• Management & Information Systems Review
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• v.4
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• pp.257-284
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• 2000

According as the drivers increase who have their cars, the comprehensive studies on the automobile for the traffic safety have been raised as the important problems. Visual Recognition System for radio-controled driving is a part of the sensor processor of Unmanned Autonomous Vehicle System. When a driver drives his car on an unknown highway or general road, it produces a model from the successively inputted road traffic information. The suggested Recognition System of the Road Traffic Safety Information Board is to recognize and distinguish automatically a Road Traffic Safety Information Board as one of road traffic information. The whole processes of Recognition System of the Road Traffic Safety Information Board suggested in this study are as follows. We took the photographs of Road Traffic Safety Information Board with a digital camera in order to get an image and normalize bitmap image file with a size of $200{\times}200$ byte with Photo Shop 5.0. The existing True Color is made up the color data of sixteen million kinds. We changed it with 256 Color, because it has large capacity, and spend much time on calculating. We have practiced works of 30 times with erosion and dilation algorithm to remove unnecessary images. We drawing out original image with the Region Splitting Technique as a kind of segmentation. We made three kinds of grouping(Attention Information Board, Prohibit Information Board, and Introduction Information Board) by RYB( Red, Yellow, Blue) color segmentation. We minimized the image size of board, direction, and the influence of rounding. We also minimized the Influence according to position. and the brightness of light and darkness with Eigen Vector and Eigen Value. The data sampling this feature value appeared after building the learning Code Book Database. The suggested Recognition System of the Road Traffic Safety Information Board firstly distinguished three kinds of groups in the database of learning Code Book, and suggested in order to recognize after comparing and judging the board want to recognize within the same group with Nearest Neighborhood Decision Making.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.544-554
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• 2014

In this paper, we introduce a cyber-physical intersection systems (CPIS) which intimately interconnects roadside units (RSU) located at intersection, on-board units (OBU) of moving vehicles, and smartphone apps. Based on the architecture of CPIS, we also present a green light optimal speed advisory based on the reference mobility models (GLOSA-RMM) to reduce intersection stopping time (IST) and fuel consumption. Based on several reference mobility models, the GLOSA-RMM determines the appropriate speed advisory by taking into account the current mobility and the intersection traffic light status, and then provides screen/voice GLOSA instructions to minimize the driver's distraction. We show that the GLOSA-RMM can reduce both the IST and the fuel consumption through the numerical results obtained from the prototype of the CPIS consisting of the OBU, the RSU and the smartphone app.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.422-424
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• 2010

Recently the car attached many ECUs and entertainment devices to provide the easiness maintenance and driver's convenience. CAN and MOST networks have been used to manage and control those devices in the car. Wireless network also has been established to receive information from external. These days a car navigation system with GPS is being integrated with CAN, MOST and Wireless network. In these circumstances, the car navigation system can have HMI function to integrate and control the car networks' devices. To solve the GPS problems such as positioning errors or losing signals from satellites in the tunnels and urban canyons, this paper designs and implements a method for positioning vehicle by using the sensing data of sensors and Wi-Fi devices based on this integrated environment.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.54-61
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• 2019

Recently, IITS (intelligent integrated transportation system) has been important topic in Smart City related industry. As a main objective of IITS, prevention of traffic jam (due to car accidents) has been attempted with help of advanced sensor and communication technologies. Studies show that car accident has certain correlation with some factors including characteristics of location, weather, driver's behavior, and time of day. We concentrate our study on observing auto correlativity of car accidents in terms of time of day. In this paper, we performed the ARIMA tests including ADF (augmented Dickey-Fuller) to check the three factors determining auto-regressive, stationarity, and lag order. Summary on forecasting of hourly car crash counts is presented, we show that the traffic accident data obtained in Korea can be applied to ARIMA model and present a result that traffic accidents in Korea have property of being recurrent daily basis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.632-637
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• 2019

Recent researches on autonomous driving of vehicles are becoming very active, and it is a trend to assist safe driving and improve driver's convenience. Autonomous vehicles are required to combine artificial intelligence, image recognition capability, and Internet communication between objects. Because mobile telecommunication networks have limitations in their processing, they can be easily implemented and scale using an easily expandable Wi-Fi network. We propose a wireless design method to construct such a vehicle control network. We propose the arrangement of AP and the software configuration method to minimize loss of data transmission / reception of mobile terminal. Through the design of the proposed network system, the communication performance of the moving vehicle can be dramatically increased. We also verify the packet structure of GPS, video, voice, and data communication that can be used for the vehicle through experiments on the movement of various terminal devices. This wireless design technology can be extended to various general purpose wireless networks such as 2.4GHz, 5GHz and 10GHz Wi-Fi. It is also possible to link wireless intelligent road network with autonomous driving.

