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Holistic Vehicle Instrumentation for Assessing Driver Driving Styles

Nowadays, autonomous vehicles are increasing, and the driving scenario that includes both autonomous and human-driven vehicles is a fact. Knowing the driving styles of drivers in the process of automating vehicles is interest in order to make driving as natural as possible. To this end, this article...

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Autores principales: Garrosa, María, Olmeda, Ester, Fuentes del Toro, Sergio, Díaz, Vicente
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923203/
https://www.ncbi.nlm.nih.gov/pubmed/33670670
http://dx.doi.org/10.3390/s21041427
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author Garrosa, María
Olmeda, Ester
Fuentes del Toro, Sergio
Díaz, Vicente
author_facet Garrosa, María
Olmeda, Ester
Fuentes del Toro, Sergio
Díaz, Vicente
author_sort Garrosa, María
collection PubMed
description Nowadays, autonomous vehicles are increasing, and the driving scenario that includes both autonomous and human-driven vehicles is a fact. Knowing the driving styles of drivers in the process of automating vehicles is interest in order to make driving as natural as possible. To this end, this article presents a first approach to the design of a controller for the braking system capable of imitating the different manoeuvres that any driver performs while driving. With this aim, different experimental tests have been carried out with a vehicle instrumented with sensors capable of providing real-time information related to the braking system. The experimental tests consist of reproducing a series of braking manoeuvres at different speeds on a flat floor track following a straight path. The tests distinguish between three types of braking manoeuvre: maintained, progressive and emergency braking, which cover all the driving circumstances in which the braking system may intervene. This article presents an innovative approach to characterise braking types thanks to the methodology of analysing the data obtained by sensors during experimental tests. The characterisation of braking types makes it possible to dynamically classify three driving styles: cautious, normal and aggressive. The proposed classifications allow it possible to identify the driving styles on the basis of the pressure in the hydraulic brake circuit, the force exerted by the driver on the brake pedal, the longitudinal deceleration and the braking power, knowing in all cases the speed of the vehicle. The experiments are limited by the fact that there are no other vehicles, obstacles, etc. in the vehicle’s environment, but in this article the focus is exclusively on characterising a driver with methods that use the vehicle’s dynamic responses measured by on-board sensors. The results of this study can be used to define the driving style of an autonomous vehicle.
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spelling pubmed-79232032021-03-03 Holistic Vehicle Instrumentation for Assessing Driver Driving Styles Garrosa, María Olmeda, Ester Fuentes del Toro, Sergio Díaz, Vicente Sensors (Basel) Article Nowadays, autonomous vehicles are increasing, and the driving scenario that includes both autonomous and human-driven vehicles is a fact. Knowing the driving styles of drivers in the process of automating vehicles is interest in order to make driving as natural as possible. To this end, this article presents a first approach to the design of a controller for the braking system capable of imitating the different manoeuvres that any driver performs while driving. With this aim, different experimental tests have been carried out with a vehicle instrumented with sensors capable of providing real-time information related to the braking system. The experimental tests consist of reproducing a series of braking manoeuvres at different speeds on a flat floor track following a straight path. The tests distinguish between three types of braking manoeuvre: maintained, progressive and emergency braking, which cover all the driving circumstances in which the braking system may intervene. This article presents an innovative approach to characterise braking types thanks to the methodology of analysing the data obtained by sensors during experimental tests. The characterisation of braking types makes it possible to dynamically classify three driving styles: cautious, normal and aggressive. The proposed classifications allow it possible to identify the driving styles on the basis of the pressure in the hydraulic brake circuit, the force exerted by the driver on the brake pedal, the longitudinal deceleration and the braking power, knowing in all cases the speed of the vehicle. The experiments are limited by the fact that there are no other vehicles, obstacles, etc. in the vehicle’s environment, but in this article the focus is exclusively on characterising a driver with methods that use the vehicle’s dynamic responses measured by on-board sensors. The results of this study can be used to define the driving style of an autonomous vehicle. MDPI 2021-02-18 /pmc/articles/PMC7923203/ /pubmed/33670670 http://dx.doi.org/10.3390/s21041427 Text en © 2021 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
Garrosa, María
Olmeda, Ester
Fuentes del Toro, Sergio
Díaz, Vicente
Holistic Vehicle Instrumentation for Assessing Driver Driving Styles
title Holistic Vehicle Instrumentation for Assessing Driver Driving Styles
title_full Holistic Vehicle Instrumentation for Assessing Driver Driving Styles
title_fullStr Holistic Vehicle Instrumentation for Assessing Driver Driving Styles
title_full_unstemmed Holistic Vehicle Instrumentation for Assessing Driver Driving Styles
title_short Holistic Vehicle Instrumentation for Assessing Driver Driving Styles
title_sort holistic vehicle instrumentation for assessing driver driving styles
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923203/
https://www.ncbi.nlm.nih.gov/pubmed/33670670
http://dx.doi.org/10.3390/s21041427
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