Integrating Spatial and Temporal Approaches for Explaining Bicycle Crashes in High-Risk Areas in Antwerp (Belgium)

Hwachyi Wang, S. K. Jason Chang, Hans De Backer, Dirk Lauwers and Philippe De Maeyer
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Hwachyi Wang: Department of Civil Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
S. K. Jason Chang: Department of Civil Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
Hans De Backer: Department of Civil Engineering, Technologiepark Zwijnaarde 904, Ghent University, B-9052 Zwijnaarde, Belgium
Dirk Lauwers: Center for Mobility and Spatial Planning, Ghent University, Sint-Pietersnieuwstraat 41 B2, B-9000 Gent, Belgium
Philippe De Maeyer: Department of Geography, Krijgslaan 281 S8, Ghent University, B-9000 Gent, Belgium

Sustainability, 2019, vol. 11, issue 13, 1-28

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.

Keywords: urban arterial roads; geographic information system; bicycle–motorized vehicle (BMV) crashes; spatial; weighted kernel density estimation; temporal; negative binomial; crash severity index (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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