A New Ontology-Based Multi-Agent System Model for Air Traffic Management

Document Type : Research Paper

Authors

1 PhD Student, Department of computer engineering, Neyshabur Branch, Islamic Azad University, Neyshabur, Iran

2 Assistant Prof, Department of computer engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran

3 Assistant Prof , Department of computer engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran

4 Assistant Prof , Department of computer engineering, Neyshabur Branch, Islamic Azad University, Neyshabur, Iran

Abstract

Problems such as flights sequences, flights emergency positions, hijacking, airport controlled space management, and Free Flight are problems that the Air Traffic Management (ATM) are faced with it. Managing a large volume of flights data and their correct interpretation plays a key role in the prevention of air accidents, human errors, and flight interactions. The agent-based systems and ontology are tools that together have attributes such as autonomy, learning, and cooperation to solve ATM's problems. This research proposed a new ontology-based multi-agent system for air traffic management. The design of air agents has been done on the architectural basis of BDI. This model contains five main modules that were designed under Multi-agent Software Engineering (MaSE) methodology in AgentTool tools. Methontology methodology was exploited for the engineering of the ontology of agents and the implementation process was carried out using the Protégé software. The hybrid model ATM ontology-based multi-agent system (ATM-onto-mas) has been implemented with Java Agent Development Framework (JADE). The actual flight data of Mashhad Airport, Iran used to evaluate and test this model. Terminal control area (TMA) of Mashhad Airport was designed and simulated in an ATCsim simulator based on real data. The obtained results of the ATM-onto-mas system in a simulated environment indicate improvement in the evaluated parameters Compared with other methods.

Keywords

References

- Kristan, Trevor, et al. "An evolutionary outlook of air traffic flow management techniques ." Progress in Aerospace Sciences 88 (2017): 15-42.
 
- Sternberg, Alice, et al. "A review on flight delay prediction." arXiv preprint arXiv: 1703.06118 (2017).
 
- Aghdam, Mahdi Yousefzadeh, et al. "Optimization of air traffic management efficiency based on deep learning enriched by the long short-term memory (LSTM) and extreme learning machine (ELM)." Journal of Big Data 8.1 (2021): 1-26.
 
- Aghdam, Mahdi Yousefzadeh, Seyed Reza Kamel Tabbakh, and Seyed Javad Mahdavi Chabok. "Ontology generation for flight safety messages in air traffic management." Journal of Big Data 8.1 (2021): 1-21.
 
- Molina, Martin, Sergio Carrasco, and Jorge Martin. "Agent-based modeling and simulation for the design of the futurEuropeanan air traffic management system: The experience oCassiopeiaia." International Conference on Practical Applications of Agents and Multi-Agent Systems. Springer, Cham, 2014.
 
- Gore, Brian F. "Man-machine integration design and analysis system (MIDAS) v5: Augmentations, motivations, and directions for aeronautics applications." Human modeling in assisted transportation. Springer, Milano, 2011. 43-54.
 
- Šišlák, David, et al. "AGENTFLY: Towards multi-agent technology in free flight air traffic control." Defense industry applications of autonomous agents and multi-agent systems. Birkhäuser Basel, 2007. 73-96.
 
- Molina, Martin, Sergio Carrasco, and Jorge Martin. "Agent-based modeling and simulation for the design of the future European air traffic management system: The experience of Cassiopeia." International Conference on Practical Applications of Agents and Multi-Agent Systems. Springer, Cham, 2014.
 
- Becker-Asano, Christian, et al. "A multi-agent system based on unity 4 for virtual perception and wayfinding." Transportation Research Procedia 2 (2014): 452-455.
 
- Bazzan, Ana LC, and Franziska Klügl. Multi-agent systems for traffic and transportation engineering. IGI Global, 2009.
- Breil, Romaric, et al. "Multi-agent systems to help to manage air traffic structure." Journal of Aerospace Operations 5.1-2 (2017): 119-148.
 
- Sheng, Yin, et al. "An ontology for decision-making support in air traffic management." Artificial Intelligence in China. Springer, Singapore, 2020. 458-466.
 
- Gringinger, E., Keller, R. M., Vennesland, A., Schuetz, C. G., & Neumayr, B. (2019, September). A comparative study of two complex ontologies in air traffic management. In 2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC) (pp. 1-9). IEEE.
 
- Fernández-López, Mariano, Asunción Gómez-Pérez, and Natalia Juristo. "Methontology: from ontological art towards ontological engineering." (1997).
International Journal of Transportation Engineering
Volume 10, Issue 3 - Serial Number 39
January 2023
Pages 1055-1068

Files

Share

How to cite

Statistics