Open AccessThe Model of Severity Prediction of Traffic Crash on the Curve
Author(s) -
Jianfeng Xi,
Hai-zhu Liu,
Wei Cheng,
Zhonghao Zhao,
Tongqiang Ding
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/832723
Subject(s) - crash , logistic regression , sample (material) , reliability (semiconductor) , statistics , transport engineering , ordered logit , regression analysis , engineering , computer science , mathematics , power (physics) , chemistry , physics , chromatography , quantum mechanics , programming language
With the study of traffic crashes on curved road segments as the focus of research, a logistic regression based curve road crash severity prediction model was established based on a sample crash database of 20000 entries collected from 4 regions of China and 15 evaluation indicators involving driver, driving environment, and traffic environment factors. Maximum Likelihood Estimation and step-back technique were deployed for data analysis, the conclusion of which is that the three main contributory factors on curve road crash severity are weather, roadside protection facility, and pavement structure. Hosmer and Lemeshow tests were used to verify the reliability of the model, and the model variables were discussed to a certain degree as well
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