Open AccessAnalysis of traffic accident severity in Baghdad city using Binary Logistic Regression Model
Author(s) -
Hasan H. Joni,
Ali Al-Dahawi,
Omar Jabbar Al-Tamimi
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/737/1/012140
Subject(s) - logistic regression , accident (philosophy) , traffic accident , sample (material) , environmental health , regression analysis , work (physics) , statistics , transport engineering , medicine , engineering , mathematics , mechanical engineering , philosophy , chemistry , epistemology , chromatography
Severity of accident is an important issue to researchers in road safety since this work is interested not only with the prevention of accidents but also with the factors that enhance in reduction of their severity. One of the ways to achieve the latter is to determine the potential factors that influence the severity of accident. This research can be considered as one of the few studies in this approach in Iraq, especially in Baghdad City, where the analysis of accidents has not been carried out for many years since 2003, especially analysis of accidents’ severity. Therefore, it is essential to establish baseline information on accident severity. The data utilized in this research consists of a sample size of (268) observations and it was collected manually from traffic officers due to the deficiency in record system (as there is no specific archive system for registered accident reports). The results from binary logistic regression model indicate that there are three variables significantly associated with severity of accidents namely; site, vehicle body type, and cause of accident.