Готові списки джерел за темами / Airports Traffic control Mathematical models

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Добірка наукової літератури з теми "Airports Traffic control Mathematical models"

Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

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Статті в журналах з теми "Airports Traffic control Mathematical models"

1

Zhang, Honghai, Yan Xu, Lei Yang, and Hao Liu. "Macroscopic Model and Simulation Analysis of Air Traffic Flow in Airport Terminal Area." Discrete Dynamics in Nature and Society 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/741654.

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We focus on the spatiotemporal characteristics and their evolvement law of the air traffic flow in airport terminal area to provide scientific basis for optimizing flight control processes and alleviating severe air traffic conditions. Methods in this work combine mathematical derivation and simulation analysis. Based on cell transmission model the macroscopic models of arrival and departure air traffic flow in terminal area are established. Meanwhile, the interrelationship and influential factors of the three characteristic parameters as traffic flux, density, and velocity are presented. Then according to such models, the macro emergence of traffic flow evolution is emulated with the NetLogo simulation platform, and the correlativity of basic traffic flow parameters is deduced and verified by means of sensitivity analysis. The results suggest that there are remarkable relations among the three characteristic parameters of the air traffic flow in terminal area. Moreover, such relationships evolve distinctly with the flight procedures, control separations, and ATC strategies.
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2

Itoh, Eri, and Mihaela Mitici. "Queue-Based Modeling of the Aircraft Arrival Process at a Single Airport." Aerospace 6, no. 10 (September 20, 2019): 103. http://dx.doi.org/10.3390/aerospace6100103.

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This paper proposes data-driven queuing models and solutions to reduce arrival time delays originating from aircraft arrival processing bottlenecks at Tokyo International Airport. A data-driven analysis was conducted using two years of radar tracks and flight plans from 2016 and 2017. This analysis helps not only to understand the bottlenecks and operational strategies of air traffic controllers, but also to develop mathematical models to predict arrival delays resulting from increased, future aircraft traffic. The queue-based modeling approach suggests that one potential solution is to expand the realization of time-based operations, efficiently shifting from traffic flow control to time-based arrival management. Furthermore, the proposed approach estimates the most effective range of transition points, which is a key requirement for designing extended arrival management systems while offering automation support to air traffic controllers.
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3

Gopalakrishnan, Karthik, and Hamsa Balakrishnan. "Control and Optimization of Air Traffic Networks." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (May 3, 2021): 397–424. http://dx.doi.org/10.1146/annurev-control-070720-080844.

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The air transportation system connects the world through the transport of goods and people. However, operational inefficiencies such as flight delays and cancellations are prevalent, resulting in economic and environmental impacts. In the first part of this article, we review recent advances in using network analysis techniques to model the interdependencies observed in the air transportation system and to understand the role of airports in connecting populations, serving air traffic demand, and spreading delays. In the second part, we present some of our recent work on using operational data to build dynamical system models of air traffic delay networks. We show that Markov jump linear system models capture many of the salient characteristics of these networked systems. We illustrate how these models can be validated and then used to analyze system properties such as stability and to design optimal control strategies that limit the propagation of disruptions in air traffic networks.
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4

Dumanska, Ilona. "RESTORATION OF THE NETWORK OF LOCAL AIRPORTS OF UKRAINE: APPROACHES, INNOVATIVE MODELS AND ACTION STRATEGIES." Innovation and Sustainability, no. 1 (December 24, 2021): 20–27. http://dx.doi.org/10.31649/ins.2021.1.20.27.

