• Journal of KIISE:Computing Practices and Letters
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• v.8 no.2
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• pp.155-166
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• 2002

Even the short history of the Web system, the technology related to the Web system has been developed rapidly. Yet, the quality of the Web-based application software has not been improved that much. For this reason, the efficient method to develop the Web-based application software is needed. This paper describes the items necessary to develop the Web-based application software. On the basis of ISO/IEC 12207-Software Life Cycle Processes this paper mainly suggests the analysis and design stage of the Web-based model for developing software. Also, this paper describes the methods to define the process and the entity for applying contents to Web-based application software. With the web-based model suggested in this paper the Web-RoadMap Methodology of KCC Information & Communication, a system provider in Korea, has been applied to the public-domain projects. Through the application, Web-RoadMap Methodology has been proved to be an applicable model for analyzing and designing the systems based on the web environments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.109-118
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• 2019

Road information is one of the most significant geospatial data for applications such as transportation, city planning, map generation, LBS (Location-Based Service), and GIS (Geographic Information System) database updates. Robust technologies to acquire and update accurate road information can contribute significantly to geospatial industries. In this study, we analyze the limitations of ACO (Ant Colony Optimization) road extraction, which is a recently introduced object-based road extraction method using high-resolution satellite images. Object-based ACO road extraction can efficiently extract road areas using both spectral and morphological information. This method, however, is highly dependent on object descriptor information and requires manual designations of descriptors. Moreover, reasonable iteration closing point needs to be specified. In this study, we perform improved ACO road extraction on VHR (Very High Resolution) optical satellite image by proposing an optimization stopping criteria and descriptors that complements the limitations of the existing method. The proposed method revealed 52.51% completeness, 6.12% correctness, and a 51.53% quality improvement over the existing algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.173-184
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• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.117-127
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• 2017

PURPOSES : The objective of this research is establishing system components and optimizing operational procedures in order to systematically manage road cave-ins in urban areas. METHODS : Based on the literature review and alternative comparison, optimization methods is suggested. RESULTS : Throughout the study, location referencing system, database structure, and operation strategy(procedure) were clarified, and the optimization methods for each item were suggested. CONCLUSIONS : Road cave-in management should be focused on user safety rather than focusing on economic aspects. The occurrence of road cave-in should be addressed thoroughly by road management system(location referencing system, database structure, and operation strategy(procedure), and the optimization methods), since they are closely related to road users' safety.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.525-527
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• 2003

Recently, the spatial resolution of earth observation satellites is significantly increased to a few meters. Such high spatial resolution images definitely will provide lots of information for detail-thirsty remote sensing users. However, it is more difficult to develop automated image algorithms for automated image feature extraction and pattern recognition. In this study, we propose a two-stage procedure to extract road information from high resolution satellite images. At first stage, a watershed segmentation technique is developed to classify the image into various regions. Then, a knowledge is built for road and used to extract the road regions. In this study, we use panchromatic and multi-spectral images of the IKONOS satellite as test dataset. The experiment result shows that the proposed technique can generate suitable and meaningful road objects from high spatial resolution satellite images. Apparently, misclassified regions such as parking lots are recognized as road needed further refinement in future research.

• Safety and Health at Work
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• v.7 no.1
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• pp.38-42
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• 2016

Background: Truck driving is known as one of the occupations with the highest accident rate. This study investigates the characteristics of traffic collisions according to road types (expressway and rural road). Methods: Classifying 267 accidents into expressway and rural road, we analyzed them based on driver characteristics (age, working experience, size of employment), time characteristics (day of accident, time, weather), and accident characteristics (accident causes, accident locations, accident types, driving conditions). Results: When we compared the accidents by road conditions, no differences were found between the driver characteristics. However, from the accident characteristics, the injured person distributions were different by the road conditions. In particular, driving while drowsy is shown to be highly related with the accident characteristics. Conclusion: This study can be used as a guideline and a base line to develop a plan of action to prevent traffic accidents. It can also help to prepare formal regulations about a truck driver's vehicle maintenance and driving attitude for a precaution on road accidents.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.5
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• pp.575-582
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• 2019

Advanced driving assist system can support safety of driver and passengers which may require vehicle dynamics states as well as road geometry. It is essential to have in real-time estimation of related variables and parameters. Among the road geometry parameters, road slope angle which can not be measured is essential parameter in pose estimation, adaptive cruise control and others on sag road. In this paper, Kalman filter based method for the estimation of the vehicle dynamics and road slope angle using a nonlinear vehicle model is proposed. It uses a combination of Kalman filter as Cascade Extended Kalman Filter. CEKF uses measured vehicle states such as yaw rate, longitudinal/lateral acceleration and velocity. Unknown vehicle parameters such as center of gravity and inertia are obtained by 2 D.O.F lateral model and experimentally. Simulation and Experimental tests conducted with commercialized vehicle dynamics model and real-car.

• Wind and Structures
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• v.20 no.2
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• pp.191-211
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• 2015

Several frameworks for the dynamic analysis of wind-vehicle-bridge systems were presented in the past decade to study the safety or ride comfort of road vehicles as they pass through bridges under crosswinds. The wind loads on the vehicles were generally formed based on the aerodynamic parameters of the stationary vehicles on the ground, and the wind loads for the pure bridge decks without the effects of road vehicles. And very few studies were carried out to explore the dynamic effects of the aerodynamic interference between road vehicles and bridge decks, particularly for the moving road vehicles. In this study, the aerodynamic parameters for both the moving road vehicle and the deck considering the mutually-affected aerodynamic effects are formulized firstly. And the corresponding wind loads on the road vehicle-bridge system are obtained. Then a refined analytical framework of the WVB system incorporating the resultant wind loads, a driver model, and the road roughness in plane to fully consider the lateral motion of the road vehicle under crosswinds is proposed. It is shown that obvious lateral and yaw motions of the road vehicle occur. For the selected single road vehicle passing a long span bridge, slight effects are caused by the aerodynamic interference between the moving vehicle and deck on the dynamic responses of the system.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.234-237
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• 2007

Road networks are important geospatial databases for various GIS (Geographic Information System) applications. Road digital maps may contain geometric spatial errors due to human and scanning errors, but manually updating roads information is time consuming. In this paper, we developed a new road features updating methodology using from multispectral high-resolution satellite image and pre-existing vector map. The approach is based on initial seed point generation using line segment matching and a modified double snake algorithm. Firstly, we conducted line segment matching between the road vector data and the edges of image obtained by Canny operator. Then, the translated road data was used to initialize the seed points of the double snake model in order to refine the updating of road features. The double snake algorithm is composed of two open snake models which are evolving jointly to keep a parallel between them. In the proposed algorithm, a new energy term was added which behaved as a constraint. It forced the snake nodes not to be out of potential road pixels in multispectral image. The experiment was accomplished using a QuickBird pan-sharpened multispectral image and 1:5,000 digital road maps of Daejeon. We showed the feasibility of the approach by presenting results in this urban area.