A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Modeling Subjective Condition Data of Asphalt Surfaced Urban Pavements
This chapter presents the application of Markov chain (MC) modeling of pavement subjective performance data to facilitate easy adoption by practitioners. The objective is to develop deterioration models of asphalt surfaced urban pavements from surface inspection rating (SIR) data for use in planning and identifying resurfacing maintenance priorities at network level. The modeling approaches used include the deterministic approach, using regression analysis, and the probabilistic approach, using MCs. The deterioration process is modeled by multiplying the start (or initial) state vector by the transition probability matrix. The chapter shows the weighted average values of probabilities predicted by the MC model developed from the initial vector and weighted by mid‐range values compared with the predictions of the logarithmic regression model over 30 years period. For the condition data used herein, the comparison of models indicates that predictions of MC model for the condition of a pavement segment are close to local experience and knowledge.
Modeling Subjective Condition Data of Asphalt Surfaced Urban Pavements
This chapter presents the application of Markov chain (MC) modeling of pavement subjective performance data to facilitate easy adoption by practitioners. The objective is to develop deterioration models of asphalt surfaced urban pavements from surface inspection rating (SIR) data for use in planning and identifying resurfacing maintenance priorities at network level. The modeling approaches used include the deterministic approach, using regression analysis, and the probabilistic approach, using MCs. The deterioration process is modeled by multiplying the start (or initial) state vector by the transition probability matrix. The chapter shows the weighted average values of probabilities predicted by the MC model developed from the initial vector and weighted by mid‐range values compared with the predictions of the logarithmic regression model over 30 years period. For the condition data used herein, the comparison of models indicates that predictions of MC model for the condition of a pavement segment are close to local experience and knowledge.
Modeling Subjective Condition Data of Asphalt Surfaced Urban Pavements
Torrenti, Jean‐Michel (editor) / La Torre, Francesca (editor)
Materials and Infrastructures 1 ; 269-285
2016-06-30
17 pages
Article/Chapter (Book)
Electronic Resource
English
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