Assessment of uncertainty propagation using first-order Markov chain for maintenance of pavement degradation

ABSTRACT

The first-order Markov Chain (MC) is used to predict the degradation of three types of pavements (rigid, semi-rigid, and mix) utilising database in the five departments in the West of France. The assessment of uncertainty in the MC evolution is presented through studying the trend of mean and standard deviation, for components of the transition probabilities (TP) using different time steps (2, 3, 4, 5 and 6 years). The results show that the trend of rigid pavements is constant with time in terms of coefficient of variation. For semi-rigid and mix pavements, the trend of the standard deviation was constant with time. These statistical properties offer the opportunity to provide uncertainty modelling of TP. The propagation of uncertainty for 2 and 6 years time steps through the prediction of pavement condition index is also performed for analysing the effect of the uncertainty. We compare the profile of states obtained from each time step in view to analyse the short (2 years) and medium term (6 years) potential of prediction.

KEYWORDS:

• First-order Markov chain
• uncertainty
• pavement
• degradation
• time steps

Acknowledgements

The authors are grateful to the Erasmus Mundus PEACE Program – Lot 2 for the financial support of the Research. Moreover, the authors would like to thank a lot the IFSTTAR in general and Dr Philippe Lepert at specific for providing the pavement database used in our research paper.

Disclosure statement

No potential conflict of interest was reported by the authors.