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The state of aviation of Ukraine in the pre- and post-pandemic period is analyzed. The peculiarities of the development of the existing objects of the aviation infrastructure of Ukraine, including the network of local airports, are determined. Factors influencing the development of state infrastructure in the field of building a network of local airports have been identified. The approach to understanding of networks of local airports as function consisting of such elements as the airport is formed; airline; organization of air traffic and factors of influence: demand for air transportation; geographical resources; technical and technological limitations; economic and organizational requirements; legal requirements; security; ecology; inclusiveness of the territory. A critical and comparative analysis of the strategy of development of the network of local airports of Ukraine on the basis of innovative models: low-cost transportation and organization of hub centers. It was identified that the socio-economic conditions of Ukraine are not favorable for the active development of air transport and the formation of a significant amount of effective demand among the population of Ukraine. The expediency of shifting the vector of aviation infrastructure financing to the development of local airports on the basis of foreign experience in shaping public demand and motivating conditions for the development of air transport on the basis of state financial support, local government financing or attracting investment from private investors. The expediency of financing from the state budget of priority local airports by their classification according to the chosen strategy of aviation infrastructure development in Ukraine, which should be reflected in the mathematical model of decision-making functions.
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5

Badrinath, Sandeep, Hamsa Balakrishnan, Emily Joback, and Tom G. Reynolds. "Impact of Off-Block Time Uncertainty on the Control of Airport Surface Operations." Transportation Science 54, no. 4 (July 2020): 920–43. http://dx.doi.org/10.1287/trsc.2019.0957.

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Congestion at major airports worldwide results in increased taxi times, fuel burn, and emissions. Regulating the pushback of aircraft from their gates, also known as departure metering, is a promising approach to mitigating surface congestion. Departure metering algorithms require models of airport surface traffic and knowledge of when a flight would be to be ready for pushback, which is called the earliest off-block time (EOBT). While EOBTs are known to be inaccurate due to several reasons, there has been little prior research on characterizing EOBT uncertainty and its impact on departure metering. We present a new class of queuing network models for the airport surface that are capable of capturing congestion at multiple locations. We demonstrate our modeling approach using operational data from three major U.S. airports: Newark Liberty International Airport, Dallas/Fort Worth International Airport, and Charlotte Douglas International Airport. We analyze the current levels of uncertainty in the EOBT information published by the airlines and conduct a parametric analysis of the reduction in departure metering benefits due to errors in the EOBT information. Our analysis indicates that the current levels of EOBT uncertainty lead to a 50% reduction in benefits at some airports when compared with an ideal case with no EOBT uncertainty. Two approaches to departure metering are considered: the National Aeronautics and Space Administration’s Airspace Technology Demonstration-2 logic and a new optimal control approach. We show that our queuing network models can help design and evaluate both approaches and that the optimal control approach is more effective in accommodating EOBT uncertainty while maintaining runway utilization.
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6

Samà, Marcella, Andrea D’Ariano, Paolo D’Ariano, and Dario Pacciarelli. "Scheduling models for optimal aircraft traffic control at busy airports: Tardiness, priorities, equity and violations considerations." Omega 67 (March 2017): 81–98. http://dx.doi.org/10.1016/j.omega.2016.04.003.

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7

Vasyutina, A. A., V. V. Popov, A. I. Kondratyev, and A. L. Boran-Keshishyan. "Improvement of the vessel traffic control system for accident-free electronic navigation in the port area." Journal of Physics: Conference Series 2061, no. 1 (October 1, 2021): 012105. http://dx.doi.org/10.1088/1742-6596/2061/1/012105.

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Abstract The increase in the intensity of navigation leads to unsafe navigation, which necessitates the improvement of existing measures to ensure safe navigation using specific mathematical models and methods. The configuration of the mathematical model of the traffic flow of ships obtained in this study is realizable on modern computer technology and can be applied by embedding advanced ship traffic control systems, which is an object of the infrastructure of a modern seaport.
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8

Ma, Yinpu, and Kai Liu. "Intelligent Transportation Design Based on Iterative Learning." Journal of Mathematics 2022 (February 8, 2022): 1–7. http://dx.doi.org/10.1155/2022/5027412.

