Title
Analysis Of Red Light Running Crashes Based On Quasi-Induced Exposure And Multiple Logistic Regression Method
Abstract
According to recent national statistics, red light running crashes represent a significant safety problem at signalized intersections. To examine the overall characteristics of red light running crashes, this study used the 1999 to 2001 Florida crash database to investigate the crash propensity related to traffic environments, driver characteristics, and vehicle types. The quasi-induced exposure concept and multiple logistic regression technique were used to perform this analysis. The results showed that traffic factors including number of lanes, crash time, weather, highway character, day of week, urban or rural location, speed limit, driver age, alcohol or drug use, physical defect, driver residence, and vehicle type were significantly associated with the risk of red light running crashes. Furthermore, it confirmed that there were significant interaction effects between the risk factors, including crash time and highway character, number of lanes and urban or rural location, weather condition and driver age, driver age and gender, alcohol or drug use and gender, and type of vehicle and gender.
Publication Date
1-1-2005
Publication Title
Transportation Research Record
Issue
1908
Number of Pages
70-79
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.3141/1908-09
Copyright Status
Unknown
Socpus ID
32644451606 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/32644451606
STARS Citation
Yan, Xuedong; Radwan, Essam; and Birriel, Elizabeth, "Analysis Of Red Light Running Crashes Based On Quasi-Induced Exposure And Multiple Logistic Regression Method" (2005). Scopus Export 2000s. 4391.
https://stars.library.ucf.edu/scopus2000/4391