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Peng Xu [1] and Reng-Kui Liu [1] and Feng Wang [2] and Fu-Tian Wang [1] and Quan-Xin Sun [1]

Academic Editor: Heiner Bubb

, 1, , Beijing Jiaotong University, , MOE Key Laboratory for Urban Transportation Complex Systems Theory, , 3 Shang Yuan Cun, , Beijing 100044, , China, , njtu.edu.cn,

, 2, , Shanghai Bureau of China Railways, , 355 Mo Ling Road, 3rd Floor, , Shanghai 200070, , China, , shrail.com,

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.

1. Introduction

Traffic accidents have long been social-economical problem which has caused increasing concerns to the public worldwide [1]. According to statistics on train accidents by Office of Safety of US Federal Railroad Administration, 542933 people were injured or killed by railway accidents mainly resulting from railway track from January 1975 to May 2011 [2].

Transportation systems play a critical role in the development of society and economy. Railway system constituted the largest part of national freight ton-miles, for example, 38.2% in 2005 in USA [3] and 49.70% in 2005 in China [4]. Railroad track as a base element of the railway system greatly and directly influences safety and cost efficiency of rail transport. In the process of track management, maintenance-of-way departments have to try to balance the cost associated with potential damages arising from unfavorable tracks and the cost for Maintenance & Renewal activities to minimize the life cycle cost of track. To attain the minimization of the life cycle cost, there are key issues which need to be addressed. One of them is the railroad track condition forecast technology which is able to allow maintenance-of-way departments to acquire accurate track condition information two or three months in advance. Such information is essential to optimally schedule Maintenance & Renewal activities, constrained by limited budgets and maintaining track in allowable condition, to minimize influences of the activities on rail traffic.

To date, there are several track condition prediction methods developed throughout the world by researchers of universities, technology firms, and railroads. Researchers of the Railway Technical Research Institute of Japan employed Double Exponential Smoothing method to develop track degradation models for predicting...

                                         

              

                                         

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