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Most of the existing traffic optimization control methods are based on accurate mathematical models. As an uncertain and complex system, the urban traffic system faces difficulty in accurately calibrating the model parameters. Therefore, the existing methods become very difficult in the actual application process. Based on the massive data contained in the urban traffic system and the repetitive characteristics of traffic flow, this paper proposes a hierarchical traffic signal control method for urban road network based on iterative learning control. The simulation results show that the algorithm can achieve better control effect and can solve the problem of urban traffic congestion more effectively than traditional traffic control methods.
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9

Suleimen, A. А., G. B. Kashaganova, G. B. Issayeva, B. R. Absatarova, and M. C. Ibraev. "OPTIMIZATION OF MANAGEMENT OF URBAN LIGHTS WITH THE USE OF NEURAL NETWORKS." BULLETIN 389, no. 1 (February 10, 2021): 14–17. http://dx.doi.org/10.32014/2021.2518-1467.2.

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Анотація:
One of the most pressing problems of large cities is the problem of traffic management of vehicles. The reason for this problem is an imperfect way to manage traffic flows. Traffic light regulation is of particular importance in traffic management. Most modern traffic light control systems operate at set time intervals and are not able to cope with the constantly changing situation on the road. A promising direction for solving this problem is to optimize the system using artificial neural networks. The advantage of neural networks is self-learning, which allows the system to adapt to the changing situation on the road. Despite numerous attempts, it has not yet been possible to obtain a high-quality mathematical model of urban traffic management. This model should determine the functional dependence of transport flow parameters on control parameters. Nowadays, traffic flows are regulated everywhere by means of traffic lights. If we can get a fairly accurate mathematical model of traffic flows, we can determine the optimal duration of the traffic signal phases to achieve the maximum capacity of the road network node. A fairly accurate mathematical model of traffic management that works in predictive mode will display an estimate of the optimal control parameters, as well as make correct decisions in emergency situations. Well-known mathematical models of road traffic take into account only the average values of traffic flows, and not the exact number of cars on each road section at a particular time.
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10

Lebedev, G. M., and V. B. Malygin. "Assessment of the application feasibility of the genetic algorithm for airports operations optimization based on the collaborative decision-making principles." Civil Aviation High Technologies 22, no. 5 (October 28, 2019): 85–93. http://dx.doi.org/10.26467/2079-0619-2019-22-5-85-93.

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The article proposes a formalization methodology of the basic characteristics of the production processes of the aviation industry major components, such as airlines, airports and air traffic control authorities. This technique is not exhaustive, but it is quite suitable as the basis for the formation of the initial data for decision-making optimization under the conditions of airport operations performance and air traffic management, based on the principles of work coordination of the airports operational units. It is proposed to use a genetic algorithm as a tool for optimizing collaborative decision-making, which allows for a smaller number of iterations in real time to obtain a suboptimal solution that meets the requirements of the process participants. The mathematical model in multiplicative form is presented in making an assessment of the application feasibility of the genetic algorithm, taking into account the interests of three stakeholders. Planning the use of aircraft for the airport flight schedule based on the formalized data of the airline fleet, the capabilities of the base airport apron, as well as the restrictions of permanent and temporary nature is accepted as the original product. The article demonstrates the potential advantage of the genetic algorithm, the point of which is that within each step of a suboptimal choice of priorities instead of brute-force options limited but effective direct search of a reduced number of those options that have been chosen as the "elite" by using multiplicative form is carried out.
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Дисертації з теми "Airports Traffic control Mathematical models"

1

Yan, Li, and 顏理. "On the traffic flow control system." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39431174.

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2

Al-Malik, Mohammed Saleh. "An investigation and development of a combined traffic signal control-traffic assignment model." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/21425.

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3

Cereser, Bruno Luís Hönigmann 1988. "Um modelo matemático para otimizar o descarregamento de navios num terminal graneleiro." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/305870.

