Analyzing Traffic Crash Severity in Work Zones under Different Light Conditions
Joint Authors
Huang, Baoshan
Chen, Huaxin
Wei, Xinxin
Shu, Xiang
Taylor, Edward L.
Source
Journal of Advanced Transportation
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-04
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Previous studies have investigated various factors that contribute to the severity of work zone crashes.
However, little has been done on the specific effects of light conditions.
Using the data from the Enhanced Tennessee Roadway Information Management System (E-TRIMS), crashes that occurred in the Tennessee work zones during 2003–2015 are categorized into three light conditions: daylight, dark-lighted, and dark-not-lighted.
One commonly used decision tree method—Classification and Regression Trees (CART)—is adopted to investigate the factors contributing to crash severity in highway work zones under these light conditions.
The outcomes from the three decision trees with differing light conditions show significant differences in the ranking and importance of the factors considered in the study, thereby indicating the necessity of examining traffic crashes according to light conditions.
By separately considering the crash characteristics under different light conditions, some new findings are obtained from this study.
The study shows that an increase in the number of lanes increases the crash severity level in work zones during the day while decreasing the severity at night.
Similarly, drugs and alcohol are found to increase the severity level significantly under the dark-not-lighted condition, while they have a limited influence under daylight and dark-lighted conditions.
American Psychological Association (APA)
Wei, Xinxin& Shu, Xiang& Huang, Baoshan& Taylor, Edward L.& Chen, Huaxin. 2017. Analyzing Traffic Crash Severity in Work Zones under Different Light Conditions. Journal of Advanced Transportation،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1170809
Modern Language Association (MLA)
Wei, Xinxin…[et al.]. Analyzing Traffic Crash Severity in Work Zones under Different Light Conditions. Journal of Advanced Transportation No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1170809
American Medical Association (AMA)
Wei, Xinxin& Shu, Xiang& Huang, Baoshan& Taylor, Edward L.& Chen, Huaxin. Analyzing Traffic Crash Severity in Work Zones under Different Light Conditions. Journal of Advanced Transportation. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1170809
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170809