• Journal of Korean Society for Geospatial Information Science
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• v.12 no.3 s.30
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• pp.51-59
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• 2004

In the study, there has been a sharp upward trend in road maintenance cost as the expansion of road networks increases. Running a pavement management system(PMS) is indispensable for efficient and scientific maintenance of the whole road networks with limited maintenance budgets. With a PMS, a maintenance plan should be drawn up after surface conditions are precisely examined and analyzed. The majority of the present PMSs are run by the fact that experts first examine surface conditions on sites, and then enter results into systems. However, considering the actual circumstances of the present time and the increase in paved road hereafter, it is inefficient that experts examine the whole paved roads in person and long-lasting PMSs can not be kept up. As a result, after analyzing the accuracy of 3-D coordinates representing road surfaces that was decided using multi orientation and digital photogrammetry, the average of standard errors turned out to be 0.0427m on the X-axis, 0.0527m on the Y-axis and 0.1539m on the Z-axis. It was found to be good enough to be put to practical use for maps drawn on scales below 1 :1000, which are being currently made and used within the country, and GIS data.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.35-46
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• 2007

In the study digital imagery was used to examine asphalt concrete pavements. With digitally mastered-image information that was filmed with a video camera fixed on a car travelling on road at a consistent speed, a road surface management system that can gain road surface information (Crack, Rutting, IRI) was developed using an object-oriented language "Delphi". This system was designed to improve visualized effects by animations and graphs. After analyzing the accuracy of 3-D coordinates of road surfaces that were decided using multiple image orientation and bundle adjustment method, the average of standard errors turned out to be 0.0427m in the X direction, 0.0527m in the Y direction and 0.1539m in the Z direction. As a result, it was found to be good enough to be put to practical use for maps drawn on scales below 1/1000, which are currently producted and used in our country, and GIS data. According to the analysis of the accuracy in crack width on 12 spots using a digital video camera, the standard error was found to be ${\pm}0.256mm$, which is considered as high precision. In order to get information on rutting, the physically measured cross sections of 4 spots were compared with cross sections generated from digital images. Even though a maximum error turned out to be 10.88mm, its practicality is found in work efficiency.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.31-39
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• 2012

On rainy days, water films form on wet road surfaces and reduce the braking force of vehicles, which often ends up in accidents. For safe driving, the road information signage provides information on road and weather conditions warning drivers of wet road conditions. Still, current information on road conditions is neither localized nor detailed but universal. The present study used the images on CCTVs installed on roads to compare the images of road surfaces in an attempt to suggest a mechanism determining factors that hamper safe driving based on the images. In the image comparison, a normal road image taken on a sunny day is used as an original image, against which road conditions occurring on rainy days are categorized and determined on a case-by-case basis to provide drivers with early warning for the sake of safe driving.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.23-26
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• 2000

An improved inverse perspective mapping (IIPM) is proposed so as to reduce computational expense of recovery of 3D road surface. An experimental system based on IIPM is developed to detect lane parameters for a driver assistant system. A re-organized image is obtained quickly and exactly by IIPM. Efficient preprocessing techniques are used to enhance the information of lane and obstacles. Lane in the preprocessed. image is located with region identification. Lane parameters are estimated effectively. An algorithm to adaptively modify the parameters of IIPM is given. Properties of obstacle on 3D road surface are discussed and used to detect obstacles in the current lane and neighboring lanes. Experimental results show that the new method can extract lane state information effectively.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.223-232
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• 2021

In general, stormwater flows to the road surface, especially in urban areas, and it is discharged through the drainage grate inlets on roads. The appropriate evaluation of the road drainage capacity is essential not only in the design of roads and inlets but also in the design of sewer systems. However, the method of road surface flow analysis that reflects the topographical and hydraulic conditions might not be fully developed. Therefore, the enhanced method of road surface flow analysis should be presented by investigating the existing analysis method such as the flow analysis module (uniform; varied) and the flow travel time (critical; fixed). In this study, the algorithm based on varied and uniform flow analysis was developed to analyze the flow pattern of road surface. The numerical analysis applied the uniform and varied flow analysis module and travel time as parameters were conducted to estimate the characteristics of rainfall-runoff in various road conditions using the developed algorithm. The width of the road (two-lane (6 m)) and the slope of the road (longitudinal slope of road 1 - 10%, transverse slope of road 2%, and transverse slope of gutter 2 - 10%) was considered. In addition, the flow of the road surface is collected from the gutter along the road slope and drained through the gutter in the downstream part, and the width of the gutter was selected to be 0.5 m. The simulation results were revealed that the runoff characteristics were affected by the road slope conditions, and it was found that the varied flow analysis module adequately reflected the gutter flow which is changed along the downstream caused by collecting of road surface flow at the gutter. The varied flow analysis module simulated 11.80% longer flow travel time on average (max. 23.66%) and 4.73% larger total road surface discharge on average (max. 9.50%) than the uniform flow analysis module. In order to accurately estimate the amount of runoff from the road, it was appropriate to perform flow analysis by applying the critical duration and the varied flow analysis module. The developed algorithm was expected to be able to be used in the design of road drainage because it was accurately simulated the runoff characteristics on the road surface.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.104-113
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• 2019