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Анотація:
Orientadores: Luiz Leduino de Salles Neto, Antonio Carlos Moretti
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
Made available in DSpace on 2018-08-23T22:02:01Z (GMT). No. of bitstreams: 1 Cereser_BrunoLuisHonigmann_M.pdf: 8696662 bytes, checksum: b4ca681ecf08f10afa47d00b3a879e9e (MD5) Previous issue date: 2013
Resumo: O transporte marítimo é fundamental para grandes empresas de caráter global. Em 2009 80% do comércio mundial foi realizado via transporte marítimo e desde então esse número só tem crescido. Devido a esse alto fluxo nos portos mundiais, surgiu o problema de alocação de navios em berços, que tem por finalidade estabelecer uma sequência de atendimento de navios para cada berço disponível no cais, visando minimizar o tempo total da operação e espera dos navios dentro dos portos. Nesse trabalho o problema de alocação de navios em berços será abordado considerando berços dependentes, e também a divisão das máquinas portuárias em berços consecutivos aplicados a terminais do Porto de Tubarão (ES). Para a representação matemática dos processos desses terminais do porto de tubarão foram desenvolvidos novos modelos matemáticos. Os testes computacionais foram exitosos
Abstract: The maritime transportation is essential to global companies. In 2009 80% of global trade was made by maritime transportation, and over the year this number has raised. Because of this high flux, the BAP (Berth Allocation Problem) arose. The BAP have intent to discovery the vessel allocation sequence in every berth with the minimum total wait time. In this work, the berths of BAP will be considered dependents, we also considered the division of portuary machines between consecutive berths. The objective of this work is the mathematical representation of the terminals Produtos Diversos and Praia Mole of the Tubarão port. For this reasons we propose here unprecedented mathematical models
Mestrado
Matematica Aplicada
Mestre em Matemática Aplicada
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4

Lierkamp, Darren University of Ballarat. "A New ramp metering control algorithm for optimizing freeway travel times." 2006. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12726.

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"In many cities around the world traffic congestion has been increasing faster than can be dealt with by new road construction. To resolve this problem traffic management devices and technology such as ramp meters are increasingly being utilized."--leaf 1.
Masters of Information Technology
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5

Lierkamp, Darren. "A New ramp metering control algorithm for optimizing freeway travel times." 2006. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/14605.

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Анотація:
"In many cities around the world traffic congestion has been increasing faster than can be dealt with by new road construction. To resolve this problem traffic management devices and technology such as ramp meters are increasingly being utilized."--leaf 1.
Masters of Information Technology
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6

Beale, Michael P. "New Approaches to Analyze Sound Barrier Effectiveness." 2012. http://hdl.handle.net/1805/3240.

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Indiana University-Purdue University Indianapolis (IUPUI)
Highway noise can cause annoyance, affect sleep patterns, and reduce the property value for people in the proximity. Current methods for analyzing the effectiveness of sound barriers only take loudness into consideration. This paper introduces new methods that can be used to analyze the effectiveness of the sound barriers. Our approach uses psychoacoustic measures including sharpness, roughness, fluctuation, strength, and annoyance. Highway noise is non-stationary, therefore each of these metrics are calculated over a short time. Finally analysis is performed the distribution and change over time. We used nth nearest neighbor algorithm to remove sounds that are not a part of the experiment. In the future, this data can be combined with human surveys to see if the change in sound quality due to the presence of sound barriers has a meaningful impact on people's lives.
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7

Yaqub, Omar Seddeq Omar. "Modeling, Analysis, and Simulation of Two Connected Intersections Using Discrete and Hybrid Petri Nets." 2014. http://hdl.handle.net/1805/3873.

