Predicting cycling accident risk in Brussels: A spatial case–control approach

This paper aims at predicting cycling accident risk for an entire network and identifying how road infrastructure influences cycling safety in the Brussels-Capital Region (Belgium). A spatial Bayesian modelling approach is proposed using a binary dependent variable (accident, no accident at location i) constructed from a case–control strategy. Control sites are sampled along the ‘bikeable’ road network in function of the potential bicycle traffic transiting in each ward. Risk factors are limited to infrastructure, traffic and environmental characteristics. Results suggest that a high risk is statistically associated with the presence of on-road tram tracks, bridges without cycling facility, complex intersections, proximity to shopping centres or garages, and busy van and truck traffic. Cycle facilities built at intersections and parked vehicles located next to separated cycle facilities are also associated with an increased risk, whereas contraflow cycling is associated with a reduced risk. The cycling accident risk is far from being negligible in points where there is actually no reported cycling accident but where they are yet expected to occur. Hence, mapping predicted accident risks provides planners and policy makers with a useful tool for accurately locating places with a high potential risk even before accidents actually happen. This also provides comprehensible information for orienting cyclists to the safest routes in Brussels.

• Record URL:
  • https://doi.org/10.1016/j.aap.2013.07.001
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0001457513002686
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier.
• Authors:
  • Vandenbulcke, Grégory
  • Thomas, Isabelle
  • Int Panis, Luc
• Publication Date: 2014-1

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 341-357
• Serial:
  • Accident Analysis & Prevention
  • Volume: 62
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0001-4575
  • Serial URL: http://www.sciencedirect.com/science/journal/00014575

Subject/Index Terms

• TRT Terms: Bicycle crashes; Bicycle facilities; Crash risk forecasting; Infrastructure; Spatial analysis
• Uncontrolled Terms: Bayesian models; Bicycle safety; Case-control studies; Road networks
• Geographic Terms: Brussels (Belgium)
• Subject Areas: Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 01519825
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 26 2014 10:11AM