Cyclist-Motorist Crash Patterns in Denmark: A Latent Class Clustering Approach

The current study aimed at uncovering patterns of cyclist/motorist crashes in Denmark and investigating their prevalence and severity. The importance of implementing clustering techniques for providing a holistic overview of vulnerable road users’ crash patterns derives from the need to prioritize safety issues and to devise efficient preventive measures. The current study focused on cyclist/motorist crashes that occurred in Denmark during the period between 2007 and 2011. To uncover crash patterns, the current analysis applied latent class clustering, an unsupervised probabilistic clustering approach that relies on the statistical concept of likelihood and allows partial overlap across clusters. The analysis yielded 13 distinguishable cyclist/motorist latent classes. Specific crash patterns for urban and rural areas were revealed. Prevalent features that allowed differentiating the latent classes were speed limit, infrastructure type, road surface conditions, number of lanes, motorized vehicle precrash maneuvers, the availability of a cycle lane, cyclist intoxication, and helmet wearing behavior. After the latent class clustering, the distribution of cyclists’ injury severity within each cluster was analyzed. The latent class clustering approach provided a comprehensive and clear map of cyclist/motorist crash patterns. The results are useful for prioritizing and resolving safety issues in urban areas, where there is a significant share of cyclists potentially involved in multiple hazardous situations or where extensive bicycle sharing programs are planned.

• Record URL:
  https://doi.org/10.1080/15389588.2012.759654
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/49192340
• Supplemental Notes:
  • Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Kaplan, Sigal
  • Prato, Carlo
• Publication Date: 2013-10

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 725-733
• Serial:
  • Traffic Injury Prevention
  • Volume: 14
  • Issue Number: 7
  • Publisher: Taylor & Francis
  • ISSN: 1538-9588
  • Serial URL: http://www.tandf.co.uk/journals/titles/15389588.html

Subject/Index Terms

• TRT Terms: Automobiles; Bicycle crashes; Bicycle helmets; Bicycle lanes; Cluster analysis; Crash characteristics; Crash reconstruction; Cyclists; Drunk driving; Highway safety; Rural areas; Speed limits; Travelers; Urban areas; Vehicle mix
• Subject Areas: Highways; Pedestrians and Bicyclists; Safety and Human Factors; I81: Accident Statistics; I83: Accidents and the Human Factor; I84: Personal Injuries;

Filing Info

• Accession Number: 01502647
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 30 2013 11:05AM