Ari, and Yati Nurhayati. "Kebutuhan Personel Air Traffic Controller (ATC) Di Bandara Sultan Mahmud Badaruddin II Palembang." Warta Penelitian Perhubungan 24, no. 5 (May 14, 2019): 474. http://dx.doi.org/10.25104/warlit.v24i5.1027.
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Assessment of personnel needs of air traffic controllers (ATC) at the Sultan Mahmud Airport Badaruddin II Palembang is to find out how many number of needs of air traffic controllers (ATC) at the Sultan Mahmud Airport Badaruddin II Palembang that has with standards / regulations by the !CAO to support flight operations in order to ensure flight safety. Assessment method was quantitative method with the decomposition of descriptive, exposure and explanation in detail based on the compilation of primary data and secondary data that have been processed. The results of the assessment show that air traffic controller (ATC) at the Sultan Mahmud Airport Badaruddin II Palembang is still not adequate, there is still lack of abaout 11 air traffic controller (ATC) personnel at the Sultan Mahmud Badaruddin II Palembang Airport.Keywords : air traffic controller (ATC), Sultan Mahmud Badaruddin II Palembang Airport Pengkajian tentang kebutuhan personel air traffic controller (ATC) di Bandara Sultan Mahmud Badaruddin II Palembang adalah untuk mengetahui bagaimana jumlah kebutuhan air traffic controller (ATC) di Bandara sultan Mahmud Badaruddin II Palembang apakah telah memenuhi standar/peraturan yang ditetapkan oleh ICAO untuk mendukung kegiatan operasi penerbangan dalam rangka menjamin keselamatan penerbangan. Metode pengkajian yang digunakan adalah metode kuantitatif dengan penguraian ( deskriptif), pemaparan dan penjelasan secara rind berdasarkan kompilasi data primer dan data sekunder yang telah diolah. Hasil pengkajian menunjukan personel air traffic controller (ATC) di Bandara sultan Mahmud Badaruddin II Palembang masih belum memadai, yakni masih terdapat kekurangan sekitar 11 personel air traffic controller (A TC) di Bandara sultan Mahmud Badaruddin II Palembang. Kata Kunci: air traffic controller (ATC),Bandara Sultan Mahmud Badaruddin II Palembang
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Bolić, Tatjana, Lorenzo Castelli, Andrea De Lorenzo, and Fulvio Vascotto. "Trajectory Clustering for Air Traffic Categorisation." Aerospace 9, no. 5 (April 21, 2022): 227. http://dx.doi.org/10.3390/aerospace9050227.
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Availability of different types of data and advances in data-driven techniques open the path to more detailed analyses of various phenomena. Here, we examine the insights that can be gained through the analysis of historical flight trajectories, using data mining techniques. The goal is to learn about usual (or nominal) choices airlines make in terms of routing, and their relation with aircraft types and operational flight costs. The clustering is applied to intra-European trajectories during one entire summer season, and a statistical test of independence is used to evaluate the relations between the variables of interest. Even though about half of all flights are less than 1000 km long, and mostly operated by one airline, along one trajectory, the analysis shows that, for longer flights, there exists a clear relation between the trajectory clusters and the operating airlines (in about 49% of city pairs) and/or the aircraft types (30%), and/or the flight costs (45%).
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Ort, Markus. "Displays in air traffic control." Information Design Journal 11, no. 1 (September 26, 2003): 17–31. http://dx.doi.org/10.1075/idj.11.1.04ort.
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Commercial aviation is becoming more and more important these days. From year to year there is an accelerated increase in the density of air traffic. The resulting fast growth in the flow of data between controllers and the technical systems they use, as well as that between controller and pilot, calls for new means of communication and visualization of information and interaction with it. Revised concepts for air traffic control must be applied, to deal safely with the increasing volume of traffic in the future. The main focus must be on designing an appropriate interface to support the interaction between ground and cockpit, making the communication as efficient, convenient and secure as possible. This undoubtedly goes further than just making information accessible in a digital format. Despite the importance and complexity of the subject, interdisciplinary projects to achieve this were launched only recently. However, as time goes on, more ergonomics specialists, psychologists and designers are working in this field dominated by engineers and programmers. So far, only a few cooperative projects have been undertaken between information designers, interaction designers and air traffic control specialists to create new interface solutions. This is all the more surprising since the structuring and visualization of this immense flow of data, the mapping of dynamic processes and the search for new means of communication constitute a highly interesting field. There is a strong belief that only such cooperation can lead to a coherent product, if interfaces are to be developed which can unfold the potential of the new Datalink-technology. The project described in this article was undertaken at the Design Department of the University of Applied Sciences Cologne, in cooperation with engineers from the Berlin University of Technology/ Institute of Aeronautics and Astronautics/ Section Flight Guidance and Transportation and IT-specialists and air traffic controllers from Skyguide (Zürich and Geneva). After a brief summary of the general situation in air traffic control and the work that controllers do, my aim in this article is to present a feasible interface solution for the arrival/departure sector, one of the most crucial areas of air traffic control.
