scholarly journals A Python Toolbox for Processing Air Traffic Data: A Use Case with Trajectory Clustering

10.29007/sf1f ◽  
2019 ◽  
Author(s):  
Xavier Olive ◽  
Luis Basora
Keyword(s):  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Traffic Data ◽  
Clustering Methods ◽  
Trajectory Clustering ◽  
Flight Parameters ◽  
Aircraft Trajectories ◽  
Python Programming ◽  
Different Sources

Problems tackled by researchers and data scientists in aviation and air traffic management (ATM) require manipulating large amounts of data representing trajectories, flight parameters and geographical descriptions of the airspace they fly through. The traffic library for the Python programming language defines an interface to usual processing and data analysis methods to be applied on aircraft trajectories and airspaces. This paper presents how traffic accesses different sources of data, leverages processing methods to clean, filter, clip or resample trajectories, and compares trajectory clustering methods on a sample dataset of trajectories above Switzerland.

scholarly journals Air Traffic Prediction as a Video Prediction Problem Using Convolutional LSTM and Autoencoder

Aerospace ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 301
Author(s):  
Hyewook Kim ◽  
Keumjin Lee
Keyword(s):  
Loss Function ◽  
Traffic Management ◽  
Short Term Memory ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Function Technique ◽  
Traffic Data ◽  
Short Term ◽  
Long Short Term Memory ◽  
New Framework

Accurate prediction of future air traffic situations is an essential task in many applications in air traffic management. This paper presents a new framework for predicting air traffic situations as a sequence of images from a deep learning perspective. An autoencoder with convolutional long short-term memory (ConvLSTM) is used, and a mixed loss function technique is proposed to generate better air traffic images than those obtained by using conventional L1 or L2 loss function. The feasibility of the proposed approach is demonstrated with real air traffic data.

scholarly journals A framework for integrated terminal airspace design

2019 ◽  
Vol 123 (1263) ◽  
pp. 567-585
Author(s):  
T.A. Granberg ◽  
T. Polishchuk ◽  
V. Polishchuk ◽  
C. Schmidt
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Traffic Management ◽  
Integrated Design ◽  
Route Planning ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Mixed Integer ◽  
Simultaneous Design ◽  
Aircraft Trajectories

ABSTRACTRoute planning and airspace sectorisation are two central tasks in air traffic management. Traditionally, the routing and sectorisation problems were considered separately, with aircraft trajectories serving as input to the sectorisation problem and, reciprocally, sectors being part of the input to the path finding algorithms.In this paper we propose a simultaneous design of routes and sectors for a transition airspace. We compare two approaches for this integrated design: one based on mixed integer programming, and one Voronoi-based model that separates potential “hotspots” of controller activity resulting from the terminal routes.We apply our two approaches to the design of Stockholm Terminal Maneuvering Area.

Safety Culture and Safety-Relevant Behavior in Air Traffic Management

2015 ◽  
Vol 5 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Michaela Schwarz ◽  
K. Wolfgang Kallus
Keyword(s):  
Safety Culture ◽  
Traffic Management ◽  
Service Providers ◽  
Five Factor Model ◽  
Principal Component ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Psychometric Validation ◽  
Safety Attitudes ◽  
Culture Development

Since 2010, air navigation service providers have been mandated to implement a positive and proactive safety culture based on shared beliefs, assumptions, and values regarding safety. This mandate raised the need to develop and validate a concept and tools to assess the level of safety culture in organizations. An initial set of 40 safety culture questions based on eight themes underwent psychometric validation. Principal component analysis was applied to data from 282 air traffic management staff, producing a five-factor model of informed culture, reporting and learning culture, just culture, and flexible culture, as well as management’s safety attitudes. This five-factor solution was validated across two different occupational groups and assessment dates (construct validity). Criterion validity was partly achieved by predicting safety-relevant behavior on the job through three out of five safety culture scores. Results indicated a nonlinear relationship with safety culture scales. Overall the proposed concept proved reliable and valid with respect to safety culture development, providing a robust foundation for managers, safety experts, and operational and safety researchers to measure and further improve the level of safety culture within the air traffic management context.

A Simulation Environment for Analyzing the Impact of Volcanic Ash on Trajectory-Based Air Traffic Management

2013 ◽  
Author(s):  
Angela Schmitt ◽  
Ruzica Vujasinovic ◽  
Christiane Edinger ◽  
Julia Zillies ◽  
Vilmar Mollwitz
Keyword(s):  
Traffic Management ◽  
Volcanic Ash ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Simulation Environment ◽  
The Impact

Withdrawal: Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

2020 ◽  
Author(s):  
Robert D. Windhorst ◽  
Shannon Zelinski ◽  
Todd A. Lauderdale ◽  
Alexander Sadovsky ◽  
Yung-Cheng Chu ◽  
...  
Keyword(s):  
Traffic Management ◽  
Air Traffic Management ◽  
Simulation System ◽  
Air Traffic ◽  
Management Systems ◽  
Initial Validation
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