Multi-Vehicle Crashes Involving Large Trucks: A Random Parameter Discrete Outcome Modeling Approach

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.


Subject(s):
Issue Date:
2015
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/207450
Published in:
Journal of the Transportation Research Forum, Volume 54, Number 1
Page range:
77-104
Total Pages:
28




 Record created 2017-04-01, last modified 2017-08-28

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