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Improving Pedestrian Safety Using Ultra-Wideband Sensors: A Study of Time-to-Collision Estimation
Pedestrian safety has been evaluated based on the mean number of pedestrian-involved collisions. Traffic conflicts have been used as a data source to supplement collision data because of their higher frequency and lower damage. Currently, the main source of traffic conflict observation is through vi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10142004/ https://www.ncbi.nlm.nih.gov/pubmed/37112510 http://dx.doi.org/10.3390/s23084171 |
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author | Fakhoury, Salah Ismail, Karim |
author_facet | Fakhoury, Salah Ismail, Karim |
author_sort | Fakhoury, Salah |
collection | PubMed |
description | Pedestrian safety has been evaluated based on the mean number of pedestrian-involved collisions. Traffic conflicts have been used as a data source to supplement collision data because of their higher frequency and lower damage. Currently, the main source of traffic conflict observation is through video cameras that can efficiently gather rich data but can be limited by weather and lighting conditions. The utilization of wireless sensors to gather traffic conflict data can augment video sensors because of their robustness to adverse weather conditions and poor illumination. This study presents a prototype of a safety assessment system that utilizes ultra-wideband wireless sensors to detect traffic conflicts. A customized variant of time-to-collision is used to detect conflicts at different severity thresholds. Field trials are conducted using vehicle-mounted beacons and a phone to simulate sensors on vehicles and smart devices on pedestrians. Proximity measures are calculated in real-time to alert smartphones and prevent collisions, even in adverse weather conditions. Validation is conducted to assess the accuracy of time-to-collision measurements at various distances from the phone. Several limitations are identified and discussed, along with recommendations for improvement and lessons learned for future research and development. |
format | Online Article Text |
id | pubmed-10142004 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101420042023-04-29 Improving Pedestrian Safety Using Ultra-Wideband Sensors: A Study of Time-to-Collision Estimation Fakhoury, Salah Ismail, Karim Sensors (Basel) Article Pedestrian safety has been evaluated based on the mean number of pedestrian-involved collisions. Traffic conflicts have been used as a data source to supplement collision data because of their higher frequency and lower damage. Currently, the main source of traffic conflict observation is through video cameras that can efficiently gather rich data but can be limited by weather and lighting conditions. The utilization of wireless sensors to gather traffic conflict data can augment video sensors because of their robustness to adverse weather conditions and poor illumination. This study presents a prototype of a safety assessment system that utilizes ultra-wideband wireless sensors to detect traffic conflicts. A customized variant of time-to-collision is used to detect conflicts at different severity thresholds. Field trials are conducted using vehicle-mounted beacons and a phone to simulate sensors on vehicles and smart devices on pedestrians. Proximity measures are calculated in real-time to alert smartphones and prevent collisions, even in adverse weather conditions. Validation is conducted to assess the accuracy of time-to-collision measurements at various distances from the phone. Several limitations are identified and discussed, along with recommendations for improvement and lessons learned for future research and development. MDPI 2023-04-21 /pmc/articles/PMC10142004/ /pubmed/37112510 http://dx.doi.org/10.3390/s23084171 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 Fakhoury, Salah Ismail, Karim Improving Pedestrian Safety Using Ultra-Wideband Sensors: A Study of Time-to-Collision Estimation |
title | Improving Pedestrian Safety Using Ultra-Wideband Sensors: A Study of Time-to-Collision Estimation |
title_full | Improving Pedestrian Safety Using Ultra-Wideband Sensors: A Study of Time-to-Collision Estimation |
title_fullStr | Improving Pedestrian Safety Using Ultra-Wideband Sensors: A Study of Time-to-Collision Estimation |
title_full_unstemmed | Improving Pedestrian Safety Using Ultra-Wideband Sensors: A Study of Time-to-Collision Estimation |
title_short | Improving Pedestrian Safety Using Ultra-Wideband Sensors: A Study of Time-to-Collision Estimation |
title_sort | improving pedestrian safety using ultra-wideband sensors: a study of time-to-collision estimation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10142004/ https://www.ncbi.nlm.nih.gov/pubmed/37112510 http://dx.doi.org/10.3390/s23084171 |
work_keys_str_mv | AT fakhourysalah improvingpedestriansafetyusingultrawidebandsensorsastudyoftimetocollisionestimation AT ismailkarim improvingpedestriansafetyusingultrawidebandsensorsastudyoftimetocollisionestimation |