An overview on conflict detection and resolution methods in air traffic management using multi agent systems

Emami, Hojjat; Derakhshan, Farnaz

doi:10.1109/aisp.2012.6313761

Cited by 13 publications

(12 citation statements)

References 27 publications

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“…Of course, in this paper, we used some of presented criterions in Kuchar and Yang paper [4] to compare proposed air traffic management models. Moreover, in following sections, we proposed some other novel criterions based on multi agent systems [35].…”

Section: Compare Air Traffic Management Models Based On Multi Agent Smentioning

confidence: 99%

“…This feature discusses that during resolving of conflicts what solution or in other words, what type of maneuver will be used to resolve conflicts. To summarize, some of the maneuvers include: speed change (decrease or increase of aircrafts' speed), changing the angles (horizontal maneuver), change and adjust altitude (vertical maneuvers) and turn maneuver [4], [35]. Some of the models have been used only one of these criterions to resolve collisions and others has used a combination of these criterions.…”

Section: Resolution Maneuversmentioning

confidence: 99%

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

Emami¹

2012

IJITCA

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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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Section: Compare Air Traffic Management Models Based On Multi Agent Smentioning

confidence: 99%

Section: Resolution Maneuversmentioning

confidence: 99%

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

Emami¹

2012

IJITCA

Self Cite

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“…Recently, the paradigm of multi-agent systems has become widely applied for air traffic management. Several researches are devoted to apply multi-agent systems for air traffic management and collision avoidance in the continental airspace [3,4]. Nevertheless, to our knowledge, no research works has applied these systems in the oceanic airspace.…”

Section: Introductionmentioning

confidence: 99%

Strategic planning of aircraft trajectories in North Atlantic oceanic Airspace based on flocking behaviour

Dhief

Dougui

Delahaye

et al. 2016

2016 IEEE Congress on Evolutionary Computation (CEC)

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The North Atlantic Airspace (NAT) accommodates traffic between Europe and North America. This area is considered as the most congested oceanic airspace in the world. Radar-Based surveillance is not applied in the most of the oceanic area due to its limited coverage. So, aircraft become obliged to follow predefined routes called Organized Track System (OTS). These routes require very restrictive separation standards which limit the traffic of aircraft. Thus, a new kind of communication system, called Automated Dependence Surveillance Broadcast (ADS-B), has been introduced in order to afford the aircraft a reliable communication with both controllers and surrounding traffic. Hence, aircraft crossing the NAT will be able to follow more flexible routes, which will improve significantly the air traffic situation over this area. In this paper, we propose a strategic planning 1 model that overcomes the constraints of the OTS system in order to produce the closest routes to the direct ones of aircraft. This method is based on flocking boid model. It provides us with satisfying results on a portion of one day traffic over the NAT airspace.

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“…The relationship between A i and A j is studied in local frame. We define P ij as P ij ¼ x i ðtÞ À x j ðtÞ; y i ðtÞ À y j ðtÞ (13) There is potential conflict hazard between UAVs if the following condition is satisfied jjP x ij ðtÞ; P y ij ðtÞjj 2 <r ij ; t 2 ð0; ÁT Þð8i; j 2 f1; . .…”

Section: Cdr Midterm Rewardmentioning

confidence: 99%

Decentralized cooperative unmanned aerial vehicles conflict resolution by neural network-based tree search method

Yang

Yin

Cheng

et al. 2016

International Journal of Advanced Robotic Systems

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In this article, a tree search algorithm is proposed to find the near optimal conflict avoidance solutions for unmanned aerial vehicles. In the dynamic environment, the unmodeled elements, such as wind, would make UAVs deviate from nominal traces. It brings about difficulties for conflict detection and resolution. The back propagation neural networks are utilized to approximate the unmodeled dynamics of the environment. To satisfy the online planning requirement, the search length of the tree search algorithm would be limited. Therefore, the algorithm may not be able to reach the goal states in search process. The midterm reward function for assessing each node is devised, with consideration given to two factors, namely, the safe separation requirement and the mission of each unmanned aerial vehicle. The simulation examples and the comparisons with previous approaches are provided to illustrate the smooth and convincing behaviours of the proposed algorithm.

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An overview on conflict detection and resolution methods in air traffic management using multi agent systems

Cited by 13 publications

References 27 publications

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

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

Strategic planning of aircraft trajectories in North Atlantic oceanic Airspace based on flocking behaviour

Decentralized cooperative unmanned aerial vehicles conflict resolution by neural network-based tree search method

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