• The Journal of the Acoustical Society of Korea
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• v.1 no.1
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• pp.6-18
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• 1982

Korean brahman bells toll magnificent sound that would be a great vehicle which brings all beings to the sutras without lecturing mat and can lead them to the Land of Purity -Nirvana. The rating processes and their results of sound quality of the most beautiful Korean Brahman Bells of Sangwonsa, Bongduksa and Boshinkak have been presented in detail. This evaluation scheme is also a very effective measure in determining the beauty of sound not only of bells but also of any music.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.279-282
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• 2002

This Paper of use vision system, there is no DGPS's information, DGPS data value receives real time exactly without being influenced in surroundings environment because using vision system that is used in self-regulation traveling by car system. Therefore, conversion and DGPS of received in camera coordinate changing coordinate error correct and wish to grasp correctly position of vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.142-151
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• 2018

In the era of the 4th Industrial Revolution, research and development on autonomous vehicles have been actively conducted all over the world. Under these international trends, the Ministry of Land, Infrastructure and Transport is actively promoting the development of autonomous vehicles aiming at commercialization of autonomous vehicles at level 3 or higher by 2020. In the level 3 autonomous vehicle, it is essential to transfer control between the driver and the vehicle according to driving situations. Prior to the full-fledged autonomous vehicle age, this study developed a representative scenario for the safety evaluation on take-over on expressways. To accomplish this, we developed a highway driving scenario first, and then developed six control transition scenarios based on 2014 highway traffic accident data and take-over data. The variables to be considered in the developed scenarios are divided into drivers, vehicles, and environmental factors. A total of 36 variables are selected.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.6-13
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• 2022

The Ministry of Land, Infrastructure and Transport (MoLIT) and the Korean Automobile Testing and Research Institute (KATRI) are supporting the development of Lv.3 automated vehicle (hereinafter, AV) technology by constructing an automated driving pilot city (as known as K-City) equipped with total 5 evaluation environments (urban, motorway, suburban, community road, and autonomous parking facility) which is a test bed exclusively for AV (2017~2018). An upgrade project is in a progress to materialize harsh environments such as bad weather (rain, fog, etc.) and reproduction of communication jamming (GPS blocking, etc.) with the purpose of supporting the development of Lv.4 connected & automated vehicle (hereinafter, CAV) technology (2019~2022). We intend to proactively establish a national level standard for CAV test-bed and test road requirements, test method, etc. for establishment of a road map for the construction of the test bed which is being promoted step by step and analyze and, when required, benchmark the case of China that has announced and is utilizing it. Through this, we plan to define standardized requirements (evaluation facility, evaluation system, etc.) on the test bed for the development of Lv.4/4+ CAV technology and utilize the same for the design and construction of a test bed, establishment of a road map for the construction of a real car-based test environment related to the support for autonomous driving service substantiation, etc. through provision of an evaluation environment utilizing K-City, and the establishment of a K-City upgrade strategies, etc.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.79-88
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• 2009

The objective of this study is to develop the new vehicle classification algorithm and minimize classification errors. The existing vehicle classification algorithm collects data from loop and piezo sensors according to the specification("Vehicle classification guide for traffic volume survey" 2006) given by the Ministry of Land, Transport and Maritime Affairs. The new vehicle classification system collects the vehicle length, distance between axles, axle type, wheel-base and tire type to minimize classification error. The main difference of new system is the "Wandering" sensor which is capable of measuring the wheel-base and tire type(single or dual). The wandering sensor obtains the wheel-base and tire type by detecting both left and right tire imprint. Verification tests were completed with the total traffic volume of 762,420 vehicles in a month for the new vehicle classification algorithm. Among them, 47 vehicles(0.006%) were not classified within 12 vehicle types. This results proves very high level of classification accuracy for the new system. Using the new vehicle classification algorithm will improve the accuracy and it can be broadly applicable to the road planning, design, and management. It can also upgrade the level of traffic research for the road and transportation infrastructure.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.314-320
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• 2016

