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  4. Integrating spatial and temporal approaches for explaining bicycle crashes in high-risk areas in Antwerp (Belgium)
 
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Integrating spatial and temporal approaches for explaining bicycle crashes in high-risk areas in Antwerp (Belgium)

Journal
Sustainability (Switzerland)
Journal Volume
11
Journal Issue
13
Date Issued
2019
Author(s)
Wang, H.
Chang, S.K.J.
De Backer, H.
Lauwers, D.
De Maeyer, P.
SHYUE-KOONG CHANG  
DOI
10.3390/su11133746
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/437808
URL
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068639864&doi=10.3390%2fsu11133746&partnerID=40&md5=1af58198b14cbb324f2899e15c362b75
Abstract
The majority of bicycle crash studies aim at determining risk factors and estimating crash risks by employing statistics. Accordingly, the goal of this paper is to evaluate bicycle-motor vehicle crashes by using spatial and temporal approaches to statistical data. The spatial approach (a weighted kernel density estimation approach) preliminarily estimates crash risks at the macro level, thereby avoiding the expensive work of collecting traffic counts; meanwhile, the temporal approach (negative binomial regression approach) focuses on crash data that occurred on urban arterials and includes traffic exposure at the micro level. The crash risk and risk factors of arterial roads associated with bicycle facilities and road environments were assessed using a database built from field surveys and five government agencies. This study analysed 4120 geocoded bicycle crashes in the city of Antwerp (CA, Belgium). The data sets covered five years (2014 to 2018), including all bicycle-motorized vehicle (BMV) crashes from police reports. Urban arterials were highlighted as high-risk areas through the spatial approach. This was as expected given that, due to heavy traffic and limited road space, bicycle facilities on arterial roads face many design problems. Through spatial and temporal approaches, the environmental characteristics of bicycle crashes on arterial roads were analysed at the micro level. Finally, this paper provides an insight that can be used by both the geography and transport fields to improve cycling safety on urban arterial roads. ? 2019 by the authors.
Subjects
Bicycle-motorized vehicle (BMV) crashes; Crash severity index; Geographic information system; Negative binomial; Spatial; Temporal; Urban arterial roads; Weighted kernel density estimation
SDGs

[SDGs]SDG3

[SDGs]SDG11

Other Subjects
electric vehicle; estimation method; GIS; health risk; index method; integrated approach; risk factor; road; safety; spatial analysis; temporal analysis; Antwerp [Belgium]; Belgium
Type
journal article

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