Risk Factors for Pedestrian and Bicycle Crashes

Monsere, Chris; Wang, Haizhong; Wang, Yi; Chen, Chen; Portland State University. Dept. of Civil & Environmental Engineering; Oregon State University. School of Civil and Construction Engineering

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Risk Factors for Pedestrian and Bicycle Crashes

2017-05-31
By Monsere, Chris ; Wang, Haizhong ; Wang, Yi ; ...

[PDF-2.98 MB]

English

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Details:

Creators:

Monsere, Chris ; Wang, Haizhong ; Wang, Yi ; Chen, Chen

Monsere, Chris ; Wang, Haizhong ; Wang, Yi ; Chen, Chen Less -
Corporate Creators:

Portland State University. Dept. of Civil & Environmental Engineering ; Oregon State University. School of Civil and Construction Engineering

Portland State University. Dept. of Civil & Environmental Engineering ; Oregon State University. School of Civil and Construction Engineering Less -
Corporate Contributors:

Oregon. Dept. of Transportation. Research Section ; United States. Federal Highway Administration

Oregon. Dept. of Transportation. Research Section ; United States. Federal Highway Administration Less -
Subject/TRT Terms:

[+]

Accident Prone Locations Accident Severity Bicycle Accidents Bicycle Safety Highways Logistic Regression Analysis Pedestrian Accidents Pedestrian Safety Pedestrians And Bicyclists Risk Analysis Safety And Human Factors Traffic Safety
Publication/ Report Number:

FHWA-OR-RD-17-13 ; SPR 779

FHWA-OR-RD-17-13 ; SPR 779 Less -
Resource Type:

Tech Report
Geographical Coverage:

United States ; Oregon

United States ; Oregon Less -
TRIS Online Accession Number:

01659813
Edition:

Final Report
Corporate Publisher:

Oregon. Dept. of Transportation. Research Section
Abstract:

The primary goal of this research was to develop a tool for the Oregon Department of Transportation (ODOT) to improve methods to identify and prioritize locations with increased or elevated risk for pedestrian and bicycle crashes. This report includes a comprehensive review of many scientific reports and papers about the pedestrian and bicycle crashes on road segments or intersections. To develop the risk model data were collected from 188 segments and 184 intersections randomly selected following the data collection plan. . These samples included 213 bicycle and pedestrian crashes on the segments and 238 at intersections. Geometric, land use, volume, and crash data were collected from different databases, including Google Maps, EPA’s Smart Location Database and the ODOT crash database from 2009-2013. The research team developed logistic regression models for both crash occurrence (crash or not) and crash severity models. The models related to crash severity were not robust, most likely due to the few segments and intersections with severe crashes in the dataset. The crash occurrence models were used to create a risk-scoring tool. The risk-scoring tool was applied to safety projects identified in the 2015 All Roads Transportation Safety (ARTS) project lists from Oregon DOT’s Region 1 and 2. The risk scores for the case study applications aligned reasonably well with the project’s benefit-costs estimates.
Format:

PDF
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:912cdb76d79d657f2339c455d02466c2d4c0064a55e32a910c8ca628c6380880
Download URL:

https://rosap.ntl.bts.gov/view/dot/36343/dot_36343_DS1.pdf
File Type:

SPR779_Risk_Score_ODOT_v7.xlsx

xlsx

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