Identifying High Risk Built Environments for Severe Bicycling Injuries

Shen, Qing; Chen, Peng; Pacific Northwest Transportation Consortium (PacTrans) (UTC); University of Washington. Dept. of Urban Design and Planning; Puget Sound Regional Council

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Identifying High Risk Built Environments for Severe Bicycling Injuries

2017-01-15
By Shen, Qing ; Chen, Peng

[PDF-1.45 MB]

English

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Creators:

Shen, Qing ; Chen, Peng

Shen, Qing ; Chen, Peng Less -
Corporate Creators:

Pacific Northwest Transportation Consortium (PacTrans) (UTC) ; University of Washington. Dept. of Urban Design and Planning ; Puget Sound Regional Council

Pacific Northwest Transportation Consortium (PacTrans) (UTC) ; University of Washington. Dept. of Urban Design and Planning ; Puget Sound Regional Council Less -
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Bicycling Built Environment Case Studies Injury Severity Safety
Publication/ Report Number:

2015-S-UW-92
Resource Type:

Tech Report
Geographical Coverage:

Miami (Florida) ; Minneapolis (Minnesota) ; Seattle (Washington) ; United States

Miami (Florida) ; Minneapolis (Minnesota) ; Seattle (Washington) ; United States Less -
Corporate Publisher:

Pacific Northwest Transportation Consortium (PacTrans) (UTC)
Abstract:

This study was aimed at filling part of the knowledge gap on bicycling safety in the built environment by addressing two questions. First, are built environment features and bicyclist injury severity correlated, and if so, what built environment factors most significantly relate to severe bicycling injuries? Second, do the identified statistical associations vary substantially among cities with different levels of bicycling and different built environments? The cities of Miami, Seattle, and Minneapolis, which differ in built environments, bicycle mode share, and bicyclist fatality rate, were selected as representative cases for the analysis. The generalized ordered logit (GOL) model was employed to examine the relationship between built environment features and bicyclist injury severity. Bicyclist injury severity was coded into four injury types: no injury (NI), possible injury (PI), evident injury (EI), and severe injury and fatality (SIF). The findings from the three-cities-pooled data included the following: (1) higher percentages of residential land and green space, commercial land, and office or mixed-use land were correlated with lower probabilities of EI and SIF; (2) land-use mixture was negatively correlated with EI and SIF; (3) steep slopes were positively associated with bicyclist injury severity; (4) in areas with more transit routes, bicyclist injury was less likely to be severe; (5) a higher speed limit was more likely to result in SIF; and (6) wearing a helmet was negatively associated with SIF, but positively related to PI and EI. GOL models for individual cities showed broad consistency with the pooled GOL model in the estimated relationship between built environment features and bicyclist injury severity.
Format:

PDF
Funding:

DTRT13-G-UTC40
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha256:e961a31989a876fcff5c763b9f3322e1a00929bcd35ab52265221885aca06e3c
Download URL:

https://rosap.ntl.bts.gov/view/dot/64802/dot_64802_DS1.pdf
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Identifying High Risk Built Environments for Severe Bicycling Injuries

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