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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F12%3A00196958%21RIV13-MSM-21230___
rdf:type
skos:Concept n15:Vysledek
rdfs:seeAlso
http://www.aaai.org/ocs/index.php/IAAI/IAAI-12/paper/view/4873
dcterms:description
The Next-Generation Transportation program coordinates the evolution and transformation of the current air-traffic management (ATM) system for the National Airspace System (NAS). Currently the NAS has a limited capacity and cannot handle the increasing future air traffic demands. However, before newly proposed ATM concepts are deployed they must be rigorously evaluated under realistic conditions. This paper presents AGENTFLY, an emerging NAS-wide highfidelity multi-agent ATM simulator with precise emulation of the human controller operation workload model and human-system interaction. The simulator is validated using a flight scenario developed by the U.S. Federal Aviation Administration that is based on real data. We present preliminary results focusing on the accuracy of the simulated controllers within AGENTFLY. The Next-Generation Transportation program coordinates the evolution and transformation of the current air-traffic management (ATM) system for the National Airspace System (NAS). Currently the NAS has a limited capacity and cannot handle the increasing future air traffic demands. However, before newly proposed ATM concepts are deployed they must be rigorously evaluated under realistic conditions. This paper presents AGENTFLY, an emerging NAS-wide highfidelity multi-agent ATM simulator with precise emulation of the human controller operation workload model and human-system interaction. The simulator is validated using a flight scenario developed by the U.S. Federal Aviation Administration that is based on real data. We present preliminary results focusing on the accuracy of the simulated controllers within AGENTFLY.
dcterms:title
Multi-Agent Simulation of En-Route Human Air-Traffic Controller Multi-Agent Simulation of En-Route Human Air-Traffic Controller
skos:prefLabel
Multi-Agent Simulation of En-Route Human Air-Traffic Controller Multi-Agent Simulation of En-Route Human Air-Traffic Controller
skos:notation
RIV/68407700:21230/12:00196958!RIV13-MSM-21230___
n15:predkladatel
n22:orjk%3A21230
n4:aktivita
n14:V
n4:aktivity
V
n4:dodaniDat
n12:2013
n4:domaciTvurceVysledku
n16:2490013 n16:9738452 n16:9710299
n4:druhVysledku
n6:D
n4:duvernostUdaju
n17:S
n4:entitaPredkladatele
n9:predkladatel
n4:idSjednocenehoVysledku
152300
n4:idVysledku
RIV/68407700:21230/12:00196958
n4:jazykVysledku
n5:eng
n4:klicovaSlova
air-traffic management; human modeling; multi-agent simulation
n4:klicoveSlovo
n11:human%20modeling n11:multi-agent%20simulation n11:air-traffic%20management
n4:kontrolniKodProRIV
[B8DF9590E026]
n4:mistoKonaniAkce
Toronto
n4:mistoVydani
Menlo Park, California
n4:nazevZdroje
Proceedings of the 24th Innovative applications of artificial intelligence conference
n4:obor
n20:JC
n4:pocetDomacichTvurcuVysledku
3
n4:pocetTvurcuVysledku
6
n4:rokUplatneniVysledku
n12:2012
n4:tvurceVysledku
Nguyen, D. N. Volf, Přemysl Cannon, C. T. Regli, W.C. Šišlák, David Pěchouček, Michal
n4:typAkce
n10:WRD
n4:zahajeniAkce
2012-07-22+02:00
s:numberOfPages
6
n13:hasPublisher
AAAI Press
n7:isbn
978-1-57735-568-7
n18:organizacniJednotka
21230