• Journal of IKEEE
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• v.22 no.4
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• pp.970-977
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• 2018

The autonomous vehicle is based on an advanced driver assistance system (ADAS) consisting of a sensor that collects information about the surrounding environment and a control module that determines the measured data. As interest in autonomous navigation technology grows recently, an easy development framework for ADAS beginners and learners is needed. However, existing development and verification methods are based on high performance vehicle simulator, which has drawbacks such as complexity of verification method and high cost. Also, most of the schemes do not provide the sensing data required by the ADAS directly from the simulator, which limits verification reliability. In this paper, we present an interactive ADAS development and verification framework using a 3D vehicle simulator that overcomes the problems of existing methods. ADAS with image recognition based artificial intelligence was implemented as a virtual sensor in a 3D car simulator, and autonomous driving verification was performed in real scenarios.

• Journal of the Korean Institute of Rural Architecture
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• v.25 no.1
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• pp.35-44
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• 2023

This study aimed to understand the driver change of recent research in relation to rural and migrant and draw overarching issues as well as to provide implications to contribute to migrants' social integration in Korean rural areas. As for the scope and method of the study, data through quantitative bibliographic analysis (quantitative data) and research keywords by period were derived. To address the aim this study employed bibliometric analysis utilising netwok mapping interface analysis by VOSviewer and topic modeling analysis by Netminer. The findings were revealed that firstly mental health issues in abroad research and employment and discrimination in domestic research both derived from migrant mobility constituted staple key issues, secondly internal and external research differed two issues in health and violence where Korea has overlooked the issues seriously. Therefore this study presented implications which are about first, health and violence-related sections for migrants should be specified into domestic law, second domestic-focused MIPEX index should be developed in which the two issues are over-weighted and last such newly emerging approach 'inclusive formation of social psychological mechanisms should be widely spread. Concluding remark is that delivering the implications can be foster to migrants' integration in rural area underlining that this will ultimately contribute to migrants' quality of life.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.535-538
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• 2022

For Plug & Play of IoT devices, we develop a module that recognizes the type of USB, which is a typical wired interface of IoT devices, through image recognition. In order to drive an IoT device, a driver for communication and device hardware is required. The wired interface for connecting to the IoT device is recognized by using the image obtained through the camera of smartphone shooting to recognize the corresponding communication interface. For USB, which is a most popular wired interface, types of USB are classified through artificial neural network-based machine learning. In order to secure sufficient data set of artificial neural networks, USB images are collected through the Internet, and additional image data sets are secured through image processing. In addition to the convolution neural networks, recognizers are implemented with various deep artificial neural networks, and their performance is compared and evaluated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.388-390
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• 2021

This paper introduces a system that can help visually impaired people to board a bus using an embedded board with keypad, dot matrix, lidar sensor, NFC reader, a public data portal Open API system, and deep learning algorithm (YOLOv5). The user inputs the desired bus number through the NFC reader and keypad, and then obtains the location and expected arrival time information of the bus through the Open API real-time data through the voice output entered into the system. In addition, by displaying the bus number as the dot matrix, it can help the bus driver to wait for the visually impaired, and at the same time, a deep learning algorithm (YOLOv5) recognizes the bus number that stops in real time and detects the distance to the bus with a distance detection sensor such as lidar sensor.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.241-246
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• 2010

This study is to estimate the link travel time of road networks in urban areas utilizing traffic information which is collected throughout the operation of Bus Information System (BIS). BIS, which applies the hightech information technology to an existing bus system, has been developing and operating in many bodies including the local self-government entities. However, a study to consider the technology trend is relatively rare. Even though some useful traffic informations have been collected throughout the operation of an existing BIS, which set limits to the development of a future service of integrated analysis. Accordingly, in this study, a fundamental research is performed for traffic controls in urban areas and providing a traffic information for driver throughout the estimation of link travel time of road networks. The study is proceeded throughout the data collected from the operation of BIS (Bus Information System). The result showed that the patterns of going through traffic were divided up to 2 in the bus travel time in BIS then estimate two link travel time.