• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.207-218
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• 2006

The extraction of horizontal alignment and cross-section of roads is very important task in road safety diagnosis. Existing road safety diagnosis methods by investigators need much time and expense but don't provide various data. Therefor, we need road shape classification automatically and extraction method of horizontal alignment and cross-section of roads through digital photogrammetry system using GPS-VAN with laser scanner. In this paper, we propose a method of mobile laser scanning data acquisition, processing and developing extraction methods of horizontal alignment and cross-section of roads using mobile laser scanning data by GPS-VAN.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.3-9
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• 2005

The extraction of traffic information based on image processing is under broad research recently because the method based on image processing takes less cost and effort than the traditional method based on physical equipment. The main purpose of the algorithm based on image processing is to extract vehicles from an image correctly. Before the extraction, the algorithm needs the pre-processing such as background subtraction and binary image thresholding. During the pre-processing much noise is brought about because roadside tree and passengers in the sidewalk as well as vehicles are extracted as traffic flow. The noise undermines the overall accuracy of the algorithm. In this research, most of the noise could be removed by extracting the exact road area which does not include sidewalk or roadside tree. To extract the exact road area, traffic lanes in the image were used. Algorithm speed also increased. In addition, with the ratio between the sequential images, the problem caused by vehicles' shadow was minimized.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.233-238
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• 2004

This study deals with the extraction of highway's superelevation using digital imagery which are economic method in constructing database for the side of highway management. Using CCD camera, both center line and shoulder of highway are measured by analyzing the result value and enough result values were obtained. This study is expected to become effective method for extraction of highway alignment elements in the Digital Photogrammetry.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.471-474
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• 2007

On the road, geometric structure such as horizontal alignment, vortical alignment and crossing inclination ate important to explain characteristics of road and safety analysis. Especially, horizontal and vortical alignment are have to do with safety of covering. In existing road, for the safety analysis or alignment improvement and expansion pavement, it needs alignment factor of road. Alignment factor of road can be acquired by design drawing. But, design drawing can be not exist because of rack of facility management and national policy that centered to construction. And also, existing design drawing have a lot of differences in comparison with another existing design drawing cause of alignment improvement. In this case, for the precise analysis of alignment, 3-dimensional location information on the road centerline and acquisition of location information which related geometric structure are must to be preceded. In this study, therefore, it provide alignment factors which needed to alignment improvement and road safety analysis by acquisition of road space information and extraction of road centerline data using LiDAR data.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.1-6
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• 2021

In the modern society, traffic problems are occurring as vehicle ownership increases. In particular, the incidence of highway traffic accidents is low, but the fatality rate is high. Therefore, a technology for detecting an abnormality in a vehicle is being studied. Among them, there is a vehicle anomaly detection technology using deep learning. This detects vehicle abnormalities such as a stopped vehicle due to an accident or engine failure. However, if an abnormality occurs on the road, it is possible to quickly respond to the driver's location. In this study, we propose a deep learning-based vehicle anomaly detection using road CCTV data. The proposed method preprocesses the road CCTV data. The pre-processing uses the background extraction algorithm MOG2 to separate the background and the foreground. The foreground refers to a vehicle with displacement, and a vehicle with an abnormality on the road is judged as a background because there is no displacement. The image that the background is extracted detects an object using YOLOv4. It is determined that the vehicle is abnormal.

• Spatial Information Research
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• v.11 no.1
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• pp.33-40
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• 2003

For effective management of information about establishment and repair of road and road facilities, we built GPS-Van mapping system that CCD Cameras, GPS receivers and INS are integrated and using it surveyed test area. Suggested a scheme that possible put acquired data into photo database systematically. Prototype of road facilities management system using the database shows us that extraction of qualitative information and management are possible through relation attribute information. And it raise cognitive faculty of user about objects using field photographs.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.147-159
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• 2002

This paper proposes a method to recognize the noisiness of road images connected with the extraction of lane-related information in order to prevent the usage of erroneous information. The proposed method uses a fuzzy neural network(FNN) with the back-Propagation loaming algorithm. The U decides road images good or bad with respect to visibility of lane marks on road images. Most input parameters to the FNN are extracted from an edge distribution function(EDF), a function of edge histogram constructed by edge phase and norm. The shape of the EDF is deeply correlated to the visibility of lane marks of road image. Experimental results obtained by simulations with real images taken by various lighting and weather conditions show that the proposed method was quite successful, providing decision-making of noisiness with about 99%.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2575-2586
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• 2000

In this paper, we propose an algorithm which can automatically extract the road information in a map image. The proposed method extracts the road image in the complex map image. The extracted image is converted into the skeleton image by thining method. The converted image contains various problems. In order to correct these problems, after the road is classified by the number of Rutovitz-connectivity which represents the characteristic of road, those are respectively corrected according to the load characteristic. In the simulation, the proposed method has obtained good results for the various type of map images.

• KIISE Transactions on Computing Practices
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• v.22 no.9
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• pp.419-425
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• 2016

In navigator systems, keeping map data up-to-date is an important task. Manual update involves a substantial cost and it is difficult to achieve immediate reflection of changes with manual updates. In this paper, we present a method for trajectory-center extraction, which is essential for automatic road map generation with GPS data. Though clustered trajectories are necessary to extract the center road, real trajectories are not clustered. To address this problem, this paper proposes a new method using the maximum overlapping interval and trajectory clustering. Finally, we apply the Virtual Running method to extract the center road from the clustered trajectories. We conducted experiments on real massive taxi GPS data sets collected throughout Gang-Nam-Gu, Sung-Nam city and all parts of Seoul city. Experimental results showed that our method is stable and efficient for extracting the center trajectory of real roads.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4208-4215
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• 2015

Most of the administrative works are executed based on the address. Therefore, spatial information is an essential factor for administrative works. So far, many systems, which apply spatial information to administrative works, have been implemented. However, there is little approach to apply spatial information to road occupation permit works. In this paper, we introduce system implementation plan for applying spatial information to road occupation permit administrative works. System implementation plan includes work analysis, applying scenarios extraction, system function extraction, and datamart construction plans. First, work processes and activities are defined based on the analysis of work handbook. Also, activities are displayed in diagram. Second, scenarios applying spatial information to road occupation permit works are extracted. Third, we derive service functions for system, which realize work processes and applying scenarios. Finally, spatial information datamart construction plan is established. Proposed system implementation plan in this research includes application architecture and part of data architecture. For implementing the system, plan for hardware and software architecture should be studied.