An Agent-Based Approach for the Design of the Future European Air Traffic Management System

Molina, Martín; Martín, Jorge; Carrasco, Sergio Carrasco

doi:10.1007/978-3-319-07551-8_38

Cited by 3 publications

(4 citation statements)

References 3 publications

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“…The level of abstraction of agent-based modeling is an issue that needs to be properly weighed to deal with the scale and complexity of the problem to be solved in a system. Although agent components described at a high level of abstraction could result in efficient systems, a great amount of computation time is usually required, as well as extensive input preparation [ 25 ]. Specifically, running a model for an ATM system defined at a microscopic level and the consideration of details (such as aircraft approaches, runways, taxiways, aircraft movements, bus movements, and passenger behavior during check-in) typically requires several hours [ 20 ].…”

Section: Modeling Overviewmentioning

confidence: 99%

“…However, there are some critical issues to be solved when these models are used for delay prediction in the phase of tactical Air Traffic Flow Management (ATFM). Specifically, most of these models attempt to control the degree of system refinement to achieve a tradeoff between accuracy and the time-consuming computations for predicting and analyzing delays [ 25 ], while more detailed and real-time parameter acquisition is not emphasized. For example, the minimal ground turnaround time is only a function of an aircraft seat category [ 19 ], or obtained by percentile values [ 26 ], or substituted by a constant [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

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Prediction of air traffic delays: An agent-based model introducing refined parameter estimation methods

Wang

Yang

et al. 2021

PLoS ONE

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We propose an agent-based model for predicting individual flight delays in an entire air traffic network. In contrast to previous work, more detailed parameter estimation methods were incorporated into the agent-based model, acting on the state transitions of agents. Specifically, a conditional probability model was proposed for modifying the expected departure time, which was used to indicate whether a flight had experienced the necessary waiting due to Ground Delay Programs (GDPs) or carrier-related reasons. Additionally, two random forest regression models were presented for estimating the turnaround time and the elapsed time of flight agents in the agent-based delay prediction model. The parameter models were trained and fitted using the flight data for 2017 in the United States. The performance of the delay prediction model was tested for thirty days with three types of delay levels (low, medium, and high), which were randomly selected from 2018. The experimental results showed that the average absolute error in the test days was 6.8 min, and the classification accuracy with a 15 min threshold for a two-hour forecast horizon was 89.5%. The performance of our model outperformed that of existing research. Additionally, the positive effect of introducing parameter models and the negative impact of increasing the prediction horizon on the prediction performance were further studied.

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Section: Modeling Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction of air traffic delays: An agent-based model introducing refined parameter estimation methods

Wang

Yang

et al. 2021

PLoS ONE

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“…ABMS has been used to address a wide number of different ATM problems in several research projects within the SESAR Exploratory Research framework, such as ELSA (Bongiorno et al, 2015),ACCESS (Herranz, et al, 2015), TREE (Ciruelos et al, 2015), CASSIOPEIA (Molina et al, 2014), MAREA (Stroeve et al, 2013), SPAD (Pasquini et al, 2013), EMERGIA (Blom & Bakker, 2016), and SAFECORAM (Palumbo et al, 2015). In these projects, ABMS is used (usually in combination with other techniques) either as an analysis tool to understand emergent behaviours of ATM systems (as in CASSIOPEIA, ELSA, and EMERGIA), or to study resilience and disturbance propagation (as in MAREA, SPAD, TREE, and SAFECORAM), or as a tool to determine airport slot auctioning and allocation (as in ACCESS).…”

Section: Literature Reviewmentioning

confidence: 99%

Support to Design for Air Traffic Management: An Approach with Agent-Based Modelling and Evolutionary Search

Gigante¹,

Palumbo²,

Pascarella³

et al. 2021

IJAAA

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“…In the recent years, some attempts have been made within the SESAR Program. Many exploratory research projects (e.g., ELSA [14], ACCESS [15], TREE [16], CASSIOPEIA [17], MAREA [18], SPAD [19], EMERGIA [20]) have adopted the agent-based modeling paradigm to address a wide number of different ATM problems. In these projects, the agent-based simulation is used (usually in combination with other techniques) either as an analysis tool to understand emergent behaviors of the ATM system or to study resilience and disturbance propagation, or even as a tool to determine airport slot auctioning and allocation.…”

Section: Related Workmentioning

confidence: 99%

Simulation-Based Evolutionary Optimization of Air Traffic Management

Pellegrini¹,

Sanzo²,

Beatrice³

et al. 2020

IEEE Access

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In the context of aerospace engineering, the optimization of processes may often require to solve multi-objective optimization problems, including mixed variables, multi-modal and non-differentiable quantities, possibly involving highly-expensive objective function evaluations. In Air Traffic Management (ATM), the optimization of procedures and protocols becomes even more complicated, due to the involvement of human controllers, which act as final decision points in the control chain. In this article, we propose the use of computational intelligence techniques, such as Agent-Based Modelling and Simulation (ABMS) and Evolutionary Computing (EC), to design a simulation-based distributed architecture to optimize control plans and procedures in the context of ATM. We rely on Agent-Based fast-time simulations to carry out offline what-if analysis of multiple scenarios, also taking into account human-related decisions, during the strategic or pre-tactical phases. The scenarios are constructed using real-world traffic data traces, while multiple optimization variables governed by an EC algorithm allow to explore the search space to identify the best solutions. Our optimization approach relies on ad-hoc multiobjective performance metrics which allow to assess the goodness of the control of aircraft and air traffic regulations. We present experimental results which prove the viability of our approach, comparing them with real-world data traces, and proving their meaningfulness from an Air Traffic Control perspective.

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An Agent-Based Approach for the Design of the Future European Air Traffic Management System

Cited by 3 publications

References 3 publications

Prediction of air traffic delays: An agent-based model introducing refined parameter estimation methods

Prediction of air traffic delays: An agent-based model introducing refined parameter estimation methods

Support to Design for Air Traffic Management: An Approach with Agent-Based Modelling and Evolutionary Search

Simulation-Based Evolutionary Optimization of Air Traffic Management

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