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Анотація:
Indiana University-Purdue University Indianapolis (IUPUI)
In recent decades, Petri nets (PNs) have been used to model traffic networks for different purposes, such as signal phase control, routing, and traffic flow estimation, etc. Because of the complex nature of traffic networks where both discrete and continuous dynamics come into play, the Hybrid Petri net (HPN) model becomes an important tool for the modeling and analysis of traffic networks. In Chapter 1 a brief historical summery about traffic systems control and then related work is mentioned followed by the major contributions in this research. Chapter 2 provides a theoretical background on Petri nets. In Chapter 3, we develop a HPN model for a single signalized intersection first, then we extend this model to study a simple traffic network that consists of two successive intersections. Time delays between different points of network are also considered in order to make the model suitable for analysis and simulation. In addition to HPN models, we also consider discrete Petri nets where their modeling simplicity enables the characterization of the occurrences of all events in the system. This discrete PN is particularly useful to give a higher-level representation of the traffic network and study its event occurrences and correlations. In Chapter 4, we build a discrete PN model to represent a traffic network with two successive intersections. However, we find that the model leads to unbounded places which cannot accurately reflect the dynamics of the traffic in terms of event occurrences. Hence, we introduce the Modified Binary Petri nets (MBPN) to overcome the limitation and resolve the confliction problem when we design our controllers. This MBPN model is a powerful tool and can be useful for the modeling and analysis of many other applications in traffic networks. Chapter 5 gives a summary for each chapter, provides conclusion and discusses future work for both discrete and hybrid Petri nets.
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Книги з теми "Airports Traffic control Mathematical models"

1

Ozoka, Angus Ifeanyi. Aviation facilities planning, research, and development: A global experience. Lagos, Nigeria: Nigerian Gong Press, 1997.

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2

Air transport system analysis and modelling: Capacity, quality of services and economics. [New York?]: Gordon and Breach Science Publishers, 2000.

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3

Xing, Jing. Reexamination of color vision standards. Washington, D.C: Federal Aviation Administration, Office of Aerospace Medicine, 2006.

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4

Jaehn, Florian. Robust flight gate assignment. Frankfurt am Main: P. Lang, 2008.

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5

Smulders, S. A. Control of freeway traffic flow. Amsterdam, Netherlands: Centrum voor Wiskunde en Informatica, 1996.

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6

D, Griffiths J., ed. Mathematics in transport planning and control: Proceedings of the 3rd IMA International Conference on Mathematics in Transport Planning and Control. Amsterdam: Pergamon, 1998.

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7

Li, Weigang. Computational models, software engineering, and advanced technologies in air transportation: Next generation applications. Hershey, PA: Engineering Science Reference, 2010.

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8

Pedestrian dynamics: Mathematical theory and evacuation control. Boca Raton: Taylor & Francis, 2009.

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9

1958-, Li Weigang, Barros Alexandre de, and Oliveira Ítalo Romani de, eds. Computational models, software engineering, and advanced technologies in air transportation: Next generation applications. Hershey, PA: Engineering Science Reference, 2010.

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10

Kerner, Boris S. Introduction to Modern Traffic Flow Theory and Control: The Long Road to Three-Phase Traffic Theory. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2009.

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Частини книг з теми "Airports Traffic control Mathematical models"

1

Kachroo, Pushkin, and Kaan M. A. Özbay. "Traffic Assignment: A Survey of Mathematical Models and Techniques." In Advances in Industrial Control, 25–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-69231-9_2.

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2

Galvão França, Felipe Maia, and Félix Mora-Camino. "Cooperative Control for Ground Traffic at Airports." In Computational Models, Software Engineering, and Advanced Technologies in Air Transportation, 57–70. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-800-0.ch004.

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With the sustained increase in air transportation, resulting in increased operational costs, potential danger with conflictive traffic conditions and delays for passengers and airlines, ground traffic has become a critical issue for many airports. In this communication the ground traffic at an airport is considered to be composed of three dependent flows: aircraft, passenger vehicles and servicing vehicles. It is assumed in this study that each type of vehicles belongs to a common pool which attends every arriving or departing aircraft. The objective here is to propose a global control structure based on cooperation between the different agents responsible for the management of each fleet to reduce overall aircraft traffic delays at airside.
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Тези доповідей конференцій з теми "Airports Traffic control Mathematical models"

1

Amanuel QasMarrogy, Ghassan, and Husham Jawad Ahmad. "Modeling of an Airport Traffic Control (ATC) Radars Using Mathcad." In 4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022). Cihan University, 2022. http://dx.doi.org/10.24086/cocos2022/paper.576.

