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...

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Main Authors: Yi Liu, Zongzhi Li, Jingxian Liu, Harshingar Patel
Format: Article
Language:English
Published: Elsevier 2016-09-01
Series:Data in Brief
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340916304140
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spelling doaj-63bbb7d0fc764bc78570bbff552685c02020-11-25T01:39:01ZengElsevierData in Brief2352-34092016-09-018930933Vehicular crash data used to rank intersections by injury crash frequency and severityYi Liu0Zongzhi Li1Jingxian Liu2Harshingar Patel3Wuhan University of Technology, ChinaIllinois Institute of Technology, United States; Corresponding author. Phone: +1 312 567 3556.Wuhan University of Technology, ChinaIllinois Institute of Technology, United StatesThis 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.http://www.sciencedirect.com/science/article/pii/S2352340916304140
collection DOAJ
language English
format Article
sources DOAJ
author Yi Liu
Zongzhi Li
Jingxian Liu
Harshingar Patel
spellingShingle Yi Liu
Zongzhi Li
Jingxian Liu
Harshingar Patel
Vehicular crash data used to rank intersections by injury crash frequency and severity
Data in Brief
author_facet Yi Liu
Zongzhi Li
Jingxian Liu
Harshingar Patel
author_sort Yi Liu
title 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_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_sort vehicular crash data used to rank intersections by injury crash frequency and severity
publisher Elsevier
series Data in Brief
issn 2352-3409
publishDate 2016-09-01
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.
url http://www.sciencedirect.com/science/article/pii/S2352340916304140
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AT zongzhili vehicularcrashdatausedtorankintersectionsbyinjurycrashfrequencyandseverity
AT jingxianliu vehicularcrashdatausedtorankintersectionsbyinjurycrashfrequencyandseverity
AT harshingarpatel vehicularcrashdatausedtorankintersectionsbyinjurycrashfrequencyandseverity
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