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Evaluation of pavement condition index by different methods: Case study of Maringá, Brazil

Jéssica Marcomini Pinatt, Marcelo Luiz Chicati, Jesner Sereni Ildefonso, Cláudia Regina Grégio D'arce Filetti

2020Transportation Research Interdisciplinary Perspectives32 citationsDOIOpen Access PDF

Abstract

In order to speed up and prioritize investments in pavement recovery, it is necessary to perform localization and characterization studies of the defects. Thus, the objectives of this study were to analyze the objective and subjective evaluations of the Pavement Condition Index (PCI) used in the Urban Pavement Management System (UPMS) using GIS and identify the most damaged pathways. This research was carried out in the state of Paraná (PR), Brazil. A functional evaluation was performed, with defect identification by means of visual analysis using the PCI method. Two types of evaluation were performed, objective and subjective, which were compared to each other using the coefficient of Pearson's correlation. Subsequently, maps were generated in the ArcGIS 10.2 software. It was observed that 92.21% of the sections were classified as “very good” to “fair,” whereas 7.94% were classified as “poor” or “very poor”. It was possible to prove the similarity between the results of the objective and subjective evaluations from Pearson's correlation. The coefficient resulted in 0.95, a value close to 1 which represents a strong correlation between the data. Thus, the PCI can be determined more quickly and simply through subjective evaluations. Subjective evaluations are indicated for cities where maintenance is performed without any planning, it is a simplified way to evaluate the pavement and have good results. The use of the GIS tool facilitated the visualization of the pavement conditions in the different sections.

Topics & Concepts

Pearson product-moment correlation coefficientCorrelation coefficientPavement managementConventional PCIVisualizationComputer scienceIndex (typography)CorrelationStatisticsIdentification (biology)Data miningMathematicsTransport engineeringEngineeringMedicineWorld Wide WebBiologyPsychiatryBotanyMyocardial infarctionGeometryInfrastructure Maintenance and MonitoringTraffic and Road SafetyTraffic Prediction and Management Techniques