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Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior
The aim of this paper was to provide a methodological framework for estimating the amount of driving data that should be collected for each driver in order to acquire a clear picture regarding their driving behavior. We examined whether there is a specific discrete time point for each driver, in the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248787/ https://www.ncbi.nlm.nih.gov/pubmed/32370264 http://dx.doi.org/10.3390/s20092600 |
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author | Stavrakaki, Anna-Maria Tselentis, Dimitrios I. Barmpounakis, Emmanouil Vlahogianni, Eleni I. Yannis, George |
author_facet | Stavrakaki, Anna-Maria Tselentis, Dimitrios I. Barmpounakis, Emmanouil Vlahogianni, Eleni I. Yannis, George |
author_sort | Stavrakaki, Anna-Maria |
collection | PubMed |
description | The aim of this paper was to provide a methodological framework for estimating the amount of driving data that should be collected for each driver in order to acquire a clear picture regarding their driving behavior. We examined whether there is a specific discrete time point for each driver, in the form of total driving duration and/or the number of trips, beyond which the characteristics of driving behavior are stabilized over time. Various mathematical and statistical methods were employed to process the data collected and determine the time point at which behavior converges. Detailed data collected from smartphone sensors are used to test the proposed methodology. The driving metrics used in the analysis are the number of harsh acceleration and braking events, the duration of mobile usage while driving and the percentage of time driving over the speed limits. Convergence was tested in terms of both the magnitude and volatility of each metric for different trips and analysis is performed for several trip durations. Results indicated that there is no specific time point or number of trips after which driving behavior stabilizes for all drivers and/or all metrics examined. The driving behavior stabilization is mostly affected by the duration of the trips examined and the aggressiveness of the driver. |
format | Online Article Text |
id | pubmed-7248787 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72487872020-08-13 Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior Stavrakaki, Anna-Maria Tselentis, Dimitrios I. Barmpounakis, Emmanouil Vlahogianni, Eleni I. Yannis, George Sensors (Basel) Article The aim of this paper was to provide a methodological framework for estimating the amount of driving data that should be collected for each driver in order to acquire a clear picture regarding their driving behavior. We examined whether there is a specific discrete time point for each driver, in the form of total driving duration and/or the number of trips, beyond which the characteristics of driving behavior are stabilized over time. Various mathematical and statistical methods were employed to process the data collected and determine the time point at which behavior converges. Detailed data collected from smartphone sensors are used to test the proposed methodology. The driving metrics used in the analysis are the number of harsh acceleration and braking events, the duration of mobile usage while driving and the percentage of time driving over the speed limits. Convergence was tested in terms of both the magnitude and volatility of each metric for different trips and analysis is performed for several trip durations. Results indicated that there is no specific time point or number of trips after which driving behavior stabilizes for all drivers and/or all metrics examined. The driving behavior stabilization is mostly affected by the duration of the trips examined and the aggressiveness of the driver. MDPI 2020-05-02 /pmc/articles/PMC7248787/ /pubmed/32370264 http://dx.doi.org/10.3390/s20092600 Text en © 2020 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 Stavrakaki, Anna-Maria Tselentis, Dimitrios I. Barmpounakis, Emmanouil Vlahogianni, Eleni I. Yannis, George Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior |
title | Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior |
title_full | Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior |
title_fullStr | Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior |
title_full_unstemmed | Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior |
title_short | Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior |
title_sort | estimating the necessary amount of driving data for assessing driving behavior |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248787/ https://www.ncbi.nlm.nih.gov/pubmed/32370264 http://dx.doi.org/10.3390/s20092600 |
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