Infrastructure Deterioration Prediction with a Poisson Hidden Markov Model on Time Series Data

Abstract

AbstractThe deterioration of a pavement surface can be described in terms of the presence and severity of distinct distresses, like potholes, cracking, and rutting. Each deterioration process is ordinarily described by a set of pavement indicators (e.g., number of potholes, percentage of cracks, international roughness index) that are measured during monitoring and inspection activities. Manifestly, there exist statistical correlations among the deterioration processes. For instance, cracks appearing on a road section may contribute to an increase in pothole occurrence, and vice versa. In order to mathematically formulate the statistical interdependency among deterioration processes, a Poisson hidden Markov model is proposed in this paper. The model describes the complex process of pavement deterioration, which includes the frequent occurrence of local damage (e.g., potholes) as well as the degradation of other pavement indicators (e.g., cracks, roughness). To model the concurrent frequency of local damag...