• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.60-68
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• 2015

Recent proliferation of advanced technologies such as wireless communication, mobile, sensor technology and so on has caused significant changes in a traffic environment. Human beings, in particular drivers, as well as roads and vehicles were advanced on information, intelligence and automation thanks to those advanced technologies; Intelligent Transport Systems (ITS) and autonomous vehicles are the results of changes in a traffic environment. This study proposed considerations when designing a simulation model for future transportation environments, which are difficult to predict the change by means of advanced technologies. First of all, approximability, flexibility and scalability were defined as a macroscopic concept for a simulation model design. For actual similarity, calibration is one of the most important steps in simulation, and Physical layer and MAC layer should be considered for the implementation of the communication characteristics. Interface, such as API, for inserting the additional models of future traffic environments should be considered. A flexible design based on compatibility is more important rather than a massive structure with inherent many functions. Distributed computing with optimized H/W and S/W together is required for experimental scale. The results of this study are expected to be used to the design of future traffic simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.279-282
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• 2017

Kinect depth sensor, a depth camera developed by Microsoft as a natural user interface for game appeared as a very useful tool in computer vision field. In this paper, due to kinect's depth sensor and its high frame rate, we developed a distance measurement system using Kinect camera to test it for unmanned vehicles which need vision systems to perceive the surrounding environment like human do in order to detect objects in their path. Therefore, kinect depth sensor is used to detect objects in its field of view and enhance the distance measurement system from objects to the vision sensor. Detected object is identified in accuracy way to determine if it is a real object or a pixel nose to reduce the processing time by ignoring pixels which are not a part of a real object. Using depth segmentation techniques along with Open CV library for image processing, we can identify present objects within Kinect camera's field of view and measure the distance from them to the sensor. Tests show promising results that this system can be used as well for autonomous vehicles equipped with low-cost range sensor, Kinect camera, for further processing depending on the application type when they reach a certain distance far from detected objects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.224-226
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• 2016

With the technical development and rapid increase of private demand, the new market for unmanned vehicle combined with the characteristics of 'unmanned automation' and 'vehicle' is rapidly growing. Even though the pilot driving is currently allowed in some countries, there is no country that has institutionalized the formal driving of self-driving cars. In case of the existing vehicles, safety incidents are frequently happening due to the frequent malfunction of the rear sensor, blind spot of the rear camera, or drivers' carelessness. Once such minor flaws are complemented, the relevant regulations for the commercialization of self-driving car and small drone could be relieved. Contrary to the ultrasonic and laser sensors used for the existing vehicles, this paper aims to attempt the distance measurement by using the depth sensor. A depth camera calculates the distance data based on the TOF method calculating the time difference by lighting laser or infrared light onto an object or area and then receiving the beam coming back. As this camera can obtain the depth data in the pixel unit of CCD camera, it can be used for collecting depth data in real-time. This paper suggests to solve problems mentioned above by using depth data in real-time and also to design the obstacle avoidance system through distance measurement.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.78-90
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• 2021

In order to construct a precision geoid, it has been diversified into land, sea, aviation, and satellite gravity measurement methods, and measurement technology has developed, making it possible to secure high-resolution, high-precision gravity data. The construction of precision geoids can be fast and conveniently decided through GNSS surveys without separate leveling, and since 2014, the National Geographic Information Institute has been developing a hybrid geoid model to improve the accuracy of height surveying based on GNSS. In this study, the results of the GNSS height measurement were compared and analyzed choosing existing public reference points to verify the GNSS height measurement of public surveys. Experiments are conducted with GNSS height measurements and analyzed precision for public reference points on coastal, border, and mountainous terrain presented as low-precision areas or expected-to-be low-precision in research reports. To verify the GNSS height measurement, the GNSS ellipsoid height of the surrounding integrated datum to be used as a base point for the GNSS height measurement at the public datum. Based on the checked integrated datum, the GNSS ellipsoid of the public datum was calculated, and the elevation was calculated using the KNGeoid18 model and compared with the results of the direct level measurement elevation. The analysis showed that the results of GNSS height measurement at public reference points in the coastal, border, and mountainous areas were satisfied with the accuracy of public level measurement in grades 3 and 4. Through this study, GNSS level measurement can be used more efficiently than existing direct level measurements depending on the height accuracy required by users, and KNGeoids 18 can also be used in various fields such as autonomous vehicles and unmanned aerial vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.62-73
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• 2022

As the competition among the autonomous vehicle (AV, here after) developers are getting fierce, Korean government has been supporting developers by deregulating safety standards and providing financial subsidies. Recently, some OEMs announced their plans to market Lv3 and Lv4 automated driving systems. However, these market changes raised concern among public road management sectors for monitoring road conditions and alleviating hazardous conditions for AVs and human drivers. In this regards, the authors proposed a methodology for monitoring road infrastructure to identify hazardous factors for AVs and categorizing the hazards based on their level of impact. To evaluate the degrees of the harm on AVs, the authors suggested a methodology for managing road hazard factors based on vehicle performance features including vehicle body, sensors, and algorithms. Furthermore, they proposed a method providing AVs and road management authorities with potential risk information on road by delivering them on the monitoring map with node and link structure.

