Multi-Agent Tools for Air Traffic Management

Oliveira, Ítalo Romani de; Carvalho, F.S.; Camargo, João Batista; Sato, Líria Matsumoto

doi:10.1109/csew.2008.46

Cited by 10 publications

(3 citation statements)

References 3 publications

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“…Some of these values are fixed data, while others can be modified and represent our scope for reducing conflict. In this paper, we assume that the flight level and the Mach number are constant since we are tackling only the enroute phase 3 . For each flight the following input data are given :…”

Section: A Flight Modelmentioning

confidence: 99%

“…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%

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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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Section: A Flight Modelmentioning

confidence: 99%

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)

View full text Add to dashboard Cite

show abstract

“…If the agents can interact with each other at doing delegated tasks then the efficiency of the system increases. Proposed models based on multi agent systems for air traffic management that use interactional process and negotiation techniques are more efficient than solutions in which agents use nonintractable process or traditional approaches [10], [11]. For example, surely if agents interact and negotiate with each other in conflict detection and resolution process, firstly, the volume of controller workload can be reduced by each agent, and if agents are coordinated with each other, they can distribute the necessary tasks -for example in a particular area -to resolve conflicts and perform things faster and more accurate.…”

Section: Agents' Interactionmentioning

confidence: 99%

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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An Overview of Cooperative and Consensus Control of Multiagent Systems

Davoodi

Gallehdari

Saboori

et al. 2016

Wiley Encyclopedia of Electrical and Electronics Engineering

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There has been a growing interest toward the development of networked unmanned autonomous systems that can operate without an extensive involvement of humans. The motivation for this focus can be traced to the emergence of applications where direct human intervention is not possible due to the environmental hazards, complexity of the tasks, or other restrictions. These networks can consist of a large number of dynamical systems (agents), such as unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and unmanned underwater vehicles (UUVs). These systems commonly include a number of sensors, actuators, and decisionmakers. Therefore, the network of these systems is a network of a large number of sensors and actuators or, as is known in the literature, a system of systems (SoS). In this work, we provide a brief overview of controlling these networks, their applications, and the solutions that are proposed for these problems in the literature. Specifically, this article overviews recent results and progress made on multiagent consensus by focusing on cooperative control and consensus (formation) control in the presence of communication, control implementation, and saturation constraints. In addition, we review the active areas of event‐triggered consensus control, network security and attacks on the agents, and networks and resilient consensus control strategies that are proposed to handle these challenges.

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Multi-Agent Tools for Air Traffic Management

Cited by 10 publications

References 3 publications

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

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

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

An Overview of Cooperative and Consensus Control of Multiagent Systems

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