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Article . 2018
License: CC BY
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A Comparison Framework for Conflict Detection and Resolution Multi Agent Modeling Methods in Air Traffic Management

Authors: Hojjat Emami;

A Comparison Framework for Conflict Detection and Resolution Multi Agent Modeling Methods in Air Traffic Management

Abstract

Nowadays air traffic density increased, thus existing air traffic management systems are not able to manage the massive capacities of air traffic perfectly. To solve problems in current air traffic management systems, the aviation industry focused on a new concept called Free flight. Nonetheless, the most important challenge in current air traffic management and especially in free flight is conflict detection and resolution between different aircrafts. So far a number of methods have been presented in order to automate air traffic management using multi agent systems technology. However, there has been a little discussion about the efficiency of these methods. Also, there has not been created a comprehensive comparison of these methods. In this paper, we presented a clear framework to categorization and comparing different multi agent models for conflict detection and resolution in air traffic management. Then, using this framework, we evaluated various proposed models. Our comparison framework is based on characteristic such as: agent selection (the entity which selected as Agent), agent’s actions, agents’ interaction method in the process of conflict detection and resolution, the strategy used in agents’ implementation, type of the multi agent system (pure multi agent system or combined), conflict detection method, conflict resolution method, Plan Dimensions, Maneuvers, and management the multiple aircrafts’ conflict.

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Keywords

Air Traffic Management, Multi Agent Systems, Free flight,

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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