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Zuluaga-Gomez, Juan, Karel Veselý, Alexander Blatt, Petr Motlicek, Dietrich Klakow, Allan Tart, Igor Szöke, et al. "Automatic Call Sign Detection: Matching Air Surveillance Data with Air Traffic Spoken Communications." Proceedings 59, no. 1 (December 3, 2020): 14. http://dx.doi.org/10.3390/proceedings2020059014.
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Voice communication is the main channel to exchange information between pilots and Air-Traffic Controllers (ATCos). Recently, several projects have explored the employment of speech recognition technology to automatically extract spoken key information such as call signs, commands, and values, which can be used to reduce ATCos’ workload and increase performance and safety in Air-Traffic Control (ATC)-related activities. Nevertheless, the collection of ATC speech data is very demanding, expensive, and limited to the intrinsic speakers’ characteristics. As a solution, this paper presents ATCO2, a project that aims to develop a unique platform to collect, organize, and pre-process ATC data collected from air space. Initially, the data are gathered directly through publicly accessible radio frequency channels with VHF receivers and LiveATC, which can be considered as an “unlimited-source” of low-quality data. The ATCO2 project explores employing context information such as radar and air surveillance data (collected with ADS-B and Mode S) from the OpenSky Network (OSN) to correlate call signs automatically extracted from voice communication with those available from ADS-B channels, to eventually increase the overall call sign detection rates. More specifically, the timestamp and location of the spoken command (issued by the ATCo by voice) are extracted, and a query is sent to the OSN server to retrieve the call sign tags in ICAO format for the airplanes corresponding to the given area. Then, a word sequence provided by an automatic speech recognition system is fed into a Natural Language Processing (NLP) based module together with the set of call signs available from the ADS-B channels. The NLP module extracts the call sign, command, and command arguments from the spoken utterance.
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Ardhiani, Lusi Nur, Galuh Rita Kumala, and Nur Makie Perdana. "ANALISIS KUALITATIF PENERAPAN SITUATION AWARENESS PADA AKTIVITAS KERJA AIR TRAFFIC CONTROLLER (ATC)." SEURUNE: Jurnal Psikologi UNSYIAH 2, no. 1 (July 19, 2019): 16–32. http://dx.doi.org/10.24815/s-jpu.v2i1.13270.
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Berdasarkan fakta yang dirilis oleh Airport Council International (ACI), Indonesia memasuki peringkat ke-17 bandar udara dengan lalu lintas terpadat di dunia. Pengontrol lalu lintas udara atau air traffic controller (ATC) merupakan salah satu pihak yang paling berperan dalam mengatur kepadatan lalu lintas di jalur udara Indonesia. Penelitian ini bertujuan untuk mengetahui penerapan Situation Awareness (SA) pada aktivitas kerja sehari-hari air traffic controller di dunia penerbangan. Model yang digunakan dalam penelitian ini adalah studi kasus konklusif deskriptif. Data dikumpulkan melalui wawancara terhadap delapan orang yang berprofesi sebagai air traffic controller (ATC) dari Air-Nav Indonesia maupun TNI-AU. Hasil verbatim wawancara kemudian dikoding dan diinterpretasi serta dianalisis dengan menggunakan teori serta data-data dari penelitian pendahulu. Penelitian ini menghasilkan data deskripsi perilaku maupun situasi yang teridentifikasi sebagai aspek maupun indikator penting dalam penerapan tiga level situation awareness pada aktivitas kerja air traffic controller (ATC). Aspek-aspek dan indikator-indikator tersebut kemudian dikelompokkan pada tabel yang terbagi dalam tiga level Situation Awareness. Data yang dihasilkan dapat digunakan untuk mendesain alat ukur, pelatihan, penelitian, maupun evaluasi guna meningkatkan kewaspadaan air traffic controller.Kata kunci: Situation Awareness, Tiga level, Air Traffic Control
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Senarathna, Mahesh, Sajith Priyankara, Rohan Jayaratne, Rohan Weerasooriya, Lidia Morawska, and Gayan Bowatte. "Measuring TrafficRelated Air Pollution Using Smart Sensors In Sri Lanka: Before And During A New Traffic Plan." GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY 15, no. 3 (October 4, 2022): 27–36. http://dx.doi.org/10.24057/2071-9388-2022-011.
