scholarly journals Ontology generation for flight safety messages in air traffic management

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mahdi Yousefzadeh Aghdam ◽  
Seyed Reza Kamel Tabbakh ◽  
Seyed Javad Mahdavi Chabok ◽  
Maryam kheyrabadi
Keyword(s):  
Traffic Management ◽  
Telecommunication Network ◽  
Implementation Process ◽  
Air Traffic ◽  
Flight Safety ◽  
Human Errors ◽  
Air Traffic Flow Management ◽  
Traffic Flow Management ◽  
Aviation Network

AbstractThe analysis of various data is a challenging issue in the field of air traffic flow management (ATFM). Managing a large volume of data and their correct interpretation plays a key role in the prevention of air accidents, human errors, and flight interactions. In general, pilots and flight navigators deal with massive and variety information, including flight safety messages, meteorological messages, aviation notes for air man (NOTAMs) and etc. Therefore relationship between Heterogeneous big data is problem. Recently, the semantic web has been recognized as a novel foundation of knowledge management that relies on ontology (concept modeling language). The present study aimed to propose an efficient infrastructure for ATMs by defining the concepts, rules, and relationships between the concepts related to the scope of flight information. To this end, we designed and implemented the ontology of flight safety messages, which included an important part of flight operation information. In this research, the internet protocol suite (IPS)-based aviation networks and methontology methodology were exploited for the engineering of the ontology of flight messages. In addition, the implementation process was carried out using the Protégé software. The analysis of the system was performed using the actual data of Mashhad Airport, Iran. Finally, the implementation of the ontology of flight messages was demonstrated after a case study of several flight examples. The developed ontology could be incorporated into the foundation of an aeronautical telecommunication network (ATN) aviation network as an application.

scholarly journals Ontology Generation for Flight Safety Messages in Air Traffic Management(ATM)

2021 ◽  
Author(s):  
mahdi Yousefzadeh Aghdam1 ◽  
Seyed Reza Kamel ◽  
Seyed Javad Mahdavi Chabok ◽  
maryam khairabadi
Keyword(s):  
Traffic Management ◽  
Implementation Process ◽  
Large Data ◽  
High Volume ◽  
Air Traffic ◽  
Flight Safety ◽  
Human Errors ◽  
Air Traffic Flow Management ◽  
Reliability Factor ◽  
Traffic Flow Management

Abstract The analysis of various data is a challenging issue in the field of air traffic flow management (ATFM). Managing a large volume of data and their correct interpretation plays a key role in the prevention of air accidents, human errors, and flight interactions. In general, pilots and flight navigators deal with massive information, including flight safety messages, meteorological messages, aviation NOTAMs, aviation company information messages, and airplane system alerts. Air collisions are possible due to the high volume and variety of such information considering the human errors in their interpretation and application. Therefore, attempts should be made to develop systematic information and establish logical communication between large data volumes in order to increase the reliability factor in flights. Recently, the semantic web has been recognized as a novel foundation of knowledge management that relies on ontology (concept modeling language) and effective techniques for the modeling of integrated information systems and eliminating barriers to the interpretation and exchange of data. The present study aimed to propose an efficient infrastructure for ATMs by defining the concepts, rules, and relationships between the concepts related to the scope of flight information. To this end, we designed and implemented the ontology of flight safety messages, which included an important part of flight operation information. In this research, the IPS-based aviation networks and methontology methodology were exploited for the engineering of the ontology of flight messages. In addition, the implementation process was carried out using the Protégé software. The analysis of the system was performed using the actual data of Mashhad Airport, Iran. The obtained data were based on the inbound and outbound flights of the airport, which were collected using the radar system and FDS and normalized. Finally, the implementation of the ontology of flight messages was demonstrated after a case study of several flight examples. The developed ontology could be incorporated into the foundation of an ATN aviation network as an application.

A Multi-Agent Simulation of Collaborative Air Traffic Flow Management

2009 ◽  
pp. 357-381 ◽  
Author(s):  
Shawn R. Wolfe ◽  
Peter A. Jarvis ◽  
Francis Y. Enomoto ◽  
Maarten Sierhuis ◽  
Bart-Jan van Putten
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Air Traffic ◽  
Simulation Design ◽  
Flow Management ◽  
Air Traffic Flow Management ◽  
Air Traffic Flow ◽  
Traffic Flow Management ◽  
Agent Simulation ◽  
Traffic Management System

Today’s air traffic management system is not expected to scale to the projected increase in traffic over the next two decades. Enhancing collaboration between the controllers and the users of the airspace could lessen the impact of the resulting air traffic flow problems. The authors summarize a new concept that has been proposed for collaborative air traffic flow management, the problems it is meant to address, and our approach to evaluating the concept. The authors present their initial simulation design and experimental results, using several simple route selection strategies and traffic flow management approaches. Though their model is still in an early stage of development, these results have revealed interesting properties of the proposed concept that will guide their continued development, refinement of the model, and possibly influence other studies of traffic management elsewhere. Finally, they conclude with the challenges of validating the proposed concept through simulation and future work.

The Adoption of Network-Centric Data Sharing in Air Traffic Management

2021 ◽  
pp. 127-151
Author(s):  
Karel Joris Bert Lootens ◽  
Marina Efthymiou
Keyword(s):  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Point Of View ◽  
Structured Interviews ◽  
Air Navigation Services ◽  
Aviation Network ◽  
Collaborative Decision ◽  
Insight Into

Network-centric sharing of data between all Air Traffic Management (ATM) stakeholders can improve the aviation network substantially. The System Wide Information Management (SWIM) platform is a platform for the open sharing of all information between aircraft operators, airports, air navigation services providers (ANSPs), and meteorology services, but has struggled to find a following. This article aims to identify the potential reasons for the slow adoption of the SWIM platform, and to investigate how to better communicate its potential. To gain insight into the drivers for each of the stakeholders, a series of semi-structured interviews was conducted with airlines, airports and ANSPs. Moreover, an Airport Collaborative Decision Making (A-CDM) initiative at the airport in Dublin was included as a case study. Recommendations are provided on how to address the results from a governance point of view.

