Abstract
Almost every today's smartphone is integrated with many useful sensors. The sensors are originally designed to make the smartphones' user interface and applications more convenient and appealing. These sensors, moreover, are potentially useful for many other applications in different fields. Using smartphone sensors to estimate road roughness condition has a great potential, since many similar sensors are already in use in many sophisticated road roughness profilers. This study explores the use of data, collected by sensors from smartphones under realistic settings, in which the smartphones are placed at more realistic locations and under realistic manner inside a moving vehicle, to evaluate its relationship with the actual road pavement roughness. An experiment has been conducted to collect data from smartphone acceleration and Global Positioning System (GPS) sensors; frequency domain analysis is also carried out. It has been revealed that the data from smartphone accelerometers has a linear relationship with road roughness condition, whereas the strength of the relationship varies at different frequency ranges. The results of this paper also confirm that smartphone sensors have a great potential to be used for estimating the current status of the road pavement condition.
Highlights
Maintaining and monitoring road infrastructure is a challenging task for almost all governments and road authorities
A 100-m length of acceleration data is chosen as a unit for road roughness estimation in this study because (i) Road Management System in Laos requires road pavement condition to be estimated for every 100-m section as it is believed to be convenient for maintenance planning, and (ii) there is a concern on the accuracy of Global Positioning System (GPS) position data; choosing a shorter section unit may cause some issues in data matching between Vehicular Intelligent Monitoring System (VIMS) and smartphone GPS data
4 Results and discussion 4.1 Correlation between the sum of magnitudes and International Roughness Index (IRI) In our previous study [3], with the smartphones being fixed to the dashboard of the experiment vehicles, we have observed that road roughness can be estimated from acceleration data
Summary
Maintaining and monitoring road infrastructure is a challenging task for almost all governments and road authorities. The attention that should be addressed on data collection is usually ignored or neglected mainly due to the lack of technology and budget. In these countries, road infrastructure condition data is often left outdated, making it difficult for proper planning and programming of the maintenance. In our previous study [3], we explored the use of smartphones, fixed to vehicles with predetermined orientation, to estimate road roughness where promising results have been observed. This study will take a further step by attempting to estimate road roughness condition from smartphones under more realistic settings, which is beyond fixed orientation and/or fastening the devices themselves tightly with vehicles while collecting data.
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