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Title:

Bicycle Safety Analysis at Intersections from Crowdsourced Data

Accession Number:

01699717

Record Type:

Component

Availability:

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Order URL: http://worldcat.org/issn/03611981

Abstract:

Cycling is encouraged in countries around the world as an economic, energy efficient, and sustainable mode of transportation. Although there are many studies focusing on analyzing bicycle safety, they have limitations because of the shortage of bicycle exposure data. This study represents a major step forward in estimating safety performance functions for bicycle crashes at intersections by using crowdsourced data from STRAVA. Several adjustments in respect of the population distribution and field observations were made to overcome the disproportionate representation of the STRAVA data. The adjusted STRAVA data which include bicycle exposure information were used as input to develop safety performance functions. The functions are negative binomial models aimed at predicting frequencies of bicycle crashes at intersections. The developed model was compared with three counterparts: the model using the unadjusted STRAVA data, the model using the STRAVA data with field observation data adjustments only, and the model using the STRAVA data with adjusted population. The results revealed that the case of STRAVA data with both population and field observation data adjustments had the best performance in bicycle crash modeling. The results also addressed several key factors (e.g., signal control system, intersection size, bike lanes) which are associated with bicycle safety at intersections. Additionally, the safety-in-numbers effect was acknowledged when bicycle crash rates decreased as bicycle activities increased. The study concluded that crowdsourced data are a reliable source for exploring bicycle safety after the appropriate adjustments.

Report/Paper Numbers:

19-00232

Language:

English

Authors:

Saad, Moatz
Abdel-Aty, Mohamed
Lee, Jaeyoung
Cai, Qing

Pagination:

pp 1-14

Publication Date:

2019-4

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Volume: 2673
Issue Number: 4
Publisher: Sage Publications, Incorporated
ISSN: 0361-1981
EISSN: 2169-4052
Serial URL: http://journals.sagepub.com/home/trr

Media Type:

Digital/other

Features:

Figures (8) ; References (64) ; Tables (5)

Subject Areas:

Data and Information Technology; Highways; Pedestrians and Bicyclists; Safety and Human Factors

Files:

TRIS, TRB, ATRI

Created Date:

Feb 19 2019 4:21PM