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Vehicle Driver Monitoring through the Statistical Process Control

This paper proposes the use of the Statistical Process Control (SPC), more specifically, the Exponentially Weighted Moving Average method, for the monitoring of drivers using approaches based on the vehicle and the driver’s behavior. Based on the SPC, we propose a method for the lane departure detec...

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Detalles Bibliográficos
Autores principales: Assuncao, Arthur N., Aquino, Andre L. L., Câmara de M. Santos, Ricardo C., Guimaraes, Rodolfo L. M., Oliveira, Ricardo A. R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678967/
https://www.ncbi.nlm.nih.gov/pubmed/31336711
http://dx.doi.org/10.3390/s19143059
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author Assuncao, Arthur N.
Aquino, Andre L. L.
Câmara de M. Santos, Ricardo C.
Guimaraes, Rodolfo L. M.
Oliveira, Ricardo A. R.
author_facet Assuncao, Arthur N.
Aquino, Andre L. L.
Câmara de M. Santos, Ricardo C.
Guimaraes, Rodolfo L. M.
Oliveira, Ricardo A. R.
author_sort Assuncao, Arthur N.
collection PubMed
description This paper proposes the use of the Statistical Process Control (SPC), more specifically, the Exponentially Weighted Moving Average method, for the monitoring of drivers using approaches based on the vehicle and the driver’s behavior. Based on the SPC, we propose a method for the lane departure detection; a method for detecting sudden driver movements; and a method combined with computer vision to detect driver fatigue. All methods consider information from sensors scattered by the vehicle. The results showed the efficiency of the methods in the identification and detection of unwanted driver actions, such as sudden movements, lane departure, and driver fatigue. Lane departure detection obtained results of up to 76.92% (without constant speed) and 84.16% (speed maintained at ≈60). Furthermore, sudden movements detection obtained results of up to 91.66% (steering wheel) and 94.44% (brake). The driver fatigue has been detected in up to 94.46% situations.
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spelling pubmed-66789672019-08-19 Vehicle Driver Monitoring through the Statistical Process Control Assuncao, Arthur N. Aquino, Andre L. L. Câmara de M. Santos, Ricardo C. Guimaraes, Rodolfo L. M. Oliveira, Ricardo A. R. Sensors (Basel) Article This paper proposes the use of the Statistical Process Control (SPC), more specifically, the Exponentially Weighted Moving Average method, for the monitoring of drivers using approaches based on the vehicle and the driver’s behavior. Based on the SPC, we propose a method for the lane departure detection; a method for detecting sudden driver movements; and a method combined with computer vision to detect driver fatigue. All methods consider information from sensors scattered by the vehicle. The results showed the efficiency of the methods in the identification and detection of unwanted driver actions, such as sudden movements, lane departure, and driver fatigue. Lane departure detection obtained results of up to 76.92% (without constant speed) and 84.16% (speed maintained at ≈60). Furthermore, sudden movements detection obtained results of up to 91.66% (steering wheel) and 94.44% (brake). The driver fatigue has been detected in up to 94.46% situations. MDPI 2019-07-11 /pmc/articles/PMC6678967/ /pubmed/31336711 http://dx.doi.org/10.3390/s19143059 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Assuncao, Arthur N.
Aquino, Andre L. L.
Câmara de M. Santos, Ricardo C.
Guimaraes, Rodolfo L. M.
Oliveira, Ricardo A. R.
Vehicle Driver Monitoring through the Statistical Process Control
title Vehicle Driver Monitoring through the Statistical Process Control
title_full Vehicle Driver Monitoring through the Statistical Process Control
title_fullStr Vehicle Driver Monitoring through the Statistical Process Control
title_full_unstemmed Vehicle Driver Monitoring through the Statistical Process Control
title_short Vehicle Driver Monitoring through the Statistical Process Control
title_sort vehicle driver monitoring through the statistical process control
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678967/
https://www.ncbi.nlm.nih.gov/pubmed/31336711
http://dx.doi.org/10.3390/s19143059
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