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Air traffic control systems condensed ATC, are faculty liable for the protected, methodical, and quick progression of air traffic in the worldwide aviation authority framework. Typically positioned in airport regulation focuses and control towers on the ground, they screen the position, speed, and elevation of an airplane in their doled-out airspace outwardly and by radar, and give headings to the pilots by radio. The place of air traffic regulator requires profoundly specific information, abilities, and capacities. Therefore, it's very important to draw and analyze the model for that system. In this paper an Air Traffic Control (ATC) radar mathematical model is built using Mathcad software. The model has the capability of taking into account various radar parameters and converting them into Mathcad codes. Calculations throughout the model are based on basic theoretical equations as well as empirical engineering formulas which give acceptable error tolerances. Results are displayed graphically, particularly the maximum radar range for various essential radar parameters such as the probability of detection, probability of false alarm, and several integrated pulses.
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2

Stojanov, Z., J. Stojanov, G. Jotanovic, and D. Dobrilovic. "Weighted networks in socio-technical systems: Concepts and challenges." In The International Workshop on Information, Computation, and Control Systems for Distributed Environments. Crossref, 2020. http://dx.doi.org/10.47350/iccs-de.2020.24.

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Socio-technical systems join together humans and technique. Basic concepts and principles of socio-technical systems are outlined, as well as weighted networks as the appropriate mathematical models. Particular examples of socio-technical systems with various usages of weighted networks in domains such as airline connection networks, scientific collaboration, social networks, software engineering and urban traffic are presented. Comparative analysis of the selected examples is outlined with the focus on the nature and functions of nodes, links and weights. The identified challenges, such as the creation of networks, evolving nature of systems, and the need for multidisciplinary teams in the system design are discussed.
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3

Jung, Martin, and Axel B. Classen. "PANDEMIC SIM – Impact analysis and improvement potentials for airport security processes." In 8th International Conference on Human Interaction and Emerging Technologies. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002724.

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In the beginning of 2020, one of airports’ greatest concerns was how to provide sufficient capacity for traffic both on airside and on landside. However, since the COVID-19 pandemic affects worldwide the complete transport sector traffic numbers are significantly nosediving due to wide-ranging travel restrictions – especially as to passenger air transport (see IATA, 2020). In order to enable air transport to recover as soon as travel restrictions are lifted and to ensure that passengers as well as people working within the air transport sector will remain safe, the risk of spreading the COVID-19 virus via droplet, airborne or contact transmission during travel processes must obligatory be mitigated. A recent document, issued by the European Union Aviation Safety Agency (EASA) together with the European Centre for Disease Prevention and Control (ECDC), therefore provides “guidance for the management of air passengers and aviation personnel in relation to the COVID-19 pandemic” (EASA, ECDC, 2021). This document describes measures to minimize contamination risks along travel processes. The measures described are flanked by other documents and initiatives of the relevant actors in air transport, like the IATA, ICAO, ACI as well as governmental authorities. In our study we examine those measures that have an impact on airport-terminal’s passenger flow and capacity with emphasis on security checks (Airport Security Process – ASP) by dint of a new simulation model named Pandemic Simulation Model (Pandemic SiM), hereby namely Pandemic SiM ASP. For this purpose we advanced a recently developed baseline simulation model (SiM) reproducing the security check area of a medium sized European airport serving around 12 million passengers per year. SiM was originally developed during a former project under pre-COVID-19 conditions and validated together with experts of that airport. Pandemic SiM is now the enhanced version comprising pandemic guidelines for the purpose of process visualization, impact analysis and identification of improvement potentials and may even be adapted individually to any other airport environment.In order to examine the consequences resulting from changes in passenger management at airports we compare the results of simulation runs of the current baseline model SiM with those of our new model Pandemic SiM, updated according to the relevant measures prescribed by EASA and ECDC (EASA, ECDC, 2021). In a first step we examine the behaviour of Pandemic SiM by simulating the original baseline traffic scenario parallel in both models, SiM and Pandemic SiM. In a second step we compare the resulting figures of baseline SiM with those of Pandemic SiM COVID-19 model. This direct comparison of the simulation outputs with the same traffic scenario will show the consequences of the measures to stem the pandemia. In a third step, we will carve out an approximation of the operational capacity limits under pandemic conditions by varying traffic volume in further simulations.Based on the analysis of the simulation results we will not only be able to quantify the resulting capacity but also to develop suggestions to improve airport operations and capacity under COVID-19 conditions in the final section of our paper.
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4