• Journal of IKEEE
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• v.26 no.2
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• pp.141-149
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• 2022

With the development of artificial intelligence and unmanned technologies, the remote surveillance/autonomous driving systems have been actively researched. For an effective performance analysis of the developed remote control system, it is important to record the data of it in real time. In addition, in order to analyze the performance between the control system and the remote system, the recorded data from them should be synchronized with time. In this paper we proposed a novel time synchronization method for the remote control system. The proposed remote control system satisfies the time difference of the recorded data within 1 ms, and we can reduce the time difference by using a CPU shielding and affinity setting. The performance of the proposed method was proved through various network data storage experiments. And the experiments confirmed that the proposed method can be applied to recording devices of unmanned ground vehicles and control vehicles. The proposed method will be used as a method for analyzing network data of UGV-R (Unmanned Ground Vehicle - Reconnaissance).

• Clean Technology
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• v.28 no.3
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• pp.227-231
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• 2022

The demand for high-voltage power devices is rising in various industries, but especially in the transportation industry due to autonomous driving and electric vehicles. IGBT module parts of 3.3 kV or more are used in the power propulsion control device of electric vehicles, and the procurement of these parts for new construction and maintenance is increasing every year. In addition, research to optimize high-voltage IGBT parts is urgently required to overcome their very high technology entry barrier. For the development of high-voltage IGBT devices over 3.3 kV, the resistivity range setting of the wafer and the optimal conditions for major unit processes are important variables. Among the manufacturing processes to secure the optimal junction depth, the optimization of the diffusion process, which is one step of the unit process, was examined. In the diffusion process, the type of gas injected, the injection time, and the injection temperature are the main variables. In this study, the range of wafer resistance (Ω cm) was set for the development of high voltage IGBT devices through unit process simulation. Additionally, the well drive in (WDR) condition optimization of the diffusion process according to temperature was studied. The junction depth was 7.4 to7.5 ㎛ for a ring pattern width of 23.5 to25.87 ㎛, which can be optimized for supporting 3.3 kV high voltage power devices.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.115-131
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• 2022

Carbon dioxide (CO₂) emissions from the transportation sector in South Korea accounts for 16.5% of all CO₂ emissions, and road transportation accounts for 96.5% of this sector's emissions in South Korea. Hence, constant research is being carried out on methods to reduce CO₂ emissions from this sector. With the emerging use of smart crossings, attempts to monitor individual vehicles are increasing. Moreover, the potential commercial deployment of autonomous vehicles increases the possibility of obtaining individual vehicle data. As such, CO₂ emission research was conducted at five signalized intersections in the Gangnam District, Seoul, using data such as vehicle type, speed, acceleration, etc., obtained from image detectors located at each intersection. The collected data were then applied to the MOtor Vehicle Emission Simulator (MOVES)-Matrix model-which was developed to obtain second-by-second vehicle activity data and analyze daily CO₂ emissions from the studied intersections. After analyzing two large and three small intersections, the results indicated that 3.1 metric tons of CO₂ were emitted per day at each intersection. This study reveals a new possibility of analyzing CO₂ emissions using actual individual vehicle data using an improved analysis model. This study also emphasizes the importance of more accurate CO₂ emission analyses.

• Atmosphere
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• v.34 no.1
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• pp.35-53
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• 2024

Under the leadership of the National Institute of Meteorological Sciences (NIMS), the first domestic autonomous flight-type weather modification experimental drone for fog and lower-level cloud seeding was developed in 2021. This drone is designed based on a multi-copter configuration with a maximum takeoff weight of approximately 25 kg, enabling the installation of up to four burning flares for seeding materials and facilitating weather observations (temperature, pressure, humidity, and wind) as well as aerosol (PM₁₀, PM_2.5, and PM_1.0) particle measurements. This research aims to introduce the construction of the drone and its recent applications over the past two years, providing insights into the experimental procedures, effectiveness verification, and improvement directions of the weather modification drone-based rain enhancement. In particular, partial confirmation of the experimental effects was obtained through the fog dissipation experiment on December 10, 2021, and the lower-level cloud seeding case study on October 5, 2022. To enhance the scope and rainfall amount of weather modification experiments using drones, various technological approaches, including adjustments to experimental altitude, seeding lines, seeding amount, and verification methods are necessary. Through this research, we aim to propose the development direction for weather modification drone technology, which will serve as foundational technology for practical application of domestic rain enhancement technology.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.05a
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• pp.243-250
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• 2002

According to Ocean Korea 21, a basic plan established by the Ministry of Maritime Affairs and Fisheries (MOMAF) of Korea in May 2000, Korea Research Institute of Ships and Ocean Engineering (KRISO) proposed a program for the development of a deep-sea unmanned underwater vehicle (UUV) to explore deep sea for scientific purpose. KRISO has launched a project in May 2001 under the support of MOMAF. The deep-sea unmanned underwater vehicle will be applied to scientific researches in deep-sea as well as in shallow water. For operation of underwater vehicles in shallow water near the Korean Peninsula, a special design is required because of strong tidal current. In addition, MOMAF requires the vehicle to be designed for the purpose of long range survey, a long-term observation, and precise works in a specific area. Thus, KRISO has planned to design the system with the functional combination of both ROV and AUV. This paper presents the design of the deep-sea unmanned underwater vehicle.