• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.112-121
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• 2021

Unlike a typical small-sized robot navigating in a free space, an autonomous vehicle has to travel in a designated road which has lanes to follow and traffic rules to obey. High-Definition (HD) maps, which include road markings, traffic signs, and traffic lights with high location accuracy, can help an autonomous vehicle avoid the need to detect such challenging road surroundings. With space constraints and a pre-built HD map, a new type of path planning algorithm can be conceived as a substitute for conventional grid-based path planning algorithms, which require substantial planning time to cover large-scale free space. In this paper, we propose an obstacle-avoiding, cost-based planning algorithm in a continuous space that aims to pursue a globally-planned path with the help of HD map information. Experimentally, the proposed algorithm is shown to outperform other state-of-the-art path planning algorithms in terms of computation complexity in a typical urban road setting, thereby achieving real-time performance and safe avoidance of obstacles.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.88-94
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• 2004

Recently, vehicle simulators are widely used to evaluate driver's responses and driver assistance systems. It needs much effort to construct the virtual driving environment for a vehicle simulator. In this study, it is described how to make effectively the roads and the driving environment for a vehicle simulator. The GIS (Geographic Information System) is used to construct the roads and the environment effectively. Because the GIS is the integrated system of geographical data, it contains useful data to make virtual driving environment. First, the outline and centerline of roads is abstracted from the GIS. From the road outline, the road width is calculated. Using the centerline, the grid model of roads is constructed. The final graphic model of roads is constructed by mapping road image to the grid model according to the number of lanes and the kind of surface. Data of buildings from the GIS are abstracted. Each shape and height of buildings is determined according to kind of buildings, the final graphic model of buildings is constructed. Then, the graphic model of roadside tree is also constructed. Finally, the driving environment for driving simulator is constructed by converting the three graphic models with the graphic format of Direct-X and by joining the three graphic models.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.106-115
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• 2007

농촌진흥청에서 제공하고 있는 수치토양도는 수문 수자원 분야에서 SCS-CN법을 이용한 유효우량 및 유출곡선 산정에 가장 많이 활용되고 있다. 토양조사 국책사업 결과 전산화된 토양도 및 토양검정 데이터베이스에 기초한 토양정보 웹 시스템은 전국의 토양 전자지도와 토양 통계 자료를 주제별로 검색하거나 필지별 토양분석 성적에 따른 토양관리처방서를 조회하는데 사용되는 농업분야 이외의 사용자 그룹을 위해 필요한 정보를 제공하도록 활용 및 유통 요구도가 높아지고 있다. 수치토양도가 수문학적 토양유형 정보를 포함하도록 제공하는 것이 먼저 필요할 것으로 생각되고 다음으로는 수문 수자원 분야 활용 측면에서 수치토양도가 제공하는 속성, 축척, 제공형태, 좌표체계, 서비스 방식 등에 대하여 활용정책을 마련하여 이에 따라 자료가 유통될 수 있도록 하여야 할 것이다. 앞으로 활용이 가능하게 될 수치세부정밀토양도와 토양유형을 이용하여 충북 괴산군 소수면의 소유역에 대해 SCS 삼각법에 따른 단위도 작성, 유효우량 산출 및 유출곡선을 작성한 결과 농업과학기술원의 정 등(2006)이 분류한 토양유형을 이용한 결과 정 등(1995)에 따른 토양유형을 이용한 결과에 비해 CN값과 유효우량이 더 높게 나타났고 삼각단위도로부터 유도한 정점의 유출량과 시간별 유량 관측값에 더 가까운 것으로 나타났다.

• TTA Journal
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• s.173
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• pp.6-11
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• 2017

자율주행차는 센서와 인공지능으로 차량의 위치와 주변 상황을 인지하고 주행 경로를 계획하여, 자동차 스스로 교통법규에 따라 주행하는 차량이다. 이는 4차 산업혁명의 주역으로 2020년 상용화 될 전망이다. 2020년 자율주행차 세계 시장규모는 189억 달러로 예측되고 이를 위해 각국의 자동차사, ICT 업체들이 시장 선점을 위해 치열하게 경쟁하고 있다. 자율주행 상용화를 위한 기술적 해결 이슈로는 센서, 인공지능, 빅데이터 분석, 기능안전, 정밀지도, 신뢰성 높은 차량통신, 차량 SW 플랫폼, 차량 사이버 보안 등이 있다. 이러한 기술적 이슈가 해결되어야 2020년 자율주행차 시대를 맞이하고 새로운 시장이 열리게 될 것이다. 자율주행차 상용화를 위해서 차량, ICT 기술, 도로 인프라 등 산업 융합 및 기업체 간 협업이 기술개발과 사업화를 성공시키는 중요한 열쇠가 될 수 있다는 것을 강조하며, 이번 특집호를 통해 자율주행 실현을 위한 핵심기술 및 표준화에 대한 전체적인 흐름과 방향을 파악하는데 도움이 될 것으로 기대한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.169-175
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• 2022

