• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.868-876
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• 2021

A school zone means a certain section designated among facilities, such as schools, childcare facilities, academies, etc., to protect children from the risk of traffic accidents. Since the school zone was established in September 1995, school zone accidents have not decreased even though it has been strengthened through a total of nine revisions until January 2021. This paper aims to present a standard model for child protection zones based on disaster prevention design. Methods of research included literature research, empirical research, and cognition research. Awareness survey was conducted on children, parents and drivers. Environmental surveys included crosswalks, motorways, pedestrian roads, and traffic lights. The investigation found that visual recognition of school zones by vehicle drivers was difficult, and found that motorcycles using pedestrian roads were a very threat to children. Accordingly, improved school zone standard model design centered on disaster prevention design was presented.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.617-626
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• 2022

With the advent of the autonomous driving era, automobiles are being discussed as an extension of the media. The growth of the in-vehicle infotainment(IVI) system can provide various benefits and values to the driver and passengers. Although the development and research of related technologies is being carried out, there has been no research that specifically identified users' valuation on the main attributes of IVI systems. This study uses conjoint analysis to investigate key attributes and users' preferences. The results indicate that the most important attribute for IVI system is provider, followed by system operation type, main service and content type. For each attribute, consumers prefer a detachable infotainment system provided by a telecommunication company, and prefer to use information-oriented services and content that they have previously consumed. This paper provides practical implications, especially in terms of convergence, that operators can refer to in IVI development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.622-629
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• 2019

Recently, the government is taking new approaches to change the fact that the accident rate and accident death rate of the construction industry account for a high percentage of the whole industry. Especially, it is investing heavily in the development of construction technology that is fused with ICT technology in line with the current trend of the 4th Industrial Revolution. In order to cope with this situation, this paper proposed a concept to recognize and share the work situation information between the construction machine driver and the surrounding worker to enhance the safety in the place where construction machines are operated. In order to realize the part of the concept, we applied image processing technology using camera based on artificial intelligence to earth-moving work. Especially, we implemented an algorithm that can recognize the surrounding worker's circumstance and identify the risk situation through the experiment using the compaction equipment. and image processing algorithm based on YOLO-v3. This algorithm processes 15.06 frames per second in video and can recognize danger situation around construction machine with accuracy of 90.48%. We will contribute to the prevention of safety accidents at the construction site by utilizing this technology in the future.

• Journal of KIISE
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• v.43 no.3
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• pp.389-397
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• 2016

In this paper, we propose a highway safety system that comprises a small number of central servers and smart mobile devices. To implement this system, we constructed a central server that collects GPS location information on cars, whose update messages are decreased via the car location estimation algorithm. The in-car mobile devices use the accelerometer sensors to detect hazardous situations; this information is updated to the central server that relays the information to the corresponding endangered cars via location-based unicast using LTE communication. To evaluate the proposed algorithm, we equipped a mobile device app on a real car and conducted real experiments in various environments such as city streets, rural areas, and highway roads. Furthermore, we conducted simulations to evaluate the propagation of danger information. Finally, we conducted simulated experiments to detect car collisions as well as exceptions, such as falling of the mobile device from the cradle.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.38-44
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• 2018

In this paper, we propose Intelligent Driver Assistance System (I-DAS) for driver safety. The proposed system recognizes safety and danger status by analyzing blind spots that the driver cannot see because of a large angle of head movement from the front. Most studies use image pre-processing such as face detection for collecting information about the driver's head movement. This not only increases the computational complexity of the system, but also decreases the accuracy of the recognition because the image processing system dose not use the entire image of the driver's upper body while seated on the driver's seat and when the head moves at a large angle from the front. The proposed system uses a convolutional neural network to replace the face detection system and uses the entire image of the driver's upper body. Therefore, high accuracy can be maintained even when the driver performs head movement at a large angle from the frontal gaze position without image pre-processing. Experimental result shows that the proposed system can accurately recognize the dangerous conditions in the blind zone during operation and performs with 95% accuracy of recognition for five drivers.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.279-280
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• 2022

