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김소윤,이금진,Kim, Soyeun,Lee, Keumjin 한국항공운항학회 2016 한국항공운항학회지 Vol.24 No.4
The departure flow management is the planning tool to optimize the schedule of the departure aircraft and allows them to join smoothly into the overhead traffic flow. To that end, the arrival time prediction to the merge point for the cruising aircraft is necessary to determined. This paper proposes a trajectory prediction model for the cruising aircraft based on the machine learning approach. The proposed method includes the trajectory vectored from the procedural route and is applied to the historical data to evaluate the prediction performances.
Point-Merge 절차를 이용한 도착 스케줄링 및 조언 정보 생성 알고리즘 개발
홍성권,김소윤,전대근,은연주,오은미,Hong, Sungkweon,Kim, Soyeun,Jeon, Daekeun,Eun, Yeonju,Oh, Eun-Mi 한국항공운항학회 2017 한국항공운항학회지 Vol.25 No.3
This paper proposes arrival scheduling and advisory generation algorithms which can be used in the terminal airspace with Point-Merge procedures. The proposed scheduling algorithm consists of two steps. In the first step, the algorithm computes aircraft schedules at the entrance of the Point-Merge sequencing legs based on First-Come First-Served(FCFS) strategy. Then, in the second step, optimal sequence and schedules of all aircraft at the runway are computed using Multi-Objective Dynamic Programming(MODP) method. Finally, the advisories that have to be provided to the air traffic controllers are generated. To demonstrate the proposed algorithms, the simulation was conducted based on Jeju International Airport environments.