Analysing temporal performance profiles of UAV operators using time series clustering

Rodríguez-Fernández, Victor, Menéndez, Héctor D. ORCID logoORCID: and Camacho, David ORCID logoORCID: (2017) Analysing temporal performance profiles of UAV operators using time series clustering. Expert Systems with Applications, 70 . pp. 103-118. ISSN 0957-4174 [Article] (doi:10.1016/j.eswa.2016.10.044)

PDF - Final accepted version (with author's formatting)
Available under License Creative Commons Attribution-NonCommercial-NoDerivatives 4.0.

Download (914kB) | Preview


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.

Item Type: Article
Keywords (uncontrolled): UAVs, UAV operators, time series clustering performance measures, simulation-based training
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 28799
Notes on copyright: © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
Useful Links:
Depositing User: Hector Menendez Benito
Date Deposited: 02 Feb 2020 20:39
Last Modified: 29 Nov 2022 21:07

Actions (login required)

View Item View Item


Activity Overview
6 month trend
6 month trend

Additional statistics are available via IRStats2.