Korea's construction industry has a shortage and aging of construction manpower, low productivity compared to other industries, and a high rate of industrial accidents. The Ministry of Land, Infrastructure and Transport is preparing for the 4th industrial revolution and is expanding investment in construction automation and innovative growth engines to improve productivity in the construction industry. In order for new technologies to be utilized in the road construction field, the accuracy of the technologies and the applicability of each type of work must be evaluated. In this study, the accuracy of the mobile mapping system was tried to verify based on the relevant work regulations, and to suggest the applicability of the mobile mapping system to high-speed driving tracks through data acquisition and analysis on road construction sites. The accuracy of the equipment used in the study was verified in accordance with the relevant work regulations, and the possibility of applying the mobile mapping system used for the study to road construction surveying was presented with a maximum error of less than 10cm in the horizontal and vertical directions. In addition, the possibility of utilizing the road construction survey using the mobile mapping system was presented through comparison with the existing method for data acquisition time for construction surveying, production of construction status survey results, and calculation of heatmap and earthworks. In the future, the use of construction status surveying of the mobile mapping system will greatly improve the efficiency of construction work.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.663-671
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• 2020

Recently, there have been many natural disasters in Korea, not only in forest areas but also in urban areas, and the national requirements for them are increasing. In particular, there is no pre-disaster information system that can systematically manage the collapse of the slope of the national highway. In this study, big data analysis was conducted on the factors causing slope collapse based on the detailed investigation report on the slope collapse of national roads in Gangwon-do and Gyeongsang-do areas managed by the Cut Slope Management System (CSMS) and the basic survey of slope failures. Based on the analysis results, a slope collapse risk prediction model was established through Adaboost, a classification-based machine learning model, reflecting the collapse slope location and weather information. It also developed a visualization map for the risk of slope collapse, which is a visualization program, to show that it can be used for preemptive disaster prevention measures by identifying the risk of slope due to changes in weather conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.75-84
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• 2018

The purpose of this study is that the low-cost mobile mapping system using INS (Inertial Navigation System) based on MEMS (Micro Electro Mechanical System) could decipher the interpretation of road facility with the accuracy of x, y 0.546m plane error. Even though the MMS (Mobile Mapping System) technology as a new measurement technology has been used vividly to set up geographic information by some world leading surveying equipment manufacturers, the domestic technology is still in its beginning stage. Several domestic institutes and companies tried to catch up the leading technology but they just produced prototypes which needs more stabilization. Through this thesis, we developed low-cost mobile mapping system installed with INS based on MEMS after time synchronizing sensors for MMS such as LiDAR (Light Detection And Ranging), CCD (Charge Coupled Device), GPS/INS (Global Positioning System / Inertial Navigation System) and DMI (Distance Measurement Instrument).

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.71-77
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• 2010

Cut Slope Management System(CSMS) is a systematic maintenance and management system designed to prevent the collapse of cut slopes located along national roads. In order to implement safe road operation system, KICT has started the inventory of cut slopes and developed a cut slope database since 2006. Cut slope database management system using GIS technology and navigation system was developed as a Information Technology application. Through the Cut Slope Navigation System(SLOPE-Navi.), the previously developed database was checked and verified. The converted cut slope inventory data and field investigation data of 28,707 cut slopes were loaded on the navigation map. We consider that the Cut Slope Navigation Management System can be useful as in-situ system, which can be systematic and effective DB management and operation to prevent cut slope collapses and establish a remedial countermeasure as mitigation concerning disasters.

• Journal of Astronomy and Space Sciences
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• v.19 no.4
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• pp.351-366
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• 2002

In this study, we developed low cost INS and (D)GPS integration for continuous attitude and position and utilized it for the determination of exterior orientation parameters of image sensors which are equipped in 4S-Van. During initial alignment process, the heading information was extracted from twin GPS and fine alignment with Kalman filter was performed for the determination of roll and pitch. Simulation and van test were performed for the performance analysis. Based on simulation result, roll and pitch error is around 0.01-0.03 degrees and yaw error around 0.1 degrees. Based on van test, position error in linear road is around 10 cm and curve around 1 m. Using direct georeferencing method, the image sensor's orientation and position information can be acquired directly from (D)GPS/INS integration. 4S-Van achieved 3D spatial data using (D)GPS/INS and image data can be applied to the spatial data integration and application such as contemporary digital map update, road facility management and Video GIS DB.