Research Article | OPEN ACCESS
Mountainous Freeway Risk Degree Forecast Model of Case Study: Changjin Freeway in Jiangxi Province
Chunbo Zhang, Yingfang Ma and Kuanmin Chen
School of Highway, Chang’an University, Xi’an 710064, China
Research Journal of Applied Sciences, Engineering and Technology 2013 17:4395-4398
Received: October 30, 2012 | Accepted: December 20, 2012 | Published: May 01, 2013
Abstract
The objective of this study is to establish the mountainous freeway risk degree forecast model. Highway safety, especially mountainous freeway, relates to person, vehicle, road and environment four aspects including many factors. Firstly, this study analyzed some researches about the highway safety from these four aspects respectively. Secondly, this study considered many factors of these four aspects, established the mountainous freeway risk degree forecast model, listed the survey content needed in the forecast model. Finally, this study took Changjin Freeway in Jiangxi Province, China as example, used 91 accident data from January, 2006 to July, 2012, adopted the multiple linear regression method using spss 17.0 to obtain each parameter value of the forecast model and analyzed some parameter values to the mountainous freeway safety. The mountainous freeway risk degree forecast model is necessary and useful to evaluate the risk degree for constructed mountainous freeway, to estimate the safety of unconstructed mountainous freeway and to provide basis to improve mountainous freeway safety.
Keywords:
Highway safety, multiple linear regression, mountainous freeway, risk degree forecast model,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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