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Databases and Information Systems in the AI Era: Contributions from ADBIS, TPDL and EDA 2020 Workshops and Doctoral Consortium Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Supervised Machine Learning Model to Help Controllers Solving Aircraft Conflicts

Author : Md Siddiqur Rahman

Published in: ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium

Publisher: Springer International Publishing

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Abstract

When two or more airplanes find themselves less than a minimum distance apart on their trajectory, it is called a conflict situation. To solve a conflict, air traffic controllers use various types of information and decide on actions pilots have to apply on the fly. With the increase of the air traffic, the controllers’ workload increases; making quick and accurate decisions is more and more complex for humans. Our research work aims at reducing the controllers’ workload and help them in making the most appropriate decisions. More specifically, our PhD goal is to develop a model that learns the best possible action(s) to solve aircraft conflicts based on past decisions or examples. As the first steps in this work, we present a Conflict Resolution Deep Neural Network (CR-DNN) model as well as the evaluation framework we will follow to evaluate our model and a data set we developed for evaluation.

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Metadata
Title
Supervised Machine Learning Model to Help Controllers Solving Aircraft Conflicts
Author
Md Siddiqur Rahman
Copyright Year
2020
Book
ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium

Print ISBN: 978-3-030-55813-0

Electronic ISBN: 978-3-030-55814-7

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-55814-7_31

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