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Motor vehicle emissions are the primary air pollution source in cities worldwide. Changes in traffic flow in a city can drastically change overall levels of air pollution. The level of air pollution may vary significantly in some street segments compared to others, and a small number of stationary ambient air pollution monitors may not capture this variation. This study aimed to evaluate air pollution before and during a new traffic plan established in March 2019 in the city of Kandy, Sri Lanka, using smart sensor technology. Street level air pollution data (PM2.5 and NO2 ) was acquired using a mobile air quality sensor unit before and during the implementation of the new traffic plan. The sensor unit was mounted on a police traffic motorcycle that travelled through the city four times per day. Air pollution in selected road segments was compared before and during the new traffic plan, and the trends at different times of the day were compared using data from a stationary smart sensor. Both PM2.5 and NO2 levels were well above the World Health Organization (WHO) 24-hour guidelines during the monitoring period, regardless of the traffic plan period. Most of the road segments had comparatively higher air pollution levels during compared to before the new traffic plan. For any given time (morning, midday, afternoon, evening), day of the week, and period (before or during the new traffic plan), the highest PM2.5 and NO2 concentrations were observed at the road segment from Girls High School to Kandy Railway Station. The mobile air pollution monitoring data provided evidence that the mean concentration of PM2.5 during the new traffic plan (116.7 µg m-3) was significantly higher than before the new traffic plan (92.3 µg m-3) (p < 0.007). Increasing spatial coverage can provide much better information on human exposure to air pollutants, which is essential to control traffic related air pollution. Before implementing a new traffic plan, careful planning and improvement of road network infrastructure could reduce air pollution in urban areas.
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Harada, Akinori, Tooru Ezaki, Tomoaki Wakayama, and Koichi Oka. "Air Traffic Efficiency Analysis of Airliner Scheduled Flights Using Collaborative Actions for Renovation of Air Traffic Systems Open Data." Journal of Advanced Transportation 2018 (June 7, 2018): 1–14. http://dx.doi.org/10.1155/2018/2734763.
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The increase in air traffic worldwide requires improvement of flight operational efficiency. This study aims to reveal the potential benefits, namely, savings on fuel consumption and flight time, which are expected for Japanese airspace, by statistically evaluating the operational efficiency defined by average differences of fuel consumption, flight time, and flight distance between the original and the optimized flight of domestic flights in Japan. The aircraft position and time data used in this study were obtained from Collaborative Actions for Renovation of Air Traffic Systems Open Data—the radar data released by the Japan Civil Aviation Bureau. Flight information, such as air data and fuel flow, is estimated by applying meteorological data and aircraft performance model to the position information of radar data. Each reconstructed trajectory is optimized in terms of flight fuel consumption and flight time with an assumed cost index (CI). Dynamic programming is used as the trajectory optimization method. The flight fuel consumption and flight time of the optimized flight are compared with the original values to evaluate the operational efficiency. Herein, approximately one-third of 1-day data, i.e., 1087 cases of four aircraft types, are analyzed with reasonable CI settings. Our research findings suggest that flight fuel consumption and flight distance can be saved by 312 kg and 19.7 km, respectively, on average for the object flights. Following a statistical comparison between the original and the optimized flights, it was observed that two types of features, namely, flying on a detoured path and flying with nonoptimal altitude and speed in the cruise phase, are major factors which deteriorate the total operational efficiency in terms of fuel consumption, flight time, and flight distance.
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Kong, Jin Feng, and Yu Wang. "A Method for Predicting Air Traffic Network Flow by Short-Term Probability." Applied Mechanics and Materials 713-715 (January 2015): 1500–1503. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.1500.
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The main task of air traffic management is making adjustments when traffic flow reaches to the maximum capacity of air traffic control. It aims to increase the use ratio of airport and airspace. Air traffic flow prediction is one important part of air traffic management. Usually, air traffic prediction is divided into deterministic flow prediction and probability prediction .We research on the probability prediction on the basis of deterministic flow prediction. By analyzing aircrafts’ experienced flight time distribution, giving experienced distribution function and computing method. The data analysis shows that the accuracy rate increased by 22%.
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Li, Shanmei, Zhaoyue Zhang, and Xiaochun Cheng. "Reliability Analysis of an Air Traffic Network: From Network Structure to Transport Function." Applied Sciences 10, no. 9 (May 1, 2020): 3168. http://dx.doi.org/10.3390/app10093168.
