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Vehicular crash data used to rank intersections by injury crash frequency and severity
This article contains data on research conducted in “A double standard model for allocating limited emergency medical service vehicle resources ensuring service reliability” (Liu et al., 2016) [1]. The crash counts were sorted out from comprehensive crash records of over one thousand major signalize...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4961217/ https://www.ncbi.nlm.nih.gov/pubmed/27508245 http://dx.doi.org/10.1016/j.dib.2016.06.046 |
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author | Liu, Yi Li, Zongzhi Liu, Jingxian Patel, Harshingar |
author_facet | Liu, Yi Li, Zongzhi Liu, Jingxian Patel, Harshingar |
author_sort | Liu, Yi |
collection | PubMed |
description | This article contains data on research conducted in “A double standard model for allocating limited emergency medical service vehicle resources ensuring service reliability” (Liu et al., 2016) [1]. The crash counts were sorted out from comprehensive crash records of over one thousand major signalized intersections in the city of Chicago from 2004 to 2010. For each intersection, vehicular crashes were counted by crash severity levels, including fatal, injury Types A, B, and C for major, moderate, and minor injury levels, property damage only (PDO), and unknown. The crash data was further used to rank intersections by equivalent injury crash frequency. The top 200 intersections with the highest number of crash occurrences identified based on crash frequency- and severity-based scenarios are shared in this brief. The provided data would be a valuable source for research in urban traffic safety analysis and could also be utilized to examine the effectiveness of traffic safety improvement planning and programming, intersection design enhancement, incident and emergency management, and law enforcement strategies. |
format | Online Article Text |
id | pubmed-4961217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-49612172016-08-09 Vehicular crash data used to rank intersections by injury crash frequency and severity Liu, Yi Li, Zongzhi Liu, Jingxian Patel, Harshingar Data Brief Data Article This article contains data on research conducted in “A double standard model for allocating limited emergency medical service vehicle resources ensuring service reliability” (Liu et al., 2016) [1]. The crash counts were sorted out from comprehensive crash records of over one thousand major signalized intersections in the city of Chicago from 2004 to 2010. For each intersection, vehicular crashes were counted by crash severity levels, including fatal, injury Types A, B, and C for major, moderate, and minor injury levels, property damage only (PDO), and unknown. The crash data was further used to rank intersections by equivalent injury crash frequency. The top 200 intersections with the highest number of crash occurrences identified based on crash frequency- and severity-based scenarios are shared in this brief. The provided data would be a valuable source for research in urban traffic safety analysis and could also be utilized to examine the effectiveness of traffic safety improvement planning and programming, intersection design enhancement, incident and emergency management, and law enforcement strategies. Elsevier 2016-07-01 /pmc/articles/PMC4961217/ /pubmed/27508245 http://dx.doi.org/10.1016/j.dib.2016.06.046 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Liu, Yi Li, Zongzhi Liu, Jingxian Patel, Harshingar Vehicular crash data used to rank intersections by injury crash frequency and severity |
title | Vehicular crash data used to rank intersections by injury crash frequency and severity |
title_full | Vehicular crash data used to rank intersections by injury crash frequency and severity |
title_fullStr | Vehicular crash data used to rank intersections by injury crash frequency and severity |
title_full_unstemmed | Vehicular crash data used to rank intersections by injury crash frequency and severity |
title_short | Vehicular crash data used to rank intersections by injury crash frequency and severity |
title_sort | vehicular crash data used to rank intersections by injury crash frequency and severity |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4961217/ https://www.ncbi.nlm.nih.gov/pubmed/27508245 http://dx.doi.org/10.1016/j.dib.2016.06.046 |
work_keys_str_mv | AT liuyi vehicularcrashdatausedtorankintersectionsbyinjurycrashfrequencyandseverity AT lizongzhi vehicularcrashdatausedtorankintersectionsbyinjurycrashfrequencyandseverity AT liujingxian vehicularcrashdatausedtorankintersectionsbyinjurycrashfrequencyandseverity AT patelharshingar vehicularcrashdatausedtorankintersectionsbyinjurycrashfrequencyandseverity |