Infrastructure and spatial effects on the frequency of cyclist-motorist collisions in the Copenhagen Region

Carlo Giacomo Prato*, Sigal Kaplan, Thomas Kjær Rasmussen, Tove Hels

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Promoting cycling aims at reducing congestion and pollution as well as encouraging healthy and sustainable lifestyles but generally clashes with the perception of crash risk while riding a bicycle that is still the most significant disincentive to cycling. This study sheds light on the factors affecting the probability of cyclist–motorist collisions while accounting for heterogeneity and spatial correlation. The current study analyzed the factors contributing to increase crash risk while riding a bicycle by focusing on 5,349 cyclist–motorist collisions within 269 traffic zones in the Copenhagen Region. The model controlled for traffic exposure for bicycles and motorized transport modes, evaluated the effects of infrastructure and socioeconomic characteristics of the zones, and accounted for heterogeneity and spatial correlation across the zones. A Poisson-lognormal model with second-order conditional autoregressive (CAR) priors confirmed the existence of the safety in numbers phenomenon, contradicted previous literature about bicycle facilities not being helpful in reducing crash risk, highlighted the need for Copenhagen-style bicycle paths especially in suburban areas, and emphasized how heterogeneity and spatial correlation play a significant role in explaining the probability of cyclist-motorist crash occurrence.

Original languageAmerican English
Pages (from-to)346-360
Number of pages15
JournalJournal of Transportation Safety and Security
Volume8
Issue number4
DOIs
StatePublished - 1 Oct 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Taylor & Francis Group, LLC and The University of Tennessee.

Keywords

  • Cycling
  • Cycling exposure
  • Cycling–motorist crashes
  • Poisson-lognormal CAR model
  • Spatial correlation

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