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Mathematical Problems in Engineering
Volume 2014, Article ID 832723, 5 pages
http://dx.doi.org/10.1155/2014/832723
Research Article

The Model of Severity Prediction of Traffic Crash on the Curve

1State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
2College of Transportation, Jilin University, Changchun 130022, China
3Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650224, China

Received 5 September 2013; Revised 20 November 2013; Accepted 29 November 2013; Published 9 January 2014

Academic Editor: Wuhong Wang

Copyright © 2014 Jian-feng Xi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.