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To scientifically evaluate the reliability of air traffic networks, a definition of air traffic network reliability is proposed in this paper. Calculation models of the connectivity reliability, travel-time reliability, and capacity reliability of the air traffic network are constructed based on collected historical data, considering the current status and the predicted future evolution trends. Considering the randomness and fuzziness of factors affecting reliability, a comprehensive evaluation model of air traffic networks based on the uncertainty transformation model is established. Finally, the reliability of the US air traffic network is analyzed based on data published by the Transportation Statistics Bureau of the US Department of Transportation. The results show that the connectivity reliability is 0.4073, the capacity reliability is 0.8300, the travel-time reliability is 0.9180, and the overall reliability evaluated is “relatively reliable”. This indicates that although the US structural reliability is relatively low, the US air traffic management is very efficient, and the overall reliability is strong. The reliability in nonpeak hours is much higher than that in peak hours. The method can identify air traffic network reliability efficiently. The main factors affecting reliability can be found in the calculation process, and are beneficial for air traffic planning and management. The empirical analysis also reflects that the evaluation model based on the uncertainty transformation model can transform the quantitative data of network structure and traffic function into the qualitative language of reliability.
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TRIDIANDINI, KHANSA AULIA, Lina Rosmayanti, and Rini Sadiatmi. "THE EFFECT OF METEOROLOGICAL UNDERSTANDING OF AERODROME CONTROL TOWER PERSONNEL ON AIR TRAFFIC SERVICES AT MAKASSAR AIR TRAFFIC SERVICE CENTER." Jurnal Penelitian 7, no. 4 (January 20, 2023): 283–96. http://dx.doi.org/10.46491/jp.v7i4.1184.
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ATC personnel have an important role in the process of disseminating meteorological information for every phase of flight. The purpose of this study is to find out how much influence the meteorological understanding of ATC personnel has on air traffic services at Makassar Air Traffic Services Center. The quantitative research method is used by collecting data using questionnaires for ATC personnel and unstructured interviews with pilots at Sultan Hasanuddin International Airport in Makassar. The data processing used in this study is a correlation test, determination test, and simple linear regression. This study found the correlation coefficient is 0.79117 and the coefficient of determination is 62.6% which explains that understanding meteorology and air traffic services has a strong relationship and personnel ATC’s understanding of meteorology contributes 62.6% to air traffic services. Simple linear regression shows that for every additional 1 value of meteorological understanding, air traffic services will increase by 1.79111, the better the meteorological understanding of ATC personnel, the better the air traffic services at Makassar Air Traffic Services Center.
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Kim, Hyewook, and Keumjin Lee. "Air Traffic Prediction as a Video Prediction Problem Using Convolutional LSTM and Autoencoder." Aerospace 8, no. 10 (October 14, 2021): 301. http://dx.doi.org/10.3390/aerospace8100301.
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Accurate prediction of future air traffic situations is an essential task in many applications in air traffic management. This paper presents a new framework for predicting air traffic situations as a sequence of images from a deep learning perspective. An autoencoder with convolutional long short-term memory (ConvLSTM) is used, and a mixed loss function technique is proposed to generate better air traffic images than those obtained by using conventional L1 or L2 loss function. The feasibility of the proposed approach is demonstrated with real air traffic data.
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Kim, Hyewook, and Keumjin Lee. "Air Traffic Prediction as a Video Prediction Problem Using Convolutional LSTM and Autoencoder." Aerospace 8, no. 10 (October 14, 2021): 301. http://dx.doi.org/10.3390/aerospace8100301.
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Accurate prediction of future air traffic situations is an essential task in many applications in air traffic management. This paper presents a new framework for predicting air traffic situations as a sequence of images from a deep learning perspective. An autoencoder with convolutional long short-term memory (ConvLSTM) is used, and a mixed loss function technique is proposed to generate better air traffic images than those obtained by using conventional L1 or L2 loss function. The feasibility of the proposed approach is demonstrated with real air traffic data.
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Moon, Jucheol, Jin Gi Hong, and Tae-Won Park. "A Novel Method for Traffic Estimation and Air Quality Assessment in California." Sustainability 14, no. 15 (July 26, 2022): 9169. http://dx.doi.org/10.3390/su14159169.
