A spatial assessment of high-resolution drainage characteristics and roadway safety during wet conditions. (August 2021)
- Record Type:
- Journal Article
- Title:
- A spatial assessment of high-resolution drainage characteristics and roadway safety during wet conditions. (August 2021)
- Main Title:
- A spatial assessment of high-resolution drainage characteristics and roadway safety during wet conditions
- Authors:
- Crimmins, Michael
Park, Seri
Smith, Virginia
Kremer, Peleg - Abstract:
- Abstract: Much of the research regarding traffic crashes considers various geometric roadway features; however, ever-evolving urban watersheds and climate change increasingly impact roadway conditions. Little research has focused on the relationship between high-resolution drainage characteristics and the spatial distribution of crashes. This study incorporated local environmental and drainage risk factors in assessing network safety performance using spatial analysis techniques. Kernel density surfaces and the Local Getis Ord Gi* statistics were used to identify and visualize locations prone to experiencing crashes during wet conditions. Spatial regression modelling was used to link crashes to environmental and traffic risk factors across a citywide network. Proof-of-concept for this framework is demonstrated in the City of Philadelphia, Pennsylvania using publicly available spatial data. The results of this study show a relationship between local drainage, environmental characteristics, and wet crash distribution, providing novel insight into roadway safety during wet conditions. Highlights: This study incorporated local environmental and drainage risk factors to assess network safety performance using spatial analysis techniques. Spatial regression modelling was used to link crashes to environmental and traffic risk factors across a citywide network. This study links drainage, environmental characteristics, and crashes, providing novel insight into roadway safety duringAbstract: Much of the research regarding traffic crashes considers various geometric roadway features; however, ever-evolving urban watersheds and climate change increasingly impact roadway conditions. Little research has focused on the relationship between high-resolution drainage characteristics and the spatial distribution of crashes. This study incorporated local environmental and drainage risk factors in assessing network safety performance using spatial analysis techniques. Kernel density surfaces and the Local Getis Ord Gi* statistics were used to identify and visualize locations prone to experiencing crashes during wet conditions. Spatial regression modelling was used to link crashes to environmental and traffic risk factors across a citywide network. Proof-of-concept for this framework is demonstrated in the City of Philadelphia, Pennsylvania using publicly available spatial data. The results of this study show a relationship between local drainage, environmental characteristics, and wet crash distribution, providing novel insight into roadway safety during wet conditions. Highlights: This study incorporated local environmental and drainage risk factors to assess network safety performance using spatial analysis techniques. Spatial regression modelling was used to link crashes to environmental and traffic risk factors across a citywide network. This study links drainage, environmental characteristics, and crashes, providing novel insight into roadway safety during wet conditions. … (more)
- Is Part Of:
- Applied geography. Volume 133(2021)
- Journal:
- Applied geography
- Issue:
- Volume 133(2021)
- Issue Display:
- Volume 133, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 133
- Issue:
- 2021
- Issue Sort Value:
- 2021-0133-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-08
- Subjects:
- Roadway safety -- Weather -- Drainage -- Crash distribution -- Spatial analysis
Geography -- Periodicals
Human geography -- Periodicals
Human ecology -- Periodicals
910 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.apgeog.2021.102477 ↗
- Languages:
- English
- ISSNs:
- 0143-6228
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.590000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
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