Desenvolvimento do índice funcional de vias não pavimentadas RIA-UR baseado no uso de acelerômetro em reboque do tipo carretinha

Abstract

The management of urban and road networks is a responsibility of agencies in charge of maintaining these infrastructure elements; however, its implementation is not simple. Many condition indices are commonly used to assess the current state of a roadway, evaluating whether it provides adequate conditions for safe, comfortable, and economical traffic. Although widely applied, these indices require highly qualified professionals for data collection and analysis and do not always allow rapid assessment as required by road management agencies.This study proposes the development of a functional index based on accelerations generated during travel on unpaved roads, using the road network of the municipality of Guarapuava, Paraná, Brazil, as a case study. The proposed index, named Road Index by Accelerometer – Unpaved Roads (RIA-UR), was developed using acceleration data collected from a smartphone accelerometer installed on a utility trailer.The methodology enabled the establishment of both a simple classification system and a dual classification system capable of indicating the progression between different functional states. These classifications can be applied at both the network level, using average RMS values, and at the project level, by identifying sequences of sections with high resultant RMS values along the roadway.Additionally, a mounting device was developed to position a smartphone on a vehicle seat, aiming to approximate the behavior of a standardized seat accelerometer and to record vibrations transmitted to the driver simultaneously with the measurements obtained from the trailer. Correlation and linear regression analyses were conducted among the axes of the trailer system, among the axes of the seat accelerometer, and between both systems.Measurements were carried out on ten unpaved urban roads under different conditions and locations, totaling approximately 5km in length, evaluated in two data collection campaigns separated by an interval of about two months. The results indicate that the proposed index presents potential applicability for unpaved road management, enabling the monitoring of functional conditions and supporting maintenance and rehabilitation decision-making. For instance, a reduction in average RMS values and in the number of critical sections was observed on Gramados Road, where maintenance interventions were identified. Conversely, roads such as Costa e Silva showed deterioration associated with the absence of maintenance and worsening surface conditions.The index can also be extended to other types of road surfaces, allowing rapid data acquisition over long distances by non-specialized users. Although linear regressions between the axes of different systems did not show consistent results, correlations within the trailer system were satisfactory, with R² values of at least 0.76. Additionally, 63.6% of the predominant frequencies measured at the seat were within the range of highest human biomechanical sensitivity (4–20 Hz). Nevertheless, equivalent acceleration values remained below the health risk limits established by ISO 2631 and NHO-09 standards.