Citation

Al-Bdairi NSS, Hernandez S. Int. J. Transp. Sci. Technol. 2020; 9(2): 116-127.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.ijtst.2020.01.004

PMID

unavailable

Abstract

In spite of numerous efforts to quantitatively identify the factors contributing to the injury severity of different crash types in rural and urban settings, the distinction between rural and urban areas regarding the injury severity of run-off-road (ROR) crashes involving large trucks is still not clearly understood. As such, the objective of this study is to investigate the effect of area type (i.e., urban vs. rural) on injury severity outcomes sustained by drivers in ROR crashes involving large trucks while accounting for unobserved heterogeneity. To do this, the latent class ordered probit models with two classes are developed. The crash data pertaining to ROR crashes involving large trucks in Oregon between 2007 and 2014 were utilized. The estimation results reveal that the developed latent class ordered probit models (for urban and rural areas) are substantially distinct in terms of the contributing factors affect urban and rural ROR crash severities. The results indicate that female drivers and speed limit of 55 mph were associated with moderate injuries (non-incapacitating) in rural roadway ROR crashes while no injury outcome is most likely for crashes occurred in urban roadways with raised medians and on areas with a population density between 10,001 and 25,000. Also, the findings show that some factors increase the risk propensity of sustaining higher injury levels regardless of the land use setting such as crashes on horizontal curves, not wearing seatbelt, and driver fatigue. The findings of this study could benefit trucking industry, transportation agencies, and safety practitioners to prevent or alleviate the injury severity of ROR crashes involving large trucks by developing appropriate and cost-effective countermeasures.

Language: en

Keywords

Injury severity; Unobserved heterogeneity; Large trucks; Latent class ordered probit model; Run-off-road