• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.334-342
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• 2021

In Korea, the training is performed through independent environments without interoperability among L-V-C systems. In the L system, training for large units is limited due to civil complaints at the training grounds and road restrictions. The V system is insufficient in training related to tactical training, and the C system lacks practicality due to a lack of combat friction elements. To achieve synchronicity and integration training between upper and lower units, it is necessary to establish a system to ensure integrated training for each unit by interoperating the currently operating L, V, and C systems. The interoperability between the C-C system supports Korea-US Combined Exercise. On the other hand, the actual development of the training system through the interoperability of L, V, and C has not been made. Although efforts are being made to establish the L, V, and C system centering on the Army, the joint composite battlefield and LVC integrated architecture technology are not yet secured. Therefore, this paper proposes a new plan for the future training system by designing and implementing the LVC integrated architecture technology, which is the core technology that can build the L-V-C interoperability training system. In conclusion, a division-level L-V-C interoperability training system can be established in the future by securing the LVC integrated architecture technology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.14-34
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• 2023

The purpose of this study was to calculate the appropriate yellow-signal time for intersections, to find out the relationship between the approach speed and intersection width when calculating the time, and to secure safety by minimizing conflicts and dilemma sections in intersections that change according to the signal operation. For this purpose, 6,824 data points from 5 intersections were collected and analyzed. The main results of the study are as follows. First, the approach speed of individual vehicles in different lanes was analyzed, and the width of an intersection was defined by considering the conflict in each direction. Second, we developed a multiple regression model based on the approach speed and conflict points, which compensated for the problems of an existing formula. Third, a standard table is presented for applying the appropriate yellow-signal time according to the approach speed and intersection width based on a development formula. A method is also presented to determine the safety of the length of the dilemma according to the change in the yellow-light time by presenting a calculation table that can cross-analyze the yellow-signal time and a dilemma section using the relationship.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.189-200
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• 2022

Ground subsidence on urban roads is a social issue that can lead to human and property damages. Therefore, it is crucial to detect underground cavities in advance and repair them. Underground cavity detection is mainly performed using ground penetrating radar (GPR) surveys. This process is time-consuming, as a massive amount of GPR data needs to be interpreted, and the results vary depending on the skills and subjectivity of experts. To address these problems, researchers have studied automation and quantification techniques for GPR data interpretation, and recent studies have focused on deep learning-based interpretation techniques. In this study, we described a hyperbolic event detection process based on deep learning for GPR data interpretation. To demonstrate this process, we implemented a series of algorithms introduced in the preexisting research step by step. First, a deep learning-based YOLOv3 object detection model was applied to automatically detect hyperbolic signals. Subsequently, only hyperbolic signals were extracted using the column-connection clustering (C3) algorithm. Finally, the horizontal locations of the underground cavities were determined using regression analysis. The hyperbolic event detection using the YOLOv3 object detection technique achieved 84% precision and a recall score of 92% based on AP50. The predicted horizontal locations of the four underground cavities were approximately 0.12 ~ 0.36 m away from their actual locations. Thus, we confirmed that the existing deep learning-based interpretation technique is reliable with regard to detecting the hyperbolic patterns indicating underground cavities.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.4
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• pp.285-303
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• 2023

Interest in building underground spaces is increasing for the creation of downtown infrastructure and efficient space utilization. A representative method of utilizing underground space is a tunnel, and in addition to road tunnels, the construction of utility tunnels such as power conduits and utility conduits is gradually increasing. The current basic tunnel construction method can be divided into NATM (New Austrian Tunnelling Method) and TBM (Tunnel Boring Machine). The NATM is a reliable method, but it is accompanied by vibration and noise due to blasting. In the case of the TBM excavation method, there are disadvantages in terms of construction period and construction cost, but it is possible to improve economic feasibility by introducing appropriate complementary methods. In this study, a blasting method was develop using the NATM after TBM pre-excavation using the protective shield method. This is a method that compensates for the disadvantages of each tunnel construction method, and is expected to reduce construction costs, blasting vibration, and noise. In order to review the performance of the developed method, an experiment was conducted to evaluate the performance of explosion-proof tube to which a protective shield scale model was applied, and the impact of blasting vibration of the protective shield method was analyzed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.477-483
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• 2010

