Developing optimized prioritizing road maintenance

Ewadh, Hussein Ali; Almuhanna, Raid; Alasadi, Saja · 2018 · Crossref

DOI: 10.1051/matecconf/201816201044

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Summary

This study addresses the challenge of optimizing road maintenance prioritization under limited financial resources, a critical issue for developing nations where infrastructure deterioration incurs significant economic losses. The authors argue that relying solely on the Pavement Condition Index (PCI) to prioritize maintenance is insufficient, as the lowest PCI does not always justify immediate intervention. The research aims to demonstrate optimized methods for ranking maintenance projects to maximize benefits and cost-effectiveness. The study focuses on a selected zone of the roadway system in Karbala city, Iraq, comprising urban streets classified as major/minor arterials, collectors, and local roads. The researchers utilized the PAVER system integrated with Geographic Information Systems (GIS) to estimate and display PCI values. Three prioritization methods were developed and applied: (1) simple ranking by PCI; (2) ranking by multiple measures using a Maintenance Priority Index (MPI); and (3) incremental benefit-cost analysis (BCR) ranking. The MPI method incorporated expert-derived weights for variables including maintenance cost, work easiness, average daily traffic, and functional classification, determined via a questionnaire of 35 experts. The incremental BCR method calculated the ratio of benefits (defined as the decrease in PCI from 100) to costs, using MATLAB software for iterative evaluation. Data for 56 road sections were analyzed, with maintenance costs and easiness scores derived from expert experience and distress type severity. The results indicate that while the three methods produced different visual layouts for priority rankings, statistical analysis revealed no significant difference between them. Using the Wilcoxon signed-rank test in SPSS software, the authors compared the rankings generated by PCI, MPI, and incremental BCR methods. The test results, with a significance level of 0.05, showed that the null hypothesis of no significant difference could not be rejected. Specifically, the Z-scores for comparisons between PCI and MPI, PCI and BCR, and MPI and BCR were all non-significant. This suggests that despite the complexity of the multi-measure and benefit-cost approaches, they yield prioritization outcomes statistically similar to the simpler PCI-based ranking for this specific dataset. The significance of this work lies in providing a structured framework for pavement management in resource-constrained environments. By validating that complex optimization methods align with simpler condition-based rankings, the study supports the use of integrated tools like PAVER and GIS for efficient decision-making. It offers engineers a systematic process to determine maintenance needs, ensuring that allocated funds are used optimally to preserve highway assets and extend pavement life cycles.

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