Pemberian Expected Approach Time (EAT) pada Pesawat Arrival Berdasarkan Average Time Interval (ATI) di Bandara Sultan Thaha Jambi

2021 ◽  
Vol 4 (1) ◽  
pp. 32-38
Author(s):  
Ahmad Bahrawi

Bandar Udara Sultan Thaha approach clearance yang diberikan untuk pesawat arrival belum memuat informasi berupa Expected Approach Time (EAT) yang merupakan perkiraan waktu yang diberikan oleh Air Traffic Controller (ATC) kepada pesawat arrival yang mengalami delay untuk meninggalkan holding fix yang kemudian melanjutkan approach untuk landing. Kondisi tersebut menyebabkan kurang efisiennya manoeuver pesawat karena pilot belum mengetahui perkiraan waktu untuk melakukan approach. Pemberian Expected Approach Time (EAT) terhadap pesawat arrival dapat mempengaruhi kelancaran dan keamanan lalu lintas penerbangan. Dalam keadaan tertentu terjadi communication failure terhadap pesawat arrival, maka seorang pilot akan mengikuti instruksi EAT yang terakhir diberikan. Seperti yang kita ketahui, kejadian-kejadian communication faiure tidak ada yang dapat mengetahui kapan akan terjadi dan hal tersebut tidak dapat dihindari. Seorang Controller hanya dapat mengurangi resiko konflik dari terjadinya hal tersebut dengan memberikan pelayanan lalu lintas penerbangan dengan cara memberikan EAT pada saat pesawat tersebut melakukan first contact. Jika diberikan EAT, pilot mendapatkan kepastian sehingga tidak lagi menanyakan posisi traffic yang ada di depanny. Pilot juga dapat mengatur kecepatan pesawat sehingga mengurangi holding jika memang diharuskan untuk holding. Oleh karena itu, pemberian EAT terhadap pesawat arrival mempengaruhi kelancaran dan keamanan lalu lintas penerbangan.

2013 ◽  
Vol 3 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Yvonne Pecena ◽  
Doris Keye ◽  
Kristin Conzelmann ◽  
Dietrich Grasshoff ◽  
Peter Maschke ◽  
...  

The job of an air traffic controller (ATCO) is very specific and demanding. The assessment of potential suitable candidates requires a customized and efficient selection procedure. The German Aerospace Center DLR conducts a highly selective, multiple-stage selection procedure for ab initio ATCO applicants for the German Air Navigation Service Provider DFS. Successful applicants start their training with a training phase at the DFS Academy and then continue with a unit training phase in live traffic. ATCO validity studies are scarcely reported in the international scientific literature and have mainly been conducted in a military context with only small and male samples. This validation study encompasses the data from 430 DFS ATCO trainees, starting with candidate selection and extending to the completion of their training. Validity analyses involved the prediction of training success and several training performance criteria derived from initial training. The final training success rate of about 79% was highly satisfactory and higher than that of other countries. The findings demonstrated that all stages of the selection procedure showed predictive validity toward training performance. Among the best predictors were scores measuring attention and multitasking ability, and ratings on general motivation from the interview.


2014 ◽  
Author(s):  
Dan Chiappe ◽  
Thomas Strybel ◽  
Kim-Phuong Vu ◽  
Lindsay Sturre

2011 ◽  
Author(s):  
Jarek Krajewski ◽  
David Sommer ◽  
Sebastian Schnieder ◽  
Martin Golz

Author(s):  
Jurriaan d'Engelbronner ◽  
Max Mulder ◽  
Marinus Van Paassen ◽  
Sebastiaan De Stigter ◽  
Hans Huisman

2018 ◽  
Vol 54 (Supplement) ◽  
pp. 1F4-2-1F4-2
Author(s):  
Hisae AOYAMA ◽  
Daisuke KARIKAWA

Author(s):  
Mirko Stojadinović

Modern computers solve many problems by using exact methods, heuristic methods and very often by using their combination. Air Traffic Controller Shift Scheduling Problem has been successfully solved by using SAT technology (reduction to logical formulas) and several models of the problem exist. We present a technique for solving this problem that is a combination of SAT solving and meta-heuristic method hill climbing, and consists of three phases. First, SAT solver is used to generate feasible solution. Then, the hill climbing is used to improve this solution, in terms of number of satisfied wishes of controllers. Finally, SAT solving is used to further improve the found solution by fixing some parts of the solution. Three phases are repeated until optimal solution is found. Usage of exact method (SAT solving) guarantees that the found solution is optimal; usage of meta-heuristic (hill climbing) increases the efficiency in finding good solutions. By using these essentially different ways of solving, we aim to use the best from both worlds. Results indicate that this hybrid technique outperforms previously most efficient developed techniques.


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