Boudjidj, Abdelghani, and Mohammed El Habib Souidi. "A Formal Composition of Multi-Agent Organization based on Category Theory." In 9th International Conference on Foundations of Computer Science & Technology (CST 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.121909.

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The application of organizational multi-agent systems (MAS) provides the possibility of solving complex distributed problems such as, task grouping mechanisms, supply chain management, and air traffic control. The composition of MAS organizational models can be considered as an effective solution to group different organizational multi-agent systems into a single organizational multi-agent system. The main objective of this paper is to provide a MAS organizational model based on the composition of two organizational models, Agent Group Role (AGR), and Yet Another Multi Agent Model (YAMAM), with the aim of providing a new MAS model combining the concepts of the composed organizational models. Category theory represents the mathematical formalism for studying and modeling different organizations in a categorical way. This paper is mainly based on the idea of modeling the multi-agent organization AGR and YAMAM in a categorical way in order to obtain formal semantic models describing these organizations of MAS, then compose them using also the theory of categories which represents a very sophisticated mathematical toolbox based on composition.
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Pérez Castán, Javier Alberto. "How do Continuous Climb Operations affect the capacity of a Terminal Manoeuvre Area?" In CIT2016. Congreso de Ingeniería del Transporte. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.3525.

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Continuous climb operations are the following step to optimise departure trajectories with the goals of minimizing fuel consumption and pollutants and noise emissions in the airports neighbourhood, although due to intrinsic nature of these procedures, the integration of these procedures need to develop a new framework for airline operators and air traffic control. Based on the BADA model developed by EUROCONTROL, three activities have been carried out: simulation of several continuous climbs for three aircraft types (Light, Medium and Heavy), analysation of different applied separations throughout the climb from the runway up to cruise level and, as third activity, definition of new separation minima to ensure that the minimum separations are not violated with this new procedures along the climb. In this work are presented the results of modelling three continuous climb type (constant true airspeed, constant climb angle and constant vertical speed) and new time-based separations for most used models in Palma TMA, which will be the case-study scenario. Finally, this theoretical analysis has been applied to a real scenario in Palma de Mallorca TMA in order to compare how the capacity deals with the introduction of this new procedure to standard departures, standard departures are understood as a departure with a level-off at a determined altitude and with the possibility to be affected by any ATC action. First outcomes are promising because capacity, theoretically, would not be grossly diminished, which could initially be expected based on previous studies on continuous descent approaches, although these results should be considered cautiously due to the fact that the model lacks several factors of associated uncertainty for a real climb.DOI: http://dx.doi.org/10.4995/CIT2016.2016.3525
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Schwartz, Michael, Cortnee Stainrod, and Irin Nizam. "Pedestrian Modeling for Mitigation of Disease Transmission in a Simulated University Environment." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001358.

