scholarly journals A Gaussian process based decision support tool for air traffic management

2017 ◽  
Author(s):  
Willem J. Eerland ◽  
Simon Box ◽  
Hans Fangohr ◽  
Andras Sobester
Keyword(s):  
Decision Support ◽  
Gaussian Process ◽  
Traffic Management ◽  
Decision Support Tool ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Support Tool

scholarly journals Identifying Operational Benefits of the Arrival Management System – A KPI-Based Experimental Method by Evaluating Radar Trajectories

2021 ◽  
Vol 33 (5) ◽  
pp. 633-645
Author(s):  
Songwei Liu ◽  
Junfeng Zhang ◽  
Zihan Peng ◽  
Haipeng Guo ◽  
Anle Pi
Keyword(s):  
Traffic Management ◽  
Decision Support Tool ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Support Tool ◽  
Performance Improvements ◽  
System A ◽  
Original Intention ◽  
Air Traffic Controllers

The arrival management (AMAN) system is a decision support tool for air traffic controllers to establish and maintain the landing sequence for arrival aircraft. The original intention of designing the AMAN system is to improve the efficiency of air traffic management (ATM), but few studies are investigating the operational benefits of this system based on key performance indicators (KPIs) and evaluating actual data in a real-time environment. The main purpose of this paper is to propose a KPI based transferable comparative analysis method for identifying the operational benefits of the AMAN through radar trajectories. Firstly, six KPIs are established from a joint study of the mainstream ATM performance frameworks worldwide. Secondly, appropriate evaluation technique approaches are determined according to the characteristics of each KPI. Finally, a Chinese metropolitan airport is taken for the case study, and three periods are defined to form data samples with high similarity for comparative experiments. The results validate the feasibility of the proposed method and find comprehensive performance improvements in arrival operations under the effects of the AMAN system.

scholarly journals Neural Network-Based Aircraft Conflict Prediction in Final Approach Maneuvers

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1708
Author(s):  
Rafael Casado ◽  
Aurelio Bermúdez
Keyword(s):  
Neural Network ◽  
Traffic Management ◽  
Autonomous Navigation ◽  
Decision Support Tool ◽  
Air Traffic ◽  
Navigation Systems ◽  
Support Tool ◽  
Final Approach ◽  
Aircraft Trajectories ◽  
Available Information

Conflict detection and resolution is one of the main topics in air traffic management. Traditional approaches to this problem use all the available information to predict future aircraft trajectories. In this work, we propose the use of a neural network to determine whether a particular configuration of aircraft in the final approach phase will break the minimum separation requirements established by aviation rules. To achieve this, the network must be effectively trained with a large enough database, in which configurations are labeled as leading to conflict or not. We detail the way in which this training database has been obtained and the subsequent neural network design and training process. Results show that a simple network can provide a high accuracy, and therefore, we consider that it may be the basis of a useful decision support tool for both air traffic controllers and airborne autonomous navigation systems.

Analysis of Air Traffic Control Command Entries and the Impact on Decision Support Tool Performance

2014 ◽  
Vol 22 (1) ◽  
pp. 1-20
Author(s):  
Jasenka Rakas ◽  
Michael Seelhorst ◽  
Bona Bernard Niu ◽  
Jeffrey Tom ◽  
Confesor Santiago
Keyword(s):  
Decision Support ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Decision Support Tool ◽  
Air Traffic ◽  
Support Tool ◽  
Tool Performance ◽  
Control Command ◽  
The Impact
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