• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.519-522
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• 2004

The purpose of this research is to design a road using digital photogrammatry method to generate DEM(digital elevation model) and digital ortho image based on GSIS which was applied to the road simulation. The example study area was the suburbs of Jeju city. To this study, 1/5,000 digital map and GSIS technique were used for optimum road design of the island based on Arc View software. Using this software we can Set an overlay map by combination of hill shade map, slope map, aspect map, and building buffer map. Based on this overlap map, we designed the best road line and along this line we performed three dimensional road simulation using Microstation CAD and Inroads road design programs. From the results, we found that the DEM and digital ortho image acquired from stereoairphoto using digital photogrammatry was satisfied for choosing the best roadline and the developed three dimensional road simulation technique using GSIS technique was very useful to estimate the reasonable road design before the real road construction works.

• Journal of Environmental Science International
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• v.13 no.6
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• pp.489-495
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• 2004

The purpose of this research is to apply GIS(Geographic Information System) for the road simulation and find some benefits analysis for the design processes. The northern Jeju island was selected as a case study. The 1/5,000 digital map and GIS technique were used for optimum road design of the island based on Arc View software. Using this software we can get an overlay map by combination of hill shade map, slope map, aspect map, and building buffer map. Based on the overlay map, we designed the optimum road line and performed three dimensional simulation. From the results, we found that the developed three dimensional road simulation technique using GIS technique that was very useful tool to estimate the reasonable road design before the real road construction works.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.6
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• pp.285-299
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• 2018

Recently much attention in building smart factory has been dramatically increased. Despite the growing interest in smart factory, few practical guidelines exist how to successfully build smart factory. The purpose of this study is to postulate and develop a road map for building successful smart factory. To enhance mundane realism, we design the road map through University-Industry research collaboration. Specifically, drawing analysis of University-Industry research collaboration, we design a prototype and detailed road map or building successful smart factory. Moreover, we apply the road map into actual smart factory development. By doing so, we successfully prove the effectiveness of the road map. Therefore, this study provides the valuable guidelines and directions to build a successful smart factory. Ultimately this study is able to help a variety of factories which establish and implement smart factory. Further, we hope that this study will be placed to be an important foundation research on behalf of smart factory building.

• ETRI Journal
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• v.37 no.5
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• pp.1032-1043
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• 2015

ETRI's Co-Pilot project is aimed at the development of an automated vehicle that cooperates with a driver and interacts with other vehicles on the road while obeying traffic rules without collisions. This paper presents a core block within the Co-Pilot system; the block is named "Co-Pilot agent" and consists of several main modules, such as road map generation, decision-making, and trajectory generation. The road map generation builds road map data to provide enhanced and detailed map data. The decision-making, designed to serve situation assessment and behavior planning, evaluates a collision risk of traffic situations and determines maneuvers to follow a global path as well as to avoid collisions. The trajectory generation generates a trajectory to achieve the given maneuver by the decision-making module. The system is implemented in an open-source robot operating system to provide a reusable, hardware-independent software platform; it is then tested on a closed road with other vehicles in several scenarios similar to real road environments to verify that it works properly for cooperative driving with a driver and automated driving.

• Journal of Environmental Science International
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• v.16 no.7
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• pp.823-830
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• 2007

Traffic noise is a kind of noise caused by cars, trains and aircraft. Among them, noise produced by cars is the most important factor in cities. According to the National Institute of Environmental Research(NIER)'s survey, Road traffic noise levels in Susan are the highest of all the cities in Korea. So, appropriate measures for road traffic noise reduction is required. For this purpose, the construction of a noise map in Susan will playa vital role. However, road traffic noise formulas are constructed considering regional characteristics such as each country road's environment and vehicle quality. Therefore, prior to constructing a noise map in Susan, examination processes about each formula constituent status and estimation process are required preferentially. In this research, the basic first stage is to estimate Susan's road traffic noise. First, investigate characteristics of each road traffic noise estimate and using this, a noise map is constructed for road traffic noise in Susan. Then the adaptation of a road traffic noise formula is evaluated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.91-97
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• 2019