Inertial navigation system (INS) has used aided systems and sensors to compensate navigation error. Global navigation satellite system (GNSS), velocity measurement sensor (VMS), and radar are commonly used to aid INS. Land navigation system (LNS) also mainly uses VMS when GNSS cannot be used such as at tunnel or on jammed scenario. A straight drive is required when VMS-aided navigation is used, because there is only speed of straight direction whereas no crossways and vertical directions. In local environment, even an expressway has lack of straight drive which is constraint of VMS-aided navigation algorithm. This paper proposes an enhanced VMS-aided navigation algorithm for LNS with indirect drive by restricting filter update condition. Also, there is a result of vehicle test to prove performance of the proposed algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.9
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• pp.731-738
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• 2014

The mission of UAV has been expanded from a land to an ocean based on an enhancement of its technologies. Korea Aerospace Research Institute (KARI) also tries to expand the mission of tilt rotor UAV to an ocean, in which the shipboard landing of UAV is required. However the environment of an oceanic operation is severer than that of land due to salty, fogy, and windy condition. The landing point for automatic landing is not fixed due to movement of shipboard in roll, pitch, and heave. It makes the oceanic operation and landing of UAV difficult. In order to conduct an oceanic operation of tilt rotor UAV, this paper presents that the sea wave modeling according to the sea state is conducted and the shipboard landing of tilt rotor UAV under the sea wave is tested and evaluated through the flight simulator for UAV.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.3
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• pp.43-49
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• 2008

The objective of this research was to test a hypothesis that sprawl increases congestion, and so the estimated evacuation time become longer. For this, sprawl was thought to be poor accessibility so that vehicle miles of travel become longer. This research shows that the daily vehicle miles per lane mile that are thought to be an accessibility index had a strong and statistically significant relationship to the estimated evacuation time, while urban population density has no statistically significant relationship to the evacuation time. The result of this research recommends that we should consider sustainable land use patterns that decrease traffic demand by providing good accessibility.

• Journal of Ocean Engineering and Technology
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• v.36 no.3
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• pp.181-193
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• 2022

This study presents a mission management technique that is a key component of underwater docking system used to expand the operating range of autonomous underwater vehicle (AUV). We analyzed the docking scenario and AUV operating environment, defining the feasible initial area (FIA) level, event level, and global path (GP) command to improve the rate of docking success and AUV safety. Non-holonomic constraints, mounted sensor characteristic, AUV and mission state, and AUV behavior were considered. Using AUV and docking station, we conducted experiments on land and at sea. The first test was conducted on land to prevent loss and damage of the AUV and verify stability and interconnection with other algorithms; it performed well in normal and abnormal situations. Subsequently, we attempted to dock under the sea and verified its performance; it also worked well in a sea environment. In this study, we presented the mission management technique and showed its performance. We demonstrated AUV docking with this algorithm and verified that the rate of docking success was higher compared to those obtained in other studies.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.1-14
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• 2017

A land cover map provides basic information to help understand the current state of a region, but its utilization in the ecological research field has deteriorated due to limited temporal and spatial resolutions. The purpose of this study was to investigate the possibility of using a land cover map with data based on high resolution images acquired by UAV. Using the UAV, 10.5 cm orthoimages were obtained from the $2.5km^2$ study area, and land cover maps were obtained from object-based and pixel-based classification for comparison and analysis. From accuracy verification, classification accuracy was shown to be high, with a Kappa of 0.77 for the pixel-based classification and a Kappa of 0.82 for the object-based classification. The overall area ratios were similar, and good classification results were found in grasslands and wetlands. The optimal image segmentation weights for object-based classification were Scale=150, Shape=0.5, Compactness=0.5, and Color=1. Scale was the most influential factor in the weight selection process. Compared with the pixel-based classification, the object-based classification provides results that are easy to read because there is a clear boundary between objects. Compared with the land cover map from the Ministry of Environment (subdivision), it was effective for natural areas (forests, grasslands, wetlands, etc.) but not developed areas (roads, buildings, etc.). The application of an object-based classification method for land cover using UAV images can contribute to the field of ecological research with its advantages of rapidly updated data, good accuracy, and economical efficiency.