Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2013(Vol.5, Issue:17)
Article Information:

Mountainous Freeway Risk Degree Forecast Model of Case Study: Mountainous Freeway Risk Degree Forecast Model of Case Study:

Chunbo Zhang, Yingfang Ma and Kuanmin Chen
Corresponding Author:  Chunbo Zhang 
Submitted: 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.

Key words:  Highway safety, multiple linear regression, mountainous freeway, risk degree forecast model, , ,
Abstract PDF HTML
Cite this Reference:
Chunbo Zhang, Yingfang Ma and Kuanmin Chen, . Mountainous Freeway Risk Degree Forecast Model of Case Study: Mountainous Freeway Risk Degree Forecast Model of Case Study: . Research Journal of Applied Sciences, Engineering and Technology, (17): 4395-4398.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved