Computational modeling demonstrates rapid structural number estimation from traffic speed deflection device data, indicating streamlined network-level pavement management.
Integrating traffic speed deflection device (TSDD) structural data into pavement management improves decision-making, budget allocation, and treatment prioritisation. Pavement engineers often use the effective structural number (SNeff) as an indicator of structural capacity, but the American Association of State Highway and Transportation Officials (AASHTO) method for SNeff was developed for falling weight deflectometer (FWD) data and relies on computationally intensive iterative processes. Differences in loading and measurement between FWD and TSDD also raise concerns about its direct use for TSDD data. This study introduces a streamlined, non-iterative method for estimating SNeff from TSDD data, developed using Long-Term Pavement Performance data and simulated datasets. A database of 32,640 cases representing various pavement structures was generated, with FWD and TSDD responses simulated and reference SNeff values derived using AASHTO’s method. A closed-form solution was proposed to efficiently estimate from TSDD data, and its accuracy was validated using field data from multiple projects.
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Nadkarni et al. (2026) studied this question.
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