Multi-Vehicle Crashes Involving Large Trucks: A Random Parameter Discrete Outcome Modeling Approach
Document Type
Article
Publication Date
2015
Digital Object Identifier (DOI)
https://doi.org/10.5399/osu/jtrf.54.1.4273
Abstract
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 multi-vehicle 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.
Was this content written or created while at USF?
No
Citation / Publisher Attribution
Journal of the Transportation Research Forum, v. 54, no. 1, p. 77-103
Scholar Commons Citation
Islam, Mouyid B., "Multi-Vehicle Crashes Involving Large Trucks: A Random Parameter Discrete Outcome Modeling Approach" (2015). CUTR Faculty Journal Publications. 110.
https://digitalcommons.usf.edu/cutr_facpub/110
