• Journal of the Institute of Convergence Signal Processing
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• v.21 no.3
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• pp.127-132
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• 2020

In this study, the process of providing information necessary to remove physical barriers such as road slopes that obstruct the activities of the disabled is in progress. Through experiments, we implement a quantified road surface roughness index that enables the implementation of IoT-based systems necessary for the elderly and the disabled to safely move to their destination. As a preliminary study, a road surface measurement device using a gyroscope was devised. To check the roughness and flatness of the road surface, X, Y displacement, and acceleration displacement were measured using a gyroscope. By calculating the measured data, the roughness and flatness of the road surface were quantified from 0 to 100. We implemented an algorithm that divides this index into 4 stages, displays it on a map, and provides it to users. Finally, a system for the disabled and elderly electric wheelchair users to secure basic mobility was established.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.1
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• pp.9-17
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• 2005

The objective of the study is to extract information about the road surfaces to be studied by analyzing asphalt concrete-paved road surface images photographed with a digital video camera. To analyze the accuracy of road surface information gained using a digital imagery processing method, it was compared and analyzed with the outcomes of control surveying. As a result, an average error of 0.0427 m in the X-axis direction, that of 0.0527 m in the Y-axis direction, and that of 0.1539 m in the Z-axis direction were found, good enough for mapping at a scale of 1:1,000 or less and GIS data. Besides, information on road surface assessment factors such as crack ratio, the amount of rutting and profile index was gained by analyzing processed digital imagery. This information made it possible to conduct road surface assessment by generating PSI and MCI. As quality digital image information has been gathered from roads and stored, important fundamental data on PMS (Pavement Management System) will become available in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.757-767
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• 2016

The power spectral density (PSD) for the road surface roughness on the bridges of minor roads in Wonju city and Hoengseong-gun, Gangwon-do is presented. To obtain the PSD, the road surface roughness on 18 different bridges with various superstructure type and span is measured by GPS at every 10 to 30cm interval. Assuming the PSD as the stationary normal probability process with zero mean value, the PSD of measured road surface roughness is obtained by applying the Maximum Entropy Method (MEM). A simple formula in evaluating the PSD of RC slab bridge, Rahmen bridge and PSC I-girder bridge which is applicable to the dynamic response analysis of bridges considering the road surface roughness is proposed. Using the calculated PSD curves, the road surface conditions on the 18 bridges are evaluated. The statistical relationship between the PSD and the IRI is presented by applying linear regression and correlation analysis.

• Journal of IKEEE
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• v.5 no.1 s.8
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• pp.75-84
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• 2001

The reliable data relating to the condition of road surface is of increasing importance to deliver the road condition to driver and road management authority. This paper describes the development of a new high-speed. automatic, road data collection system, which collects the longitudinal road data with ${\sim}30cm$ interval covering full width of the road at 100km/h speed. The system calculates the international roughness index (IRI) from the collected data and displays the IRI and road profile data on the screen. To develope the system, we implement an optical range finder, advanced distance and motion detectors, and signal processing and display modules. The measurement accuracy of the system at 70km/h operation speed shows ${\pm}0.1m/km$ in the IRI for the standard road. To confirm the performance of the developed system, we also measure the IRI of a deployed highway road and compare the results with a conventional system and human eye measurement results.