The road management institute needs lots of cost to repair road surface damage. These damages are inevitable due to natural factors and aging, but maintenance technologies for efficient repair of the broken road are needed. Various technologies have been developed and applied to cope with such a demand. Recently, maintenance technology for road surface damage repair is being developed using image information collected in the form of a black box installed in a vehicle. There are various methods to extract the damaged region, however, we will discuss the image recognition technology of the deep neural network structure that is actively studied recently. In this paper, we introduce a new neural network which can estimate the road damage and its location in the image by region-based convolution neural network algorithm. In order to develop the algorithm, about 600 images were collected through actual driving. Then, learning was carried out and compared with the existing model, we developed a neural network with 10.67% accuracy.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.4 s.22
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• pp.77-84
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• 2002

Recently, damage of pavement represented by crack is depened by the increase of traffic demand up to ten million and wight, and interest about the efficient management of pavement is being increased gradually according to the growth of maintenance expense of road surface. In this study, the possibility of application for acquisition of crack information was tested by appling DCRP and digital image processing technique and measuring crack on road surface precisely. Based on this, objective and efficient road surface measurement was planned and done. Measuring crack width, acquire result of comparative high accuracy. So, it is considered that it can be utilized as plan draft data for deterioration estimation and repair reinforcement work of pavement.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.599-604
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• 2008

Recently, many researches for autonomous mobile system have been proposed, which can recognize surrounded environment and navigate to destination without outside intervention. The basic sufficient condition for the autonomous mobile system is to navigate to destination safely without accident. In this paper, we propose a path planning method in local region for safe navigation of autonomous system through evaluation of the road surface distortion(damaged/deformed road, unpaved road, obstacle and etc.). We use laser distance sensor to get the information on the road surface distortion and apply image binalization method to evaluate safe region in the detected local region. We show the validity of the proposed method through the computer simulation based on the artificial local road map.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.319-324
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• 2004

With a PMS, a maintenance plan should be drawn up after surface conditions are precisely examined and analyzed. The majority of the present PMSs are run by the fact that experts first examine surface conditions on sites, and then enter results into systems. However, considering the actual circumstances of the present time and an increase in paved road hereafter, it is inefficient that experts examine the whole paved roads in person and long-lasting PMSs can not be kept up. Therefore, in the study digital photogrammetry was used to examine asphalt concrete pavements. In a consequence, it was found that if databases are implemented in the future with quality digital image information accumulated from studies on roads, they will be able to provide the field of pavement management system with a large amount of information and data.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.155-166
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• 2019

Road infrastructure has increased explosively due to economic development after industrialization and at present road infrastructure is being changed and increased by construction of new roads and maintenance and expansion of existing roads. Such road infrastructure should support safe driving. Road management plays an important role in safe driving. The purpose of this dissertation is to verify predictability of dangerous sections by analyzing road geometrical structure such as surface irregularity and superelevation for some sections in Central Inland Expressway by MMS and present ways of managing roads using MMS. Having analyzed surface irregularity of roads by using MMS, it was found that over 50 percent of all eight sections, targets of this study need betterments and for superelevation, over 50 percent of two sections goes against superelevation standard. Targets of this study are sections that accidents occurred frequently based on history of past accidents and predictability of dangerous sections can be verified through analysis of road geometrical structure using MMS. Using MMS data created by construction of high definition maps which are being undergone for all roads and methods proposed by this study will help investigate dangerous sections efficiently according to road environment. A result of MMS can be used for maintenance of road furniture.