The Adoption of Network-Centric Data Sharing in Air Traffic Management

2019 ◽  
Vol 32 (3) ◽  
pp. 48-69
Author(s):  
Karel Joris Bert Lootens ◽  
Marina Efthymiou
Keyword(s):  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Point Of View ◽  
Structured Interviews ◽  
Air Navigation Services ◽  
Aviation Network ◽  
Collaborative Decision ◽  
Insight Into

Network-centric sharing of data between all Air Traffic Management (ATM) stakeholders can improve the aviation network substantially. The System Wide Information Management (SWIM) platform is a platform for the open sharing of all information between aircraft operators, airports, air navigation services providers (ANSPs), and meteorology services, but has struggled to find a following. This article aims to identify the potential reasons for the slow adoption of the SWIM platform, and to investigate how to better communicate its potential. To gain insight into the drivers for each of the stakeholders, a series of semi-structured interviews was conducted with airlines, airports and ANSPs. Moreover, an Airport Collaborative Decision Making (A-CDM) initiative at the airport in Dublin was included as a case study. Recommendations are provided on how to address the results from a governance point of view.

The Airline's Perception of Air Traffic Management

1990 ◽  
Vol 43 (2) ◽  
pp. 204-208 ◽  
Author(s):  
Colin Hume
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Flow Management ◽  
Air Traffic Flow Management ◽  
Air Traffic Flow ◽  
Traffic Flow Management ◽  
Reverse Situation

The situation today can be described as very frustrating for a variety of reasons. Air traffic flow-management (ATFM) has dominated the scene for many years since its conception in 1980. At that time, the principles of ATFM were directed at ensuring that temporary or isolated sector overloads could be handled by ATC and only when broad, prolonged overloads were expected was ATFM activated. Today, we have the reverse situation, where ATFM is active throughout 16 h or more during each day. The system as such was never intended or planned to cope with such a burden and the results are seen in a variety of forms, including departure delays as shown in Fig. 1.

scholarly journals Investigation of Flight Traffic Arrangement With ICA Colonial Competition Algorithm In Air Traffic Management

2021 ◽  
Author(s):  
Mahdi Yousefzadeh Aghdam ◽  
Seyed Reza Kamel Tabbakh ◽  
Seyed Javad Mahdavi Chabok ◽  
Maryam Kheyrabadi
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Mathematical Problem ◽  
Air Traffic ◽  
Flight Delays ◽  
Flow Management ◽  
Air Traffic Flow Management ◽  
Air Traffic Flow ◽  
Traffic Flow Management ◽  
Using Data

Abstract Air traffic flow management is one of the most challenging work systems in the world. The issue of aircraft traffic arrangement to prevent interference and flight delays is one of the most important issues in the field of air traffic flow management. In most researches in this field, incoming or outgoing flights are usually dealt with separately and attempts have been made to provide solutions using data mining methods, mathematical problem solving, etc.‌ To solve the problem in this paper, to select the best aircraft ready for operation (landing or takeoff), we use the ICA colonial competition algorithm, which allows selecting aircraft for incoming or outgoing flights, according to various parameters. In designing the system, an attempt has been made to make the symbols more effective in flight, to give proper weight, and to optimize the selection of colonizers according to the lower cost. To evaluate the proposed method, flight data of Mashhad airport were used for testing. The results of the system test indicate better choices for landing or flying aircraft and the acceptable performance of the colonial competition algorithm compared to the latest work done to solve the flights landing and take off sequence problem as an innovative algorithm.

scholarly journals Insights of Models for Air Traffic Management System

2019 ◽  
Vol 8 (3S3) ◽  
pp. 459-467
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Flow Management ◽  
Air Traffic Flow Management ◽  
Traffic Flow Management ◽  
The Usa ◽  
Comprehensive Survey ◽  
Traffic Management System

In many airports and air markets, congestion problems & weather are becoming more and more severe. To keep Air Traffic Control (ATC) against the overload of Air Traffic Flow Management (ATFM) activity, attempts to anticipate and prevent the resulting overload and limit the delays. A delay in the arrival of the flight (so-called congestion) occurs when the traffic expects to surpass the arrival and departure capacity of the airport or the airsector capacity. There is a very extensive over general reasoning to be considered in this area. Generally speaking, most of the references found in the literature published a few years ago refer to the simplest versions, those that do not take airsector into account. This happens because the research was first done in the USA only, where traffic issues basicallylimited to the airports congestion. In the paper we present a comprehensive survey of the key optimization models of literature.

Improving Support for Contingency Planning in Air Traffic Flow Management

2020 ◽  
Vol 64 (1) ◽  
pp. 203-207
Author(s):  
Alicia Fernandes ◽  
Chris Brinton ◽  
Curt Kaler
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Air Traffic ◽  
Contingency Planning ◽  
Modeling Framework ◽  
Flow Management ◽  
Air Traffic Flow Management ◽  
Limited Support ◽  
Traffic Flow Management ◽  
Decision Making Processes

As air traffic continues to increase, it will be increasingly important to maximize use of available capacity. Traffic management coordinators explicitly incorporate contingency planning into their decision-making processes, but current Traffic Flow Management (TFM) tools provide limited support for such contingency planning. This paper describes an effort to explicitly support contingency planning in TFM, allowing automation to better align with the human’s approach to the situation. We propose a modeling framework and report on initial operational feedback indicating that our modeling framework captures the essence of TFM workflow.

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