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Understanding the spread of COVID-19 through mathematical modeling is an effective method of evaluating control interventions and the impact of infectious diseases. It is important to understand how individuals move and gather within indoor spaces as early awareness of specified strategies act as decision-making tools to riskier alternatives. On university campuses, indoor spaces pose unique threats due to high traffic spaces in the building hallways, restrooms and bottleneck points that lead to mass congregation and therefore increased risk of transmission. Evaluation of infectious diseases transmission as a result of pedestrian dynamics (e.g., pedestrian density, crowding, queue and wait times) was used to determine time-varying social distancing during pedestrian interactions/movements. Multiple campus buildings were modeled to demonstrate environments with varying size and complexity. Building models were constructed using the pedestrian features of AnyLogic. The proposed solution makes the following contributions by tracking the control measures of pedestrian dynamics at the microscopic level through temporal and spatial separation. This is done by enforcing social distancing through reducing the number of individual occupants at one time (i.e., segmented student population) and staggering start and end arrival times.The two greatest risk factors in the models were time and space. Entrances and exits to buildings, classrooms, and restrooms, and other queues forced simulated agents to cross the danger threshold as these building features were physical bottlenecks. Model results demonstrated sharp, but brief increases in transmission due to not staggering class arrival and departure times. Results indicated that controlling scheduling or forcing space assignments/social distancing were effective in reducing contacts and risk of spreading disease; however, the greatest reduction in risk of disease transmission occurred when both methods were used in conjunction. When class arrival and departure times are staggered, transmission between people not in the same class is only possible during chance encounters due to restroom visits, late arrivals, or early departures.
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Banerjee, Subharthi, Michael Hempel, Pejman Ghasemzadeh, Naji Albakay, and Hamid Sharif. "High Speed Train Wireless Communication: Handover Performance Analysis for Different Radio Access Technologies." In 2019 Joint Rail Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/jrc2019-1247.

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High Speed Trains (HST) face some of the most stringent requirements for ensuring passenger safety and comfort while operating at very high velocities. HST wireless communication systems therefore similarly require special considerations for network design, technology selection and system implementation. For infrastructure-based wireless communications, a handover occurs whenever a radio transitions from the coverage of the current base station to the next base station. The faster the train moves the shorter the time that it spends under coverage area before a handover is required. For HST this can be as short as 10–20 seconds. Furthermore, a HST moving at 220 mph experiences significant fast and small-scale wireless signal fading due to this velocity, but similarly may incur frequent connectivity losses due to the rapid transit across coverage areas. A route consisting of viaducts, bridges, tunnels or hilly regions drastically increases the need for rapid handovers since a large number of base stations are required to provide coverage and achieve acceptable Quality-of-Service (QoS) in such environments. Due to the relatively fixed amount of time needed to complete a handover, and the possibility of failed handovers, this reduces the usable time under coverage, and thus ensuring an optimal handover strategy selection is vital. Most of the routes span rural and suburban areas, which reinforces the need for a comprehensive network planning strategy, as these areas tend to be underdeveloped for cellular coverage. Given the complexity in available radio spectrum resources, detailed studies are required to aid in this technology selection process. However, with the predicted increase in the demand of railroad network data traffic generated by onboard sensors, onboard control and operation devices, passenger Internet services, etc., it becomes apparent that more resources are needed than are provided by current technologies such as LTE. Thus, including 5G New Radio for Railways (5G-NR2) in the consideration does not only provide railways a more cost-effective licensing option for frequencies, but also an opportunity to select the best possible radio access method for a given HST corridor. In this paper, we focus on the metrics related to handover and how they correlate with different radio access technologies for HST. Our results integrate the uncertainty of environmental factors to provide answers on technology selection driven by specific route, inter-site distances, and available bandwidth. Our wireless communication simulation results are driven by well recognized mathematical models that consider a variety of key parameters. The analysis of the handover performance will offer insights vital to future railroad network planning for multivariate radio access technologies, and to answer crucial questions about the potential for using frequency bands above 6 GHz in HST.
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