Updating and Improving Statistical Methods for Evaluating the Quality of Travel Based on the Distribution of Defects in Road Pavements
DOI:
https://doi.org/10.5281/zenodo.20166790Keywords:
Travel quality, pavement distress, multiple regression, Likert scales, infrastructure managementAbstract
This paper proposes a methodological update for assessing travel quality on highways based on the relationship between the distribution of pavement surface distresses and scores assigned by trained evaluators. Using data collected from 37 rural highway segments in São Paulo, Brazil, multiple linear regression and classification scales based on the normal distribution were applied. The results indicate that perceived travel quality can be reliably estimated from objective distress variables. Improvements to the original method are suggested, including the incorporation of machine learning techniques and expanded cross-regional data validation. It is concluded that the integration of subjective and objective data can guide maintenance priorities and improve the efficiency of road infrastructure management.
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