Simulating pavement structural condition using artificial neural networks

TLDR

The study investigates the feasibility of using an artificial neural network to model pavement structural condition within pavement management systems. The authors developed an ANN model trained on field‑gathered strain data derived from falling‑weight deflectometer measurements and ground‑penetrating radar thickness estimates, using strain assessment criteria to characterize fatigue failure of flexible asphalt pavements. A paper exercise shows the ANN model can classify pavement sections for maintenance or rehabilitation, and preliminary results suggest it can aid policy makers in optimizing pavement maintenance planning. FWD measurements were back‑analysed to derive strain data used as ANN outputs.

Abstract

This article aims to investigate the feasibility of incorporating of an artificial neural network (ANN) as an innovative technique for modelling the pavement structural condition, into pavement management systems. For the development of the ANN, strain assessment criteria are set in order to characterise the structural condition of flexible asphalt pavements with regards to fatigue failure. This initial task is directly followed with the development of an ANN model for the prediction of strains primarily based on in situ field gathered data and not through the usage of synthetic databases. For this purpose, falling weight deflectometer (FWD) measurements were systematically conducted on a highway network, with ground-penetrating radar providing the required pavement thickness data. The FWD data (i.e. deflections) were back-analysed in order to assess strains that would be utilised as output data in the process of developing the ANN model. A paper exercise demonstrates how the developed ANN model combined with the suggested conceptual approach for characterising pavement structural condition with regard to strain assessment could make provisions for pavement management activities, categorising network pavement sections according to the need for maintenance or rehabilitation. Preliminary results indicate that the ANN technique could help assist policy decision makers in deriving optimum strategies for the planning of pavement infrastructure maintenance.