• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.246-248
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• 2017

Self-driving cars have three main functions. The first recognizes the surrounding environment, judge the risk, and lastly plans the drive path. Therefore, the driving operation is minimized. And it refers to a human friendly car capable of safe driving on its own. The reason for the need for self-driving car was to reduce traffic jams on limited roads and to reduce carbon dioxide emissions. Driving ahead of these self-driving car businesses can be expected to attract and expand the existing business and expand the new business and create new business opportunities for ICT firms. It is urgent for the concerned agencies to establish legal and institutional basis for self-driving cars. By doing so, new services could be provided to consumers. Therefore, this paper introduces the technological development trends for self-driving cars.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5299-5320
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• 2019

Interest in self-driving vehicle research has been rapidly increasing, and related research has been continuously conducted. In such a fast-paced self-driving vehicle research area, the development of advanced technology for better convenience safety, and efficiency in road and transportation systems is expected. Here, we investigate research in self-driving vehicles and analyze the main technologies of driverless car software, including: technical aspects of autonomous vehicles, traffic infrastructure and its communications, research techniques with vision recognition, deep leaning algorithms, localization methods, existing problems, and future development directions. First, we introduce intelligent self-driving car and road infrastructure algorithms such as machine learning, image processing methods, and localizations. Second, we examine the intelligent technologies used in self-driving car projects, autonomous vehicles equipped with multiple sensors, and interactions with transport infrastructure. Finally, we highlight the future direction and challenges of self-driving vehicle transportation systems.

• Journal of Korea Entertainment Industry Association
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• v.13 no.5
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• pp.229-238
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• 2019

The aim of the research is to investigate relationship between drivers' self-control, driving behavior and driving stress. 180 people who have driver's licence and have experiences in driving in Gwangju and Jeonnam area participated for the research. The survey was conducted from 29^th April 2015 to 24^th July 2015 and data was analysed to figure out the relationship between drivers' self-control, driving behavior and driving stress. As a result, Firstly, drivers' self-control affected mistakes, violations, errors of driving behavior, and driving environment, traffic regulations, accident control, time pressure of driving stress. It showed a statistical significant difference and the higher drivers' self-control is, the lower sub construct factor of driving behavior and driving stress. Secondly, those factors of drivers' self-control, driving behavior and driving stress were correlated. The result showed the relationship between drivers' self-control, driving behavior and driving stress. It is also possible to utilize the information to prevent car accidents. Finally, it is expected to do research further by expanding the participants into multiple areas of people.

• The Journal of Information Systems
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• v.31 no.3
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• pp.47-65
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• 2022

Purpose With the recent development of Big Data and Artificial Intelligence technology, self-driving technology has developed into three stages (partial self-driving) or four stages (conditional self-driving), it is expected to bring a new paradigm to transportation in the city. Although many researchers are researching related technologies, there is no research on self-driving for disabled persons. In this study, the basic research was conducted based on the assumption that the shared self-driving car used by the disabled person is similar to the special transportation currently driving. Design In this study, data analysis and machine learning techniques were utilized to analyze the mobility patterns of disabled persons by type and to search for leading factors affecting the traffic volume of special transportation. Findings The study found that external physical disorders and developmental disorders often visit general welfare centers, internal organ disorders often visit general hospitals, and the elderly and mental disorders have various destinations. In addition, machine learning analysis showed that the main transportation routes for the disabled person use arterial roads and auxiliary arterial roads and that the ratio of building usage-related variables affecting the use of special transportation for a disabled person is high. In addition, the distance to the subway and bus stops was also mentioned as a meaningful variable. Based on these analysis results, it is expected that the necessary infrastructure for shared self-driving cars for disability person traffic will be used as meaningful research data in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.18-20
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• 2019

In this paper, in order to prevent accidents when deviating from the lane during high-speed self-driving, we are going to design a warning system that will sound an alarm after recognizing the surrounding situation with a $360^{\circ}$ camera. Accidents often occur while driving on self-driving cars because they try to change lanes excessively or fail to recognize people, animals and objects that appear suddenly when driving at high speeds. The government wants to identify the surrounding situation with cameras when driving off a lane during high-speed autonomous driving, and to create a car that sounds a warning system through a lane departure sensor on the underside of the vehicle to reduce various accidents that occur during self-driving and to have a safer driving system.

• Korean Journal of Culture and Social Issue
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• v.13 no.4
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• pp.101-112
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• 2007

We investigated the influences of 'Circumstance Insensibility', 'Unsafe Driving', 'Incautious Driving', and 'Self-efficacy of Driving', consisting of driving confidence level, on traffic accidents. 1055 drivers conducted Driving Confidence Level Questionnaire, items about their dangerous driving experience and traffic accidents. Among them, after checking the missing items, we analyzed data of 998 drivers. As a result, we found the relation between driving confidence levels and traffic accidents. Specially, 'Circumstance Insensibility' and 'Unsafe Driving' influenced traffic accidents. However 'Circumstance Insensibility' had negative effects, the other side 'Unsafe Driving' had positive effects on traffic accidents. This result means each factor of driving confidence levels have different relation with traffic accidents. 'Incautious Driving' and 'Self-efficacy of Driving' didn't have any effects on traffic accidents in this research. In future, it should be investigated 'Incautious Driving' and 'Self-efficacy of Driving'.

• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.223-231
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• 2020

Older drivers have an increased risk of accidents due to poor function, but they also develop self-regulation ability to check their own changes. Thus, information on whether the actual elderly driver responds to changes in driving ability and risk may provide a meaningful basis for the clinic and research of the elderly's driving ability assessment. Therefore, the purpose of this study is to provide basic data for the evaluation of elderly drivers by analyzing the driving risk