• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.95-105
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• 2019

In recent years, image processing techniques for detecting road surface damaged spot have been actively researched. Especially, it is mainly used to acquire images through a smart phone or a black box that can be mounted in a vehicle and recognize the road surface damaged region in the image using several algorithms. In addition, in conjunction with the GPS module, the exact damaged location can be obtained. The most important technology is image processing algorithm. Recently, algorithms based on artificial intelligence have been attracting attention as research topics. In this paper, we will also discuss artificial intelligence image processing algorithms. Among them, an object detection method based on an region-based convolution neural networks method is used. To improve the recognition performance of road surface damage objects, 600 road surface damaged images and 1500 general road driving images are added to the learning database. Also, supervised learning using background object recognition method is performed to reduce false alarm and missing rate in road surface damage detection. As a result, we introduce a new method that improves the recognition performance of the algorithm to 8.66% based on average value of mAP through the same test database.

• 재활복지
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• v.17 no.4
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• pp.339-370
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• 2013

This study is to suggest necessary improvements of inconvenient elements as well as the ergonomic design standard to develop disabled cars by evaluating the types of needs and observing the behavior characteristics on their car use and the survey on the complaints of the disabled drivers and their guardians in the use of disabled car. The results of this study are as follows. First, both the disabled drivers and their guardians are found to feel high inconvenience and low satisfaction with the cars they use now. Second, the disabled owner-drivers also answered in a same way as guardians. They find the most difficulty in moving the supporting equipment to get into and out of a car. Both the owner-drivers with disabilities and guardians complained of lack of handiness they face when they wear the seat belts and sitting on the seats. In view of this, a disabled car to be developed should have ergonomic design for its seats and the safety of the seatbelt as well as trouble-free supporting equipment helping them move. Third, rather than owner-drivers with handicaps, guardians expressed more difficulties and less contentment with the cars for the disabled, which is reckoned to lead to the changes of perspectives on development of cars for the disabled breaking away from existing viewpoints focusing on the accessibility to the vehicles. Fourth, both owner-drivers and guardians showed higher interests in driving and other safety and convenience measures than in using supporting equipment to get into and out of vehicles, implying that rather than the accessibility to get into and out of a car, convenience should primarily be taken into account for the design of the disabled car. Fifth, the auto-manufacturer is to give prior thought to user convenience when developing a car in practice. For this, the developer may have the disabled car users join the process of development as well as asking experts for help and participation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.34-48
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• 2019

The purpose of this study was two-fold; first, to develop safety performance functions (SPF) using transportation-related big data for all types of roads in Korea were developed, Second, to provide basic information to develop measures for relatively dangerous roads by evaluating the safety grade for various roads based on it. The coordinates of traffic accident data are used to match roads across the country based on the national standard node and link system. As independent variables, this study effort uses link length, the number of traffic volume data from ViewT established by the Korea Transport Research Institute, and the number of dangerous driving behaviors based on the digital tachograph system installed on commercial vehicles. Based on the methodology and result of analysis used in this study, it is expected that the transportation safety improvement projects can be properly selected, and the effects can be clearly monitored and quantified.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.521-531
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• 2020

QZSS (Quasi-Zenith Satellite System) provides the CLAS (Centimeter Level Augmentation Service) through the satellite's L6 band. CLAS provides correction messages called C-SSR (Compact - State Space Representation) for GPS (Global Positioning System), Galileo and QZSS. In this study, CLAS messages were received by using the AsteRx4 of Septentrio which is a GPS receiver capable of receiving L6 bands, and the messages were decoded to acquire C-SSR. In addition, Multi-GNSS (Global Navigation Satellite System) Code-PPP (Precise Point Positioning) was developed to compensate for GNSS errors by using C-SSR to pseudo-range measurements of GPS, Galileo and QZSS. And non-linear least squares estimation was used to estimate the three-dimensional position of the receiver and the receiver time errors of the GNSS constellations. To evaluate the accuracy of the algorithms developed, static positioning was performed on TSK2 (Tsukuba), one of the IGS (International GNSS Service) sites, and kinematic positioning was performed while driving around the Ina River in Kawanishi. As a result, for the static positioning, the mean RMSE (Root Mean Square Error) for all data sets was 0.35 m in the horizontal direction ad 0.57 m in the vertical direction. And for the kinematic positioning, the accuracy was approximately 0.82 m in horizontal direction and 3.56 m in vertical direction compared o the RTK-FIX values of VRS.

