计算机科学与探索
計算機科學與探索
계산궤과학여탐색
JOURNAL OF FRONTIERS OF COMPUTER SCIENCE & TECHNOLOGY
2013年
3期
247-253
,共7页
梁海军%杨红雨%杨波%刘洪%陈正茂
樑海軍%楊紅雨%楊波%劉洪%陳正茂
량해군%양홍우%양파%류홍%진정무
仿真%空中交通管理%流量管理%容量
倣真%空中交通管理%流量管理%容量
방진%공중교통관리%류량관리%용량
simulation%air traffic control%traffic flow management%capacity
介绍了一种用于空中交通流量管理系统(traffic flow management system,TFMS)中流量仿真的虚拟管制员模型(virtual controller model,VCM).流量管理主要关注空域流量变化趋势,以及当流量需求过大或者空域容量不足时,流量管制员如何采取流量控制措施平衡流量与容量.为了预测未来一段时间内扇区流量与容量是否平衡,并评估流量控制措施是否有效,提出了虚拟管制员模型.该模型根据扇区空域结构进行建模,使用扇区容量、流量控制措施对航班进行调配,计算调配后的流量与容量匹配程度.将虚拟管制员模型用于流量管理系统中,并使用一天的真实历史数据进行验证,对使用流量仿真模型预测的扇区流量和真实的数据进行对比实验,验证了虚拟管制员模型的预测能力.该方法适用于空中交通流量管理系统.
介紹瞭一種用于空中交通流量管理繫統(traffic flow management system,TFMS)中流量倣真的虛擬管製員模型(virtual controller model,VCM).流量管理主要關註空域流量變化趨勢,以及噹流量需求過大或者空域容量不足時,流量管製員如何採取流量控製措施平衡流量與容量.為瞭預測未來一段時間內扇區流量與容量是否平衡,併評估流量控製措施是否有效,提齣瞭虛擬管製員模型.該模型根據扇區空域結構進行建模,使用扇區容量、流量控製措施對航班進行調配,計算調配後的流量與容量匹配程度.將虛擬管製員模型用于流量管理繫統中,併使用一天的真實歷史數據進行驗證,對使用流量倣真模型預測的扇區流量和真實的數據進行對比實驗,驗證瞭虛擬管製員模型的預測能力.該方法適用于空中交通流量管理繫統.
개소료일충용우공중교통류량관리계통(traffic flow management system,TFMS)중류량방진적허의관제원모형(virtual controller model,VCM).류량관리주요관주공역류량변화추세,이급당류량수구과대혹자공역용량불족시,류량관제원여하채취류량공제조시평형류량여용량.위료예측미래일단시간내선구류량여용량시부평형,병평고류량공제조시시부유효,제출료허의관제원모형.해모형근거선구공역결구진행건모,사용선구용량、류량공제조시대항반진행조배,계산조배후적류량여용량필배정도.장허의관제원모형용우류량관리계통중,병사용일천적진실역사수거진행험증,대사용류량방진모형예측적선구류량화진실적수거진행대비실험,험증료허의관제원모형적예측능력.해방법괄용우공중교통류량관리계통.
This paper develops a new paradigm for building virtual controller model (VCM) for traffic flow simulator, which is applied to traffic flow management system (TFMS). The problem of interest is focused on the flow tendency of airspace and how flow control measures are applied by air traffic controllers when demand is overage or capacity shortfalls in the airspace. The paper presents the virtual controller model in order to estimate the balance between the traffic flow and the capacity of sector in future, and assess the effect of flow control measures. The VCM is modeled on the sector airspace system, uses sector capacity and flow control measures to adjust flights, and calculates the matching degree between flow and capacity. Numerical results are presented and illustrated by applying them to air traffic data for a typical day in the traffic flow management system. The results show that the predictive capabilities of the model are successfully validated by showing a comparison between real flow data and simulated sector flow, making this method appropriate for traffic flow management system.