• 한국도로학회논문집
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• 제20권2호
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• pp.127-135
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• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 추계학술대회논문집
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• pp.48-53
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• 2006

Noise mapping is performed in the city of Cheongju which has 626,614 inhabitants on a $153.41km^2$ area. This city has 71,387 buildings and 969,274m roads. Many database sets like information of roads, topography and buildings are required for making the noise map of large area. These database sets are provided by the various departments of the regional administration in Cheongju city. Using the given database sets, 3-dimensional model of topography and buildings are made to consider the multi-reflections and diffractions. A predicted noise level is compared with measured noise level of the road traffic noise. As the tool of management and decision of urban noise policy, noise map is combined into the map of land use to make the conflict noise map. This conflict noise map is useful to assess the present urban noise and to make the better life in complicated urban life.

• 대한기계학회논문집A
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• 제28권3호
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• pp.230-237
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• 2004

Lane Sensing techniques based on vision sensors are regarded promising because they require little infrastructure on the highway except clear lane markers. However, they require more intelligent processing algorithms in vehicles to generate the previewed roadway from the vision images. In this paper, a lane sensing algorithm using vision sensors is developed to improve the sensing robustness. The parallel stereo-camera is utilized to regenerate the 3-dimensional road geometry. The lane geometry models are derived such that their parameters represent the road curvature, lateral offset and heading angle, respectively. The parameters of the lane geometry models are estimated by the Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from the image plane to the global coordinate considers roll and pitch motions of a vehicle so that the mapping error is minimized during acceleration, braking or steering. The proposed sensing system has been built and implemented on a 1/10-scale model car.

• 로봇학회논문지
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• 제16권2호
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• pp.122-129
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• 2021

For the Simultaneous Localization and Mapping (SLAM) problem, a different path results in different SLAM results. Usually, SLAM follows a trail of input data. Active SLAM, which determines where to sense for the next step, can suggest a better path for a better SLAM result during the data acquisition step. In this paper, we will use reinforcement learning to find where to perceive. By assigning entire target area coverage to a goal and uncertainty as a negative reward, the reinforcement learning network finds an optimal path to minimize trajectory uncertainty and maximize map coverage. However, most active SLAM researches are performed in indoor or aerial environments where robots can move in every direction. In the urban environment, vehicles only can move following road structure and traffic rules. Graph structure can efficiently express road environment, considering crossroads and streets as nodes and edges, respectively. In this paper, we propose a novel method to find optimal SLAM path using graph structure and reinforcement learning technique.

• 융합경영연구
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• 제5권1호
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• pp.38-43
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• 2017

Purpose - The paper aims to study competency mapping in the organization and how does HR department focuses to provide a definitive road map to understand, design and implement competency models in the organization. Research Design, Data and Methodology - Descriptive research design has been used in the study. The sample size of the study is 75 consisting of employees working at DMRC, barakhamba road. A structured questionnaire was designed to collect the primary data. SPSS has been used to analyze the responses of the questionnaires. Results- DMRC frequently employs some form of competency mapping to understand how to most effectively employ the competencies of strengths of workers. Conclusion - To conclude, it was found that the company has cost effective system to recruit and select people which is working satisfactorily.

• 한국측량학회지
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• 제36권2호
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• pp.75-84
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• 2018

본 연구의 목적은 MEMS 기반의 INS를 적용한 저가형 MMS를 개발하고, 개발된 MMS를 이용하여 x, y의 평면 거리오차가 0.546m인 정확도를 확보하여 도로시설물의 판독에 활용하고자 함에 있다. MMS 기술은 해외 유수의 측량장비제작 업체를 중심으로 지리정보 구축을 위한 새로운 측량기술로 활발하게 사용되고 있지만 국내에서는 아직 관련 연구가 초기단계에 있다. 또한, MMS 장비개발은 몇몇 연구원 및 업체에서 시도를 하였으나 안정화가 이루어지지 않은 시작품 단계에 불과하다. 이러한 MMS 기술은 빠른 시간 내에 지형 지물 데이터를 취득할 수 있어 정밀지도 제작과 도로시설물 데이터 취득에 활용되고 있다. 따라서 본 연구에서는 MMS 제작에 사용하는 각종 센서(LiDAR, CCD camera, GPS/INS, DMI 등)를 동기화하여 MEMS 기반의 INS를 탑재한 저가형 MMS를 개발하고자 한다.

• 한국정밀공학회지
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• 제21권4호
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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.

• 한국측량학회지
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• 제12권1호
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• pp.89-94
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• 1994

최근 많은 연구가 실시간 지도제작시스템의 개발에 초점이 맞춰지고 있으며, 일반적으로 자동차나 비행기로부터 지형에 관련된 수치형태의 정보를 얻고 있다. 본 연구는 미국 오하이오 주립대학의 지도 제작센터에서 개발한 일명 "GPS-Van"이라고 하는 관측장비를 이용하여 얻어진 수치영상으로부터 도로정보를 자동추출하고 수치자료의 효과적인 저장과 관리를 위한 방법을 제시하는데 목적을 두고 있다. 도로의 경계선 검출은 수치사진측량기법을 적용하므로써 수치영상에서 자동추출할 수 있으며 실시간 3차원위치 결정도 가능했다. 또한 자료저장단계를 레스터자료단계, 객체지향자료단계, 벡터자료단계로 구성되는 3단계 자료 저장방법과 자료관리 측면에서 효과적인 자료압축과 검색을 위해 사지수형자료구조를 제안하였다.구조를 제안하였다.

• 한국산업융합학회 논문집
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• 제24권6_2호
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• pp.753-762
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• 2021

Google provides mapping services using satellite imagery, this is widely used for the study. Since about 20 years ago, research and business using drones have been expanding. Pix4D is widely used to create 3D information models using drones. This study compared the distance error by comparing the result of the road construction site with the DSM data of Google Earth and Pix4 D. Through this, we tried to understand the reliability of the result of distance measurement in Google Earth. A DTM result of 3.08 cm/pixel was obtained as a result of matching with 49666 key points for each image. The length and altitude of Pix4D and Google Earth were measured and compared using the obtained PCD. As a result, the average error of the distance based on the data of Pix4D was measured to be 0.68 m, confirming that the error was relatively small. As a result of measuring the altitude of Google Earth and Pix4D and comparing them, it was confirmed that the maximum error was 83.214m, which was measured using satellite images, but the error was quite large and there was inaccuracy. Through this, it was confirmed that there are difficulties in analyzing and acquiring data at road construction sites using Google Earth, and the result was obtained that point cloud data using drones is necessary.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.333-336
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• 2007

This paper is the environmental impact assessment of at road design in the light of the sense for the real from the virtual reality. For in this papers, This study developed 3D-model and virtual reality contents by suggesting the environmental impact assessment based on GIS in the road design. And, through this process, it's possible to visualize the environmental impact assessment by constructing the 3D-model and simulation. The 3D-model can be a method to show the road effectively by maximizing the road's shape visually after the construction. The main construction which composes polyhedron model that is generated from digital map and aerial photo is built by mapping the real texture, so the Sense for the Real was more heightened. Through this study, it must be made to shorten a long time exhausting period of conference and construct more real road after due scene consideration by specific and various low-cost strategy in the environmental impact assessment afterwards.