In automatic map generalization, the formalization of cartographic principles is important. This study proposes and evaluates the selection method for road network generalization that analyzes existing maps using reverse engineering and formalizes the selection rules for the road network. Existing maps with a 1:5,000 scale and a 1:25,000 scale are compared, and the criteria for selection of the road network data and the relative importance of each network object are determined and analyzed using $T{\ddot{o}}pfer^{\prime}s$ Radical Law as well as the logistic regression model. The selection model derived from the analysis result is applied to the test data, and road network data for the 1:25,000 scale map are generated from the digital topographic map on a 1:5,000 scale. The selected road network is compared with the existing road network data on the 1:25,000 scale for a qualitative and quantitative evaluation. The result indicates that more than 80% of road objects are matched to existing data.

• Journal of Korean Society of societal Security
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• v.2 no.1
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• pp.75-80
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• 2009

The objectives of this research are to develop hazard prediction map S/W for mountain river road. This mountain river road disaster happens by debris flow, landslide, debris accumulation and this cause are locally rainfall and heavy rainfall. System is constructed to GIS base. This research app lied to Kangwondo. We developed protocol to analyze calamity danger in mountain district area and examined propriety system. Furthermore examined the DB required and expression plan for hazard map creation SW construction by mountain rivers road.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.2
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• pp.223-230
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• 2015

Due to the conversion from the existing address system to road name address system, the versatility of the road name address from the public and private sectors is increasing gradually. Therefor, the reliability of the road name address basic map, of the default data is also an urgent need, this means the accuracy of the data. But, road name address basic map is production time due to the use of different map accuracy is to fall, so is also the situation insufficient of utilization. This study Construction of identify each attempt by the road name address basic map and analysis the location accuracy of road name address basic map. As a result, the RMSE of cadastral survey results showed that appears lower than the RMSE of digital map survey results. The judgment can be utilized as the basis for the proposed improvements for the road name address basic map.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1053-1060
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• 2016

As location recognition for autonomous vehicles develops, the need for a precise map for autonomous driving has increased. A precise map must be built based upon accurate position. Recent studies have accelerated research in this area by using various sensors that calculate the accurate position by comparing and recognizing objects around the roads. However, application of such methods is limited because these studies only take objects with significant verticality into consideration. Thus, new research is needed to overcome the limitations: a method that is not constrained by the existence of certain types of surrounding objects shall be proposed. Most roads contain road marking information, such as lanes, direction signs, and pedestrian crossings. Such information on the road surface is a valuable resource for building a precise map. This paper proposes a method of building a precise map by using road marking information.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.47-53
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• 2011

To enable the efficient operation of ITS, it is necessary to collect location data for vehicles on the road. In the case of futuristic transportation systems like ubiquitous transportation and smart highway, a method of data collection that is advanced enough to incorporate road lane recognition is required. To meet this requirement, technology based on radio frequency identification (RFID) has been researched. However, RFID may fail to yield accurate location information during high-speed driving because of the time required for communication between the tag and the reader. Moreover, installing tags across all roads necessarily incurs an enormous cost. One cost-saving alternative currently being researched is to utilize GNSS (global navigation satellite system) carrierbased location information where available. For lane recognition using GNSS, a precise digital map for determining vehicle position by lane is needed in addition to the carrier-based GNSS location data. A "precise digital map" is a map containing the location information of each road lane to enable lane recognition. At present, precise digital maps are being created for lane recognition experiments by measuring the lanes in the test area. However, such work is being carried out through comparison with vehicle driving information, without definitions being established for detailed performance specifications. Therefore, this study analyzes the performance requirements of a precise digital map capable of lane recognition based on the accuracy of GNSS location information and the accuracy of the precise digital map. To analyze the performance of the precise digital map, simulations are carried out. The results show that to have high performance of this system, we need under 0.5m accuracy of the precise digital map.