機場跑道容量推估與延誤分析模式之研究

Abstract

機場跑道容量推估為進行機場流量管理之基礎，其是否精確對流量管理之成效影響至鉅。其次，機場班機起降延誤程度不但影響旅客及航空公司之服務品質，更是機場流量管理績效好壞之重要指標。因此，本文之研究目的有四：1.發展跑道容量推估模式以評估目前跑道之容量是否有充份使用。2.釐清航機延誤之意義與衡量方式，發展一套有效的延誤分析模式，以便能反應流量管理績效優劣，並以此績效有效管理航機之起降運作。3.排除機場容量限制所產生的延誤，公平評估航空公司班機準點績效。4.作為班表規劃/檢核、剩餘容量使用之研究基礎與參考。 首先，基於機場運作安全與效率之原則，就松山機場航機起降時間資料，篩選出適宜分析的樣本組數，進行不同航機起降型態所對應航機隔離間距之統計分析，並以此推估之隔離間距值，運用數學規劃方式，考慮現況航機起降需求，予以求解最佳之起降型態組合及相對應之機場容量。本研究所推估之跑道容量除可作為天候良好狀況下，現有跑道可允許起降架次之依據外，並可作為機場流量管理中航機隔離間距之參考，同時亦可提供機場時間帶安排策略之參考。 其次，在釐清延誤之意義及衡量方式，除引入技術性延誤與班表系統擴散性延誤來衡量流量管理績效外，並在考量跑道及進離場航路容量的限制下，藉由數學規劃方式構建一理論性的靜態最佳化延誤分析模式。透過模擬不同服務法則來應證本延誤分析模型於流量管理績效評估之適用性。就本研究之樣本結果顯示，對於每架航機之延誤而言，理論模式會較先到先服務法則高估0.71~1.1分鐘；與到達航機優先服務法則相較，理論模式可能低估或高估，其值介於-0.11~0.24分鐘之間，由於最佳化模式之理論值與先到先服務及到達航機優先服務法則所模擬之結果間具有相當高之相關性，經由迴歸分析，以最佳化模式所分析之延誤進行先到先服務及到達航機優先法則下總延誤之推估，結果顯示預測值全數皆落在95%信賴區間，預測能力相當良好。 至於本研究所提之班機準點績效之評估方式，考量機場管理單位在實施流量管制或因機場容量限制下，各機場各時點所能提供服務水準等級的差異，以排除航機實際延誤所承擔之技術性延誤的影響，由實例個案顯示此種評估方式不但可以免除航空公司不因其總班次數多寡而影響其準點衡量上之公平性，更可明顯反映出該航空公司本身之作業績效的好壞。 最後，為達到尖峰小時跑道容量最大使用與延誤最小的目標，建議現行班表合理規劃每個時點長度與安排起降型態與架次量的改善。並就新增班表可行性建立一分析評估步驟與方式，以提供時間帶安排策略之參考。

Runway capacity estimation is the basic foundation for air traffic flow management in airport. The level of flight delays at airports affects not only passengers and the quality of airline service, but it also the performance of air traffic management. Therefore, there are four objects in this study, which estimate runway capacity, assess flight technical delay, evaluate airlines’ punctuality performance, and modify schedule timetable. First, this research is not only applying the statistics to analyze the separated value between take-off and landing craft types but also using mathematical programming to consider the demand of take-off and landing, the constrict of the relation between take-off and landing type, to estimate take-off /landing composed type and the optimal runway capacity. Our study is suitable to estimate runway capacity in the good weather not only estimating the frequency between take-off and landing aircraft on runway but also making a strategy for time-slot management problem. Second, this study seeks to clarify the causes, as well as measurements of approach delays. Furthermore, this study also examines the impacts of technical delays and scheduled system delays in measuring the performance of air traffic management. We also consider both the capacity constraints of a runway and the arrival/landing approach routes, using mathematical planning to construct a static-and-theoretical delay analysis of the optimization model. The availability of this model is clarified and tested to evaluate the performance of air traffic management by means of simulating the different service rules of actual flight delays. The outcome of the example shows that the estimate of the optimization model for each aircraft delay is higher than the estimate using the FIFS rule. However, the optimization model for each aircraft delay is probably either higher or lower than that for the arrival priority rule. The delay value of both FIFS and arrival priority are highly related to the delay value of the optimization model. By means of regression analysis and testing, the outcome of forecasted numbers are all within a 95% confidence interval. This proves the efficacy of the optimization model for correctly estimating actual flight delays. Third, this study introduces both the technical delay and timetable system delay to evaluate and modify the airlines’ punctuality. A model for evaluating the performance of airlines’ punctuality is proposed. The punctuality should not be measured by 15 minutes. It should take the constraints of airport capacity and flight timetable put consideration. At last, this study can assist timetable planning of minimum delays, choose the suitable time points and arrange suitable aircraft numbers and sequences, also proposes the planning strategies of scheduled timetable and enhance the value of available surplus capacity to analyze and arrange vacant rule of flight take-off/landing runway on the timetable.