The existing mass transport system, with its limited capacity and the saturated road networks, has given cause for a new means of transport to be developed, and strong demands for such new means of transport are observed more than ever. However, the traffic authority is seeking a new transport system that focuses more on LRT(Light Rail Transit), a downsized version of the existing urban railroad, rather than one that is appropriate to solve the traffic problems. Moreover, local governments are experiencing difficulties in planning their own mass transportation(bus or urban railroad) as they have no specified criteria for selecting a mass transport system. Accordingly, there has been an increasingly loud voice that calls for criteria to determine which mass transport system befits each transportation corridor. This paper develops a mass-transport demand forecasting model based on the GIS Buffering analysis of each transportation corridor in the city, sets up the capacity for each mass transport system and presents the criteria for selecting an optimal mass transport system for each transportation corridor. It also presents a methodology that identifies necessary and sufficient conditions for selection and evaluation, since it is most important to select the optimal mass-transport system that can meet the demand by each mass-transportation corridor.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.234-234
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• 2022

도로에서의 우수를 원활하게 처리하기 위해서 빗물받이 및 연결관 등의 노면 배수시설이 설치되고 있으며, 노면 배수는 측구부를 통해 흘러 빗물받이 유입부로 차집되고 연결관을 통해 하수관거로 배수된다. 그러나 최근 국내 기상패턴의 변화로 국지성 집중호우와 같이 시간당 강우량 증가로 도로부와 저지대에서 배수시설의 배수불량에 따른 도심지 내수침수 피해가 발생하고 있다. 이에 정부에서는 다양한 우수관거 개선사업, 빗물펌프장, 지하저류조와 같은 방재시설을 설치하고 있으나 우수유출저감시설은 대규모 예산이 소요되고 실제 침수지역에 피해 저감효과에 대한 효용성 문제에 대한 제기뿐만 아니라 과밀화된 도심지에서는 지하공간 활용에 한계가 있는 실정이므로 도심지의 다양한 공간을 활용한 도시 배수 및 저류시설에 대한 연구가 필요하다. 따라서 본 연구에서는 유휴 공간인 도로 측구부 공간을 활용하여 도로 노면수를 저류 및 지체할 수 있는 노면수 측구 저류시설의 개념을 제시하고 측구저류조의 활용성을 판단하기 위하여 빗물받이 유입구, 빗물받이, 측구 저류조 및 빗물받이와 측구저류조 연결부에서의 노면수 유입, 유출 및 저류 등의 다양한 흐름 변화를 확인하기 위하여 Fluent 모형의 적용성을 분석하였다. 수치모의 전체 형상은 50x50cm 크기의 빗물받이를 기준으로 양쪽에 2m 길이의 측구 저류조를 원형관으로 연결하여 1/5 축소모형으로 구성하고 격자는 빗물받이 유입부, 빗물받이 및 측구 저류조 내부의 복잡한 3차원 흐름을 모의하기 위해 사면체와 육면체로 조밀하게 생성하였다. 다상유동해석을 위해 VOF(Volume of Fluid)방법을 적용하였고, 수치해석 방법으로는 비정상류, 난류 모형으로는 SST k-ω모형을 적용하였다. 수치모의 조건으로는 설계빈도별(5~30년) 우수유출량을 산정하여 유입 유량별 기존 빗물받이 유입부에서의 유입흐름, 빗물받이 내부에서의 와 발생흐름, 측구 저류조 및 연결관에서의 흐름을 구현하여 분석하였다. 수치모의 결과 빗물받이 유입부에서 연결관을 통한 측구 저류조로 유입되는 유입흐름과 빗물받이 하단부의 배수관을 통해 유출되는 흐름을 정상적으로 구현하였으며, 빗물받이 유입부 및 측구 저류조 연결관에서의 유속변화도 확인할 수 있었다. 또한 빗물받이와 측구 저류조에서 다양한 흐름을 구현하기 위한 Flunet 모형의 적용성을 검토하였으며, 향후 수리실험을 통하여 실제 흐름과의 매개변수 최적화 및 다양한 도로 조건의 변화를 고려한 수치모의 분석을 통하여 지속적인 모형의 검증이 가능할 것으로 판단된다.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.363-370
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• 2023