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Motor vehicle traffic is recognized as one of the critical factors that causes air pollution; however, the relationship between traffic volume and air pollutant concentrations is unclear, especially at a local level. Traditional traffic volume monitoring systems collect traffic data through counting the number of vehicles, using either sensors or surveillance cameras, but they have clear limitations such as they can only monitor certain areas and specific occasions. To overcome such limitations, we introduce a method of monitoring traffic volume in the local area by collecting estimated travel times for virtual trips in Google Maps. We began collecting the data in January 2020; ironically, the COVID-19 pandemic provided a natural experimental environment of showing unusual trends in traffic volume and unexpected changes in air pollutants. We demonstrate monthly traffic volumes in urban areas and analyze the correlation of traffic volume with typical traffic-related air pollutants using the proposed traffic volume monitoring method.
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Susanti, Susanti. "Pengkajian Tingkat Kelelahan Petugas Air Traffic Controller (ATC) Dalam Meberikan Pelayanan Lalu Lintas PEnerbangan di Bandara Juanda Surabaya." WARTA ARDHIA 37, no. 3 (September 30, 2011): 211–22. http://dx.doi.org/10.25104/wa.v37i3.168.211-222.
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Assessment of Air Traffic Controllers (ATC) Fatigue Level in Providing flight Traffic services at Juanda International Airport Surabaya is to know how the description of Air traffic controller fatigue level in guiding services air traffic that impact on aviation safety. Assessment method used descriptive quantitative method by using Paired Sample T-Tesf method analysis, comparing the condition of fatigue before and after the ATC on duty, as well as exposure and detailed explanation based on the primary and secondary data compilation and the data have been processed. The assessment result shows that there are level of fatigue of Air Traffic Controller that significant, both of physical and psychological factors.
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Shankaramma, Supreetha H V, and Prof Nagaraj G. S. "Analysis of Air Traffic Management Models." International Journal of Innovative Technology and Exploring Engineering 11, no. 3 (January 30, 2022): 47–50. http://dx.doi.org/10.35940/ijitee.c9752.0111322.
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The high growth of air traffic flow has increased more bottleneck traffic issues in the air traffic management (ATM) system. The challenges between flight flow, air traffic control service and airspace are the major key parameters which support capability of domestic and international air transportation need to be looked by stakeholders. Many models are designed to incorporate to address the potential bottleneck issues of ATM. However, in these models’ analysis was not clearly presented. The proposed research review paper presents an analysis and insights of different models used in an air traffic management which includes, Big Data, Artificial Neural Network, Cloud Computing and Enterprise models.
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Zhu, Xiao Hui, and Zhi Kun Tang. "Optimization Model of Airplane Data Communication Network for Air Traffic Management." Applied Mechanics and Materials 505-506 (January 2014): 1084–88. http://dx.doi.org/10.4028/www.scientific.net/amm.505-506.1084.
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Aiming to better network facility deployment and reduce cost, this paper proposed an optimization model for air traffic management airplane data communication network based on multi-objective nonlinear programming to optimize the communication network trunk node and analyze user subnetwork access. Using multi-objective decomposition method, a computer-aided resolution model is presented and then simulations proved its effectiveness. This model has theoretical instruction on air traffic management plane data communication network design, and can offer reference for relate studies.
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Zhou, Rui, Shuang Qiu, Ming Li, Shuangjie Meng, and Qiang Zhang. "Short-Term Air Traffic Flow Prediction Based on CEEMD-LSTM of Bayesian Optimization and Differential Processing." Electronics 13, no. 10 (May 12, 2024): 1896. http://dx.doi.org/10.3390/electronics13101896.
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With the rapid development of China’s civil aviation, the flow of air traffic in terminal areas is also increasing. Short-term air traffic flow prediction is of great significance for the accurate implementation of air traffic flow management. To enhance the accuracy of short-term air traffic flow prediction, this paper proposes a short-term air traffic flow prediction model based on complementary ensemble empirical mode decomposition (CEEMD) and long short-term memory (LSTM) of the Bayesian optimization algorithm and data differential processing. Initially, the model performs CEEMD on the short-term air traffic flow series. Subsequently, to improve prediction accuracy, the data differencing is employed to stabilize the time series. Finally, the smoothed sequences are, respectively, input into the LSTM network model optimized by the Bayesian optimization algorithm for prediction. After data reconstruction, the final short-term flow prediction result is obtained. The model proposed in this paper is verified by using the data from Shanghai Pudong International Airport. The results show that the evaluation indexes of the prediction accuracy and fitting degree of the model, RMSE (Root Mean Square Error), MAE (Mean Absolute Error), and R2 (Coefficient of Determination), are 0.336, 0.239, and 97.535%, respectively. Compared to other classical time-series prediction models, the prediction accuracy is greatly improved, which can provide a useful reference for short-term air traffic flow prediction.