The applicability of published pavement deterioration models for national roads

Abstract

The growing interest in pavement management systems (PMSs), both in South Mrica and internationally, has been in response to a shift in importance from the construction of new roads to the maintenance of the existing paved network coupled with increasingly restrictive road funding. In order to develop a balanced expenditure programme for the national roads of South Africa there is a need to predict the rate of deterioration of a pavement and the nature of the changes in its condition so that the timing, type and cost of maintenance needs could be estimated. Internationally these expected changes in pavement condition are predicted by pavement deterioration models, which normally are algorithms developed mathematically or from a study of pavement deterioration. Since no usable pavement deterioration models existed locally, it was necessary to evaluate overseas literature on pavement deterioration prediction models with the aim of identifying models possibly applicable to the national roads of South Africa. Only deterioration models developed from the deterioration results of inservice pavements under a normal traffic spectrum were evaluated. Models developed from accelerated testing were avoided since these models virtually eliminated long·term effects (these are primarily environmental but also include effects of the rest periods between loads), and that the unrepresentative traffic loading regimes can distort the behaviour of the pavement materials, which is often stress dependent. Models developed from the following studies were evaluated: • AASHO Road Test • The Kenya study • Brazil-UNDP study (HDM-ill models) • Texas study Of all the above models studied that were developed from major studies it was concluded that the incremental models developed during the Brazil study, were the most appropriate for further evaluation under South African conditions. A sensitivity analysis was conducted on the HDM-III models to evaluate their sensitivity to changes in the different parameters comprising each model. The results obtained from the sensitivity analysis indicate that the incremental roughness prediction model incorporated into the HDM-III model tends to be insensitive to changes in most parameters. Accuracy ranges for input data were, however, also identified for parameters which indicated an increase in sensitivity in certain ranges. The local applicability of the HDM-III deterioration models were finally evaluated by comparing HDM-III model predictions with the actually observed deterioration values of a selected number of national road pavement sections. To enable the above comparison, a validation procedure had to be developed according to which the format of existing data could be transformed to that required by the HDM-ill model, as well as additional information be calculated. From the comparison it was concluded that the HDM-III models are capable of accurately predicting the observed deterioration on South African national roads, but that for most models calibration is needed for local conditions. Guidelines regarding recommended calibration factor ranges for the different HDM-ill models are given. Finally it is recommended that the HDM-III models should be considered for incorporation into a balanced expenditure programme for the national roads of South Africa.