Title
Freeway Work-Zone Crash Analysis And Risk Identification Using Multiple And Conditional Logistic Regression
Keywords
Accidents; Construction sites; Driver behavior; Highway construction; Regression models; Statistics
Abstract
Work-zone safety continues to be a priority and a concern for the Federal Highway Association as well as most state departments of transportation. The main objective of this study is to uncover work-zone freeway crash characteristics to help develop countermeasures that limit work-zones' hazards. The Florida Crash Records Database for years 2002, 2003, and 2004 was utilized for this study. Conditional logistic regression along with stratified sampling and multiple logistic regression models were estimated to unveil work-zone freeway crash traits. According to the models' results, roadway geometry, weather condition, age, gender, lighting condition, residence code, and driving under the influence of alcohol and/or drugs are significant risk factors associated with work-zone crashes. © 2008 ASCE.
Publication Date
5-1-2008
Publication Title
Journal of Transportation Engineering
Volume
134
Issue
5
Number of Pages
203-214
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1061/(ASCE)0733-947X(2008)134:5(203)
Copyright Status
Unknown
Socpus ID
42449154324 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/42449154324
STARS Citation
Harb, Rami; Radwan, Essam; Yan, Xuedong; Pande, Anurag; and Abdel-Aty, Mohamed, "Freeway Work-Zone Crash Analysis And Risk Identification Using Multiple And Conditional Logistic Regression" (2008). Scopus Export 2000s. 9905.
https://stars.library.ucf.edu/scopus2000/9905