Literature DB >> 33946324

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

Giuseppe Loprencipe1, Flavio Guilherme Vaz de Almeida Filho2, Rafael Henrique de Oliveira2, Salvatore Bruno1.   

Abstract

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 awz 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 awz determined with accelerations measured on the two different inertial sensors are made; in addition, also correlations between awz, and typical pavement indicators such as international roughness index, and ride number were also performed. The results showed very good correlations between the awz values calculated with the two inertial devices (R2 = 0.98). In addition, the correlations between awz values and the typical pavement indices showed promising results (R2 = 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.

Entities:  

Keywords:  inertial measurement unit; international roughness index; pavement monitoring; ride comfort; ride number; urban road

Year:  2021        PMID: 33946324     DOI: 10.3390/s21093127

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Sensor integration in a low cost land mobile mapping system.

Authors:  Sergio Madeira; José A Gonçalves; Luísa Bastos
Journal:  Sensors (Basel)       Date:  2012-03-02       Impact factor: 3.576

  1 in total
  2 in total

1.  Development and Testing of a 5G Multichannel Intelligent Seismograph Based on Raspberry Pi.

Authors:  Igbinigie Philip Idehen; Qingyu You; Xiqiang Xu; Shaoqing Li; Yan Zhang; Yaoxing Hu; Yuan Wang
Journal:  Sensors (Basel)       Date:  2022-05-31       Impact factor: 3.847

2.  Development of a GIS-Based Methodology for the Management of Stone Pavements Using Low-Cost Sensors.

Authors:  Salvatore Bruno; Lorenzo Vita; Giuseppe Loprencipe
Journal:  Sensors (Basel)       Date:  2022-08-31       Impact factor: 3.847

  2 in total

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