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Validation of a Low-Cost Pavement Monitoring Inertial-Based System for Urban Road Networks

Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, a novel inertial sensor-based system is proposed using a low-cost inertial measurement unit (IMU) and a global positioning system (GPS)...

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Detalles Bibliográficos
Autores principales: Loprencipe, Giuseppe, de Almeida Filho, Flavio Guilherme Vaz, de Oliveira, Rafael Henrique, Bruno, Salvatore
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125624/
https://www.ncbi.nlm.nih.gov/pubmed/33946324
http://dx.doi.org/10.3390/s21093127
Descripción
Sumario:Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, a novel inertial sensor-based system is proposed using a low-cost inertial measurement unit (IMU) and a global positioning system (GPS) module, which are connected to a Raspberry Pi Zero W board and embedded inside a vehicle to indirectly monitor the road condition. To assess the level of pavement decay, the comfort index a(wz) defined by the ISO 2631 standard was used. Considering 21 km of roads with different levels of pavement decay, validation measurements were performed using the novel sensor, a high performance inertial based navigation sensor, and a road surface profiler. Therefore, comparisons between a(wz) determined with accelerations measured on the two different inertial sensors are made; in addition, also correlations between a(wz), and typical pavement indicators such as international roughness index, and ride number were also performed. The results showed very good correlations between the a(wz) values calculated with the two inertial devices (R(2) = 0.98). In addition, the correlations between a(wz) values and the typical pavement indices showed promising results (R(2) = 0.83–0.90). The proposed sensor may be assumed as a reliable and easy-to-install method to assess the pavement conditions in urban road networks, since the use of traditional systems is difficult and/or expensive.