• 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).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.119-133
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• 2022

Due to the improvement of surveying, mapping and communication techniques, various apps for road direction guides and vehicle navigations have been developed. Although such a development has impacted on walking and driving, there is a limit to improving the daily convenience of the socially impaired people. This is mainly due to the fact that the software have been developed for normal pedestrians and drivers. Therefore, visually impaired people still have problems with the confusion of direction and/or non-provision of risk factors in walking. This study aimed to propose a scheme which constructs data for mobility-impaired or traffic-impaired people based on various geospatial information. The factors and components related to walking for the visually impaired are selected by geospatial data and a walking route guidance network that can be applied to a commercial software. As a result, it was confirmed that road direction guidance would be possible if additional contents, such as braille blocks (dotted/linear), sound signals, bus stops, and bollards are secured. In addition, an initial version of the application software was implemented based on the suggested data model and its usefulness was evaluated to a visually impaired person. To advance the stability of the service in walking for the visually impaired people, various geospatial data obtained by multiple institutes are necessary to be combined, and various sensors and voice technologies are required to be connected and utilized through ICT (Information and Communications Technologies) technology in near future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.417-425
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• 2022

Interest in micro cars is growing around the world, and policy support for micro cars has been increasing in Korea. It is important to meet minimum safety standards for the operation of micro cars on roads due to concerns around micro car safety and the limited driving range of micro cars. In this study, visibility experiments that included safety identification of micro cars were conducted to try and prevent a decrease in driver reaction time. Safety identification lights were installed to the rear of a micro car, and the visibility and discomfort of the vehicle were evaluated to determine whether the micro car was safe to drive on an expressway. As a result, the installation effect of Micro car which install safety identification lamp was found when joining the point at an acceleration lane of the grade separation intersection, and that light on/off could be effective when entering an expressway. If the micro car operation plan proposed in this study is applied, the safety of micro cars on expressways can be increased by improving the visibility of micro car.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.284-298
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• 2022

It is necessary to acquire information on traffic safety facilities installed on the roadways specifically for the operation of autonomous vehicles. The purpose of this study is to prepare a Korean version of an integrated message-set design as a way to provide to autonomous vehicles standardized information on traffic safety facilities. In this study, necessary facilities are classified according to four criteria (no legal basis; not providing information to autonomous vehicles; providing duplicate information; not standardized, and too difficult to generalize) based on information that must be provided to operate autonomous vehicles. The priority of information delivery (gross negligence followed by behavior change) was classified according to the importance of the information to be provided during autonomous driving, and the form was defined for the classification code in the information delivered. Finally, the information location and delivery method of traffic facilities for compliance with SAE J2735 were identified. This study is meaningful in that it provides a plan for roadway operations by suggesting a method for providing information to autonomously driven vehicles.

• Journal of Powder Materials
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• v.30 no.4
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• pp.324-331
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• 2023

Lithium (Li) is a key resource driving the rapid growth of the electric vehicle industry globally, with demand and prices continually on the rise. To address the limited reserves of major lithium sources such as rock and brine, research is underway on seawater Li extraction using electrodialysis and Li-ion selective membranes. Lithium lanthanum titanate (LLTO), an oxide solid electrolyte for all-solid-state batteries, is a promising Li-ion selective membrane. An important factor in enhancing its performance is employing the powder synthesis process. In this study, the LLTO powder is prepared using two synthesis methods: sol-gel reaction (SGR) and solid-state reaction (SSR). Additionally, the powder size and uniformity are compared, which are indices related to membrane performance. X-ray diffraction and scanning electron microscopy are employed for determining characterization, with crystallite size analysis through the full width at half maximum parameter for the powders prepared using the two synthetic methods. The findings reveal that the powder SGR-synthesized powder exhibits smaller and more uniform characteristics (0.68 times smaller crystal size) than its SSR counterpart. This discovery lays the groundwork for optimizing the powder manufacturing process of LLTO membranes, making them more suitable for various applications, including manufacturing high-performance membranes or mass production of membranes.