Cyclist-motorist crash patterns in Denmark: a latent class clustering approach.

Kaplan, Sigal and Prato, Carlo Giacomo (2013) Cyclist-motorist crash patterns in Denmark: a latent class clustering approach.. Traffic injury prevention, 14 7: 725-733. doi:10.1080/15389588.2012.759654


Author Kaplan, Sigal
Prato, Carlo Giacomo
Title Cyclist-motorist crash patterns in Denmark: a latent class clustering approach.
Journal name Traffic injury prevention   Check publisher's open access policy
ISSN 1538-957X
1538-9588
Publication date 2013-01-23
Year available 2013
Sub-type Article (original research)
DOI 10.1080/15389588.2012.759654
Open Access Status Not Open Access
Volume 14
Issue 7
Start page 725
End page 733
Total pages 9
Place of publication New York, NY, United States
Publisher Taylor & Francis
Language eng
Formatted abstract
Objective: 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.

Method: 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.

Results:
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.

Conclusions: 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.
Keyword Bicycle
Cyclist–motorist crashes
Cyclists’ injury severity
Latent class clustering
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Social Science Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Created: Thu, 14 Apr 2016, 08:53:46 EST by Anthony Yeates on behalf of Learning and Research Services (UQ Library)