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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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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. |
format | Online Article Text |
id | pubmed-6678967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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