Profiling of Priority Sections for FWD Surveys Using Prediction Reduals From Deterioration Heterogeneity Modeling

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Key Points

The aim is to predict early deterioration areas of pavement using advanced statistical modeling techniques.
Utilized a mixed Markov deterioration hazard model to predict pavement deterioration.
Applied random forest analysis to evaluate the impact of various deterioration factors not included in the main model.
Extracted high-priority locations for FWD surveys using prediction residuals from the model.
Identified key areas where FWD surveys provide the most benefit based on deterioration predictions.
Demonstrated the effectiveness of mixed Markov models in forecasting pavement conditions.
Enhanced understanding of the influence of various deterioration factors through random forest analysis.

Identifies priority locations for FWD surveys in early deterioration areas, suggesting targeted interventions.

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Yotsui et al. (2026) studied this question.

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