249
Views
4
CrossRef citations to date
0
Altmetric
Articles

Factors affecting the accident size of motorcycle-involved crashes: a structural equation modeling approach

, , &
Pages 16-21 | Received 08 May 2020, Accepted 01 Oct 2020, Published online: 15 Oct 2020
 

Abstract

Motorcycle users are one of the vulnerable road users in the event of a crash due to the low level of protection. In most of the studies related to the safety of motorcycle, the highest level of occupants’ injury severity is frequently taken into account, which involves one aspect of the crash. To conduct a comprehensive study of crash severity, accident size can be utilized, which consists of different aspects of a crash. Therefore, to investigate the influential factors on the accident size of motorcycle-involved crashes, structural equation modeling was used in the present study. Results reveal that the crashes involving heavy vehicles, old-aged drivers, female drivers, day time, dry road surface, two-way roads, lack of shoulder and rural roads are associated with larger accident size. This study also showed the importance of considering the driver and road characteristics in safety programs for mitigating the crash severity.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 523.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.