도로를 주행 중인 운전자들은 비상용 차량이 접근할 때 경광등 혹은 백미러를 통해 확인하고, 도로의 상황을 파악한 후에서야 길을 양보한다. 그러나 비상 차량이 접근하는 걸 뒤늦게 인지하거나, 도로의 상황이 복잡하여 차선을 변경하다 접촉사고가 발생할 수도 있고, 또한 진행할 수 있는 도로를 미리 확보하지 못하여 비상 차량이 정해진 시간 내에 도착하지 못하는 경우가 자주 발생하고 있다. 이러한 일을 개선하기 위해서 본 논문에서는 안드로이드, GPS 기술을 이용한 앱을 통해 비상 차량이 일반 차량에 일정 거리 이내에 접근할 경우에 미리 알람을 보내고 이를 사전에 방지, 및 예방할 수 있는 앱을 개발한다. 안드로이드 스튜디오를 사용하였고, Firebase를 이용해 DB및 서버를 구축하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.102-116
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• 2021

For the safe operation of autonomous vehicles, the representative technology of the 4^th industrial revolution era, a combination of various technologies such as sensor technology, software technology and car technology is required. An autonomous vehicle is a vehicle that recognizes current location and situation by using the various sensors, and makes its own decisions without depending on the driver. Perfect recognition technology is required for fully autonomous driving. Since the precise road maps provide various road information including lanes, stop lines, traffic lights and crosswalks, it is possible to minimize the cognitive errors that occur in autonomous vehicles by using the precise road maps with location information of the road facilities. In this study, the definition, necessity and technical trends of the precise road map have been analyzed, and the HD(High Definition) map prototype based on the web GIS has been built in the autonomous driving-specialized areas of Daegu Metropolitan City(Suseong Medical District, about 24km), the Happy City of Sejong Special Self-Governing City(about 33km), and the FMTC(Future Mobility Technical Center) PG(Proving Ground) of Seoul National University Siheung Campus using the MMS(Mobile Mapping System) surveying results given by the National Geographic Information Institute. In future research, the built-in precise road map service will be installed in the autonomous vehicles and control systems to verify the real-time locations and its location correction algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.63-73
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• 2024

Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.135-150
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• 2002

The basic assumption of analytical Dynamic Traffic Assignment models is that traffic demand and network conditions are known as a priori and unchanging during the whole planning horizon. This assumption may not be realistic in the practical traffic situation because traffic demand and network conditions nay vary from time to time. The rolling horizon implementation recognizes a fact : The Prediction of origin-destination(OD) matrices and network conditions is usually more accurate in a short period of time, while further into the whole horizon there exists a substantial uncertainty. In the rolling horizon implementation, therefore, rather than assuming time-dependent OD matrices and network conditions are known at the beginning of the horizon, it is assumed that the deterministic information of OD and traffic conditions for a short period are possessed, whereas information beyond this short period will not be available until the time rolls forward. This paper introduces rolling horizon implementation to enable a multi-class analytical DTA model to respond operationally to dynamic variations of both traffic demand and network conditions. In the paper, implementation procedure is discussed in detail, and practical solutions for some raised issues of 1) unfinished trips and 2) rerouting strategy of these trips, are proposed. Computational examples and results are presented and analyzed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.577-586
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• 2018

In this study, traffic safety technology was developed for rural areas by reviewingthe relevant literature and data from the Traffic Accident Analysis System for the Chungcheong region.The goal is to reduce traffic accidents in small regional cities and rural areas in Korea. A road shoulder recognition light was developed to fit the pedestrian characteristics of the people using transportation in rural areas. It also minimizes damage to crops due to light pollution from traffic lights and street lights, and it supplements problems of damage from collision with vehicles and agricultural machines. The efficiency of the technology developed in this study was verified by comparing and analyzing the number of traffic accidents and the saved cost before and after its installation. A test bedwas established based on rural areas and is being evaluated for its applicability and effectiveness. It is expected that the reliability of such facilities could be improved through continuous studies, data collection, and analysis.