A variety of advantages of railroads over other modes of transportation such as safety, more capacity, and reduction in environmental pollutions has caused its daily expansions. To sustain its high safety as well as using the uppermost capacity of this mode of transportation, it seems inevitable to develop a maintenance program for railroads. Such a development requires profound knowledge of the track degradation rate to predict its future conditions. The purpose of this study is to present an optimized method for development of a track geometrical degradation model. First, using the track quality index, a regression model was developed based on the data gathered by track geometrical condition monitoring cars in two years. Then, a probabilistic degradation model was developed using Markov Chain. For this purpose, the transition matrices were obtained on the basis of expert opinions and probing the data gathered by the cars. Finally, having compared models developed using regression and Markov Chain methods, it is concluded that the models do not have statistically significant difference.
Eslami Khouzani, A. H., Golroo, A., & Bagheri, M. (2017). Presenting a Method for the Development of Track Geometrical Degradation Model: Regression or Markov Chain. Quarterly Journal of Transportation Engineering, 8(3), 355-369.
MLA
Amir Hossein Eslami Khouzani; Amir Golroo; Morteza Bagheri. "Presenting a Method for the Development of Track Geometrical Degradation Model: Regression or Markov Chain". Quarterly Journal of Transportation Engineering, 8, 3, 2017, 355-369.
HARVARD
Eslami Khouzani, A. H., Golroo, A., Bagheri, M. (2017). 'Presenting a Method for the Development of Track Geometrical Degradation Model: Regression or Markov Chain', Quarterly Journal of Transportation Engineering, 8(3), pp. 355-369.
VANCOUVER
Eslami Khouzani, A. H., Golroo, A., Bagheri, M. Presenting a Method for the Development of Track Geometrical Degradation Model: Regression or Markov Chain. Quarterly Journal of Transportation Engineering, 2017; 8(3): 355-369.
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