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Pavement management systems can be used to efficiently allocate limited maintenance budgets to better align with pavement deterioration. However, pavement deterioration is subject to uncertain factors that complicate the prediction of future pavement conditions accurately, entailing differences in the optimum maintenance strategy. This paper addresses this challenge by introducing a method to aid local engineers in optimising the scheduling of maintenance activities under uncertain pavement deterioration conditions. Markov chains are used to simulate the variability of life-cycle performance. Moreover, a multi-objective optimisation of an urban network is carried out to find the maintenance programme that minimises the mean life-cycle cost, maximises the mean user benefit, and minimises the standard deviation of life-cycle cost. This third objective enables the optimisation routine to minimise the possibility of unintentionally increasing the life-cycle cost due to system variability. This approach results in a reduction of the life-cycle cost variability by up to 62%, provides pavement strategies that benefit road users as a result of better pavement conditions, and reduces the risk of resorting to costly future maintenance activities.

Incorporating pavement deterioration uncertainty into pavement management optimization