Object detection technology that accurately recognizes the road and surrounding conditions is a key technology in the field of autonomous driving. In the field of autonomous driving, object detection technology requires real-time performance as well as accuracy of inference services. Task offloading technology should be utilized to apply object detection technology for accuracy and real-time on resource-constrained devices rather than high-performance machines. In this paper, experiments such as performance comparison of task offloading, performance comparison according to input image resolution, and performance comparison according to camera object resolution were conducted and the results were analyzed in relation to the application of task offloading for real-time object detection of autonomous driving in resource-constrained devices. In this experiment, the low-resolution image could derive performance improvement through the application of the task offloading structure, which met the real-time requirements of autonomous driving. The high-resolution image did not meet the real-time requirements for autonomous driving due to the increase in communication time, although there was an improvement in performance. Through these experiments, it was confirmed that object recognition in autonomous driving affects various conditions such as input images and communication environments along with the object recognition model used.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.130-144
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• 2023

Recently, various positioning technologies are being researched based on signal-based positioning and image-based positioning to obtain accurate indoor location information. Among these, various studies are being conducted on image positioning technology that determines the location of a mobile terminal using images acquired through cameras and sensor data collected as needed. For video-based positioning, a method of determining indoor location is used by matching mobile terminal photos with virtual landmark images, and for this purpose, it is necessary to build indoor spatial information about various landmarks such as billboards, vending machines, and ATM machines. In order to construct indoor spatial information on various landmarks, a panoramic image in the form of a road view and accurate 3D survey results were obtained through c 13 buildings of the Electronics and Telecommunications Research Institute(ETRI). When comparing the 3D total station final result and the terrestrial lidar panoramic image coordinates, the coordinates and distance performance were obtained within about 0.10m, confirming that accurate landmark construction for use in indoor positioning was possible. By utilizing these terrestrial lidar achievements to perform 3D landmark modeling necessary for image positioning, it was possible to more quickly model landmark information that could not be constructed only through 3D modeling using existing as-built drawings.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.77-84
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• 2024

Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.64-72
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• 2009

The method to generate a digital elevation model(DEM) from contour lines causes a problem in which the low relief landform cannot be clearly presented due to the fact that it is significantly influenced by the expression of micro landform elements according to the interval of contours. Thus, this study attempts to develop a landcover burning method that recovers the micro relief landform of the DEM, which applies buffering and map algebra methods by inputting the elevation information to the landcover. In the recovering process of the micro landform, the DEM was recovered using the buffering method and elevation information through the map algebra for the landcover element for the micro landform among the primary DEM generation, making landcover map, and landcover elements. The recovering of the micro landform was applied based on stream landforms. The recovering of landforms using the buffering method was performed for the bar, which is a polygonal element, and wetland according to the properties of concave/convex through generating contours with a uniform interval in which the elevation information applied to the recovered landform. In the case of the linear elements, such as bank, road, waterway, and tributary, the landform can be recovered by using the elevation information through applying a map algebra function. Because the polygonal elements, such as stream channel, river terrace, and artificial objects (farmlands) are determined as a flat property, these are recovered by inputting constant elevation values. The results of this study were compared and analyzed for the degree of landform expression between the original DEM and the recovered DEM. In the results of the analysis, the DEM produced by using the conventional method showed few expressions in micro landform elements. The method developed in this study well described wetland, bar, landform around rivers, farmland, bank, river terrace, and artificial objects. It can be expected that the results of this study contribute to the classification and analysis of micro landforms, plain and the ecology and environment study that requires the recovering of micro landforms around streams and rivers.