Probabilistic model for prediction of international roughness index based on Monte Carlo

Abstract

The IRI International Regularity Index is a performance indicator that evaluates the functional condition of a pavement structure. Its value is a key input for the management of road assets, allowing to establish the opportune moment for carrying out interventions on the pavement. In addition, it is used to receive road surfaces, assess vehicle operating costs, evaluate the profitability of road projects and establish the cash flow in the financial administration of the project. The IRI data obtained from measurements carried out in the field, feed the deterministic deterioration model that allows future estimations of the indicator and the development of pavement maintenance programs. This research proposes to evaluate in a probabilistic way the model of the IRI International Regularity Index of the HDM-4 program, by assigning probability density functions to the input variables from real data taken in the field. To achieve this objective, a Montecarlo-type simulation model was developed, where roads must be classified by their geographical location, structural capacity of the pavement and traffic intensity expressed in Number of Equivalent Axes. The research results provide the IRI characterized by probability density functions, allowing its estimation from an expected reliability value.