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題名:即時飛航流量管理系統之建立與管理策略研擬
作者:劉仲祥
作者(外文):Jong-Shyang Liou
校院名稱:國立成功大學
系所名稱:交通管理學系碩博士班
指導教授:戴佐敏
學位類別:博士
出版日期:2004
主題關鍵詞:類神經網路模擬最佳化即時飛航流量管理系統real-time air traffic flow management (ATFM)artificial neural networkoptimizationsimulation
原始連結:連回原系統網址new window
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  本研究根據國內特性,建立一即時飛航流量管理系統,此系統接收即時資訊,可針對多機場、多時段之流量與容量進行預測,並據此建議各機場之起飛額度。此系統主要包括航機動態監控、流量預測、機場容量預測、以及流量管理最佳化模式。由於無法於實際之飛航系統進行測試,本研究將此即時飛航流量管理系統與一微觀模擬模式(ANS2.0)加以整合,模擬模式可代表實際飛航系統之運作,因此此一即時飛航流量管理系統可在模擬模式內進行各種情境之測試。
  本研究針對不同監視系統,測試即時飛航流管理系統之運作績效,所考慮的監視系統包括:民航電報、雷達資料處理(Radar Data Processor, RDP)、以及通訊、導航、監視與飛航管理系統(Comminication Nevigation Surveillance / Air Traffic Management, CNS/ATM)。在流量預測方面,本研究採用類神經網路預測航機起飛及降落之時間,將個別航機之資訊加以彙整,即可得到未來各時段之起降航機數量;在容量預測方面,則根據氣象預報,決定跑道之起降容量;流量最佳化模組則以最短路徑網路問題構建最佳化模式,並以successive shortest path algorithm求解。
  測試結果顯示,各機場之起降容量若多加一緩衝值(buffer),可減少空中等候之情形,在到場延滯方面亦有較佳之績效。另外,針對不同監視系統的比較,在越充足的資訊的情況下,即能越有效地控制空中等候。由於求解一次的時間在3分鐘之內,因此可即時得到一建議之策略,供航管人員參考。
  This research develops a real-time air traffic flow management (ATFM) program. The system considered in this research is multi-airport and multi-period. This program will predict the 15-minute traffic demand, traffic flow, and capacity for certain time frame in advance and determine departure quota of each airport based on the predicted flow and capacity. The ATFM program consists of four modules: Information Receive Module, Flow Prediction, Capacity Prediction, and Flow Optimization Model. It’s very unlikely to evaluate the performance of this ATFM program in real system. This research incorporates a microscopic simulation model to represent the airspace operation system and tests the air traffic flow management program under various scenarios.
  The performae of various surveillance systems, including Flight Data Processing (FDP), Radar Data Processing(RDP), and Communication Nevigation Surveillance (CNS), is tested and compared. The methodology of artificial neural network, ANN, is employed to better predict the flight departure and arrival times. The prediction of the flight departure and arrival times is used to predict traffic flow. The capacities of airports are estimated baed on weather information. A minimum cost flow problem is formulated to determine the optimal departure quota for each airport. Also, the successive shortest path algorithm is developed to solve this flow optimization problem.
  This ATFM program is tested for the aviation network in Taiwan. The result shows that the ATFM program with buffer concept can significantly reduce the airborne holding time, but only slightly increase the arrival delay. The performance comparison of varous surveillance systems shows that more accuate information the survailance system provides, the better performance the ATFM will have. In addition, the total computation time for an interation takes less than 3 minutes in a personal computer, which is quite promising for real time application.
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