A comparative injury severity analysis of rural intersection crashes under different lighting conditions in Alabama. Issue 9 (20th October 2020)

• Record Type: Journal Article
• Authors: Islam, Samantha; Burton, Benjamin
• Is Part Of: Journal of transportation safety & security. Volume 12:Issue 9(2020)
• Page Start: 1106
• Page End: 1127
• Publication Date: 2020-10-20
• Subjects: Dark -- injury severity -- intersection -- lighting -- random parameter -- rural; Transportation -- United States -- Safety measures -- Periodicals; Transportation -- Security measures -- United States -- Periodicals; Transportation -- Safety measures; Transportation -- Security measures; United States; Periodicals; 353.9805
• DOI: 10.1080/19439962.2019.1572682
• Languages: English
• ISSNs: 1943-9970

Abstract

Abstract: This article explores the factors contributing to the injury severity resulting from rural intersection crashes in Alabama under different lighting conditions. Given the occurrence of a crash, separate mixed logit models of injury severity (with possible outcomes of fatal, major, minor, and possible or no injury) were estimated for different lighting conditions: i. dark and ii. lighted (including daylight). The estimated models identified a variety of statistically significant factors influencing the injury severities. According to these models, some variables were found to be significant only in one model but not in the other one. For example, variables such as female drivers, presence of no opposing lane separations, and presence of stop signs were found significant only in the dark intersection model. On the other hand, variables such as senior drivers (65 years and older), presence of signaling devices, and posted speed limit 40 mph or lower were found significant only in the lighted/daylight model. In addition, some variables (such as, driver under influence of alcohol, roadway curves, etc.) were found significant in both models. Estimation findings also showed that two parameters in each model could be modeled as random parameters indicating corresponding variables' varying influences on the injury severity due to unobserved effects.