DocumentCode
2537221
Title
Analysis of the logistic model for accident severity on urban road environment
Author
Zhuanglin Ma ; Shao, Chunfu ; Yue, Hao ; Sheqiang Ma
Author_Institution
MOE Key Lab. for Transp. Complex Syst., Beijing Jiaotong Univ., Beijing, China
fYear
2009
fDate
3-5 June 2009
Firstpage
983
Lastpage
987
Abstract
In order to identify the possible contributory factors on urban road environment to accident severity, the logistic regression model was applied to traffic accident data collected from police-reports. A total of 2117 accidents occurred in Shijiazhuang in 2002 were considered for the purpose of this paper. Accident severity (dependent variable) in this paper is a dichotomous variable with two categories: extra serious or major accident and ordinary or minor accident. Because of the binary nature of this dependent variable, the logistic regression model was found suitable. Of nine independent variables obtained from police-reports, five were found most significant associated with accident severity, namely, road cross-section, accident location, road alignment, road type and lighting condition. A statistical interpretation is given of the model-developed estimates in terms of odds ratio concept. The findings show that the logistic regression model as used in this paper provides a better understanding of risk factors related to urban road environment.
Keywords
accidents; logistics; regression analysis; road safety; traffic; Shijiazhuang; accident location; accident severity; dichotomous variable; lighting condition; logistic regression model; major accident; minor accident; odds ratio concept; police-reports; road alignment; road cross-section; road type; statistical interpretation; traffic accident data; urban road environment; Electronic mail; Engineering management; Environmental management; Injuries; Logistics; Road accidents; Road safety; Road transportation; Traffic control; Vehicle crash testing; accident severity; logistic model; traffic safety; urban road environment;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium, 2009 IEEE
Conference_Location
Xi´an
ISSN
1931-0587
Print_ISBN
978-1-4244-3503-6
Electronic_ISBN
1931-0587
Type
conf
DOI
10.1109/IVS.2009.5164414
Filename
5164414
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