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BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool

The popularity of bicycles as a mode of transportation has been steadily increasing. However, concerns about cyclist safety persist due to a need for comprehensive data. This data scarcity hinders accurate assessment of bicycle safety and identification of factors that contribute to the occurrence a...

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Autores principales: Duran Bernardes, Suzana, Ozbay, Kaan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385114/
https://www.ncbi.nlm.nih.gov/pubmed/37514764
http://dx.doi.org/10.3390/s23146471
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author Duran Bernardes, Suzana
Ozbay, Kaan
author_facet Duran Bernardes, Suzana
Ozbay, Kaan
author_sort Duran Bernardes, Suzana
collection PubMed
description The popularity of bicycles as a mode of transportation has been steadily increasing. However, concerns about cyclist safety persist due to a need for comprehensive data. This data scarcity hinders accurate assessment of bicycle safety and identification of factors that contribute to the occurrence and severity of bicycle collisions in urban environments. This paper presents the development of the BSafe-360, a novel multi-sensor device designed as a data acquisition system (DAS) for collecting naturalistic cycling data, which provides a high granularity of cyclist behavior and interactions with other road users. For the hardware component, the BSafe-360 utilizes a Raspberry Pi microcomputer, a Global Positioning System (GPS) antenna and receiver, two ultrasonic sensors, an inertial measurement unit (IMU), and a real-time clock (RTC), which are all housed within a customized bicycle phone case. To handle the software aspect, BSafe-360 has two Python scripts that manage data processing and storage in both local and online databases. To demonstrate the capabilities of the device, we conducted a proof of concept experiment, collecting data for seven hours. In addition to utilizing the BSafe-360, we included data from CCTV and weather information in the data analysis step for verifying the occurrence of critical events, ensuring comprehensive coverage of all relevant information. The combination of sensors within a single device enables the collection of crucial data for bicycle safety studies, including bicycle trajectory, lateral passing distance (LPD), and cyclist behavior. Our findings show that the BSafe-360 is a promising tool for collecting naturalistic cycling data, facilitating a deeper understanding of bicycle safety and improving it. By effectively improving bicycle safety, numerous benefits can be realized, including the potential to reduce bicycle injuries and fatalities to zero in the near future.
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spelling pubmed-103851142023-07-30 BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool Duran Bernardes, Suzana Ozbay, Kaan Sensors (Basel) Article The popularity of bicycles as a mode of transportation has been steadily increasing. However, concerns about cyclist safety persist due to a need for comprehensive data. This data scarcity hinders accurate assessment of bicycle safety and identification of factors that contribute to the occurrence and severity of bicycle collisions in urban environments. This paper presents the development of the BSafe-360, a novel multi-sensor device designed as a data acquisition system (DAS) for collecting naturalistic cycling data, which provides a high granularity of cyclist behavior and interactions with other road users. For the hardware component, the BSafe-360 utilizes a Raspberry Pi microcomputer, a Global Positioning System (GPS) antenna and receiver, two ultrasonic sensors, an inertial measurement unit (IMU), and a real-time clock (RTC), which are all housed within a customized bicycle phone case. To handle the software aspect, BSafe-360 has two Python scripts that manage data processing and storage in both local and online databases. To demonstrate the capabilities of the device, we conducted a proof of concept experiment, collecting data for seven hours. In addition to utilizing the BSafe-360, we included data from CCTV and weather information in the data analysis step for verifying the occurrence of critical events, ensuring comprehensive coverage of all relevant information. The combination of sensors within a single device enables the collection of crucial data for bicycle safety studies, including bicycle trajectory, lateral passing distance (LPD), and cyclist behavior. Our findings show that the BSafe-360 is a promising tool for collecting naturalistic cycling data, facilitating a deeper understanding of bicycle safety and improving it. By effectively improving bicycle safety, numerous benefits can be realized, including the potential to reduce bicycle injuries and fatalities to zero in the near future. MDPI 2023-07-17 /pmc/articles/PMC10385114/ /pubmed/37514764 http://dx.doi.org/10.3390/s23146471 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Duran Bernardes, Suzana
Ozbay, Kaan
BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool
title BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool
title_full BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool
title_fullStr BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool
title_full_unstemmed BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool
title_short BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool
title_sort bsafe-360: an all-in-one naturalistic cycling data collection tool
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385114/
https://www.ncbi.nlm.nih.gov/pubmed/37514764
http://dx.doi.org/10.3390/s23146471
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