Multi-Vehicle Crashes Involving Large Trucks: A Random Parameter Discrete Outcome Modeling Approach
Journal of the Transportation Research Forum, 2015, vol. 54, issue 1
A growing concern on large-truck crashes increased over the years due to the potential economic impacts and level of injury severity. This study aims to analyze the injury severities of multivehicle large-trucks crashes on national highways. To capture and understand the complexities of contributing factors, two random parameter discrete outcome models – random parameter ordered probit and mixed logit – were estimated to predict the likelihood of five injury severity outcomes: fatal, incapacitating, non-incapacitating, possible injury, and no-injury. Estimation findings indicate that the level of injury severity is highly influenced by a number of complex interactions of factors, namely, human, vehicular, road-environmental, and crash dynamics that can vary across the observations.
Keywords: Public; Economics (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ags:ndjtrf:207450
Access Statistics for this article
More articles in Journal of the Transportation Research Forum from Transportation Research Forum
Bibliographic data for series maintained by AgEcon Search ().