Analysing temporal performance profiles of UAV operators using time series clustering

Article


Rodríguez-Fernández, V., Menéndez, H. and Camacho, D. 2017. Analysing temporal performance profiles of UAV operators using time series clustering. Expert Systems with Applications. 70, pp. 103-118. https://doi.org/10.1016/j.eswa.2016.10.044
TypeArticle
TitleAnalysing temporal performance profiles of UAV operators using time series clustering
AuthorsRodríguez-Fernández, V., Menéndez, H. and Camacho, D.
Abstract

The continuing growth in the use of Unmanned Aerial Vehicles (UAVs) is causing an important social step forward in the performance of many sensitive tasks, reducing both human and economical risks. The work of UAV operators is a key aspect to guarantee the success of this kind of tasks, and thus UAV operations are studied in many research fields, ranging from human factors to data analysis and machine learning. The present work aims to describe the behaviour of operators over time using a profile-based model where the evolution of the operator performance during a mission is the main unit of measure. In order to compare how different operators act throughout a mission, we describe a methodology based of multivariate-time series clustering to define and analyse a set of representative temporal performance profiles. The proposed methodology is applied in a multi-UAV simulation environment with inexperienced operators, obtaining a fair description of the temporal behavioural patterns followed during the course of the simulation.

KeywordsUAVs, UAV operators, time series clustering performance measures, simulation-based training
LanguageEnglish
PublisherElsevier
JournalExpert Systems with Applications
ISSN0957-4174
Publication dates
Online28 Oct 2016
Print15 Mar 2017
Publication process dates
Deposited02 Feb 2020
Accepted18 Oct 2016
Output statusPublished
Accepted author manuscript
License
Copyright Statement

© 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

Digital Object Identifier (DOI)https://doi.org/10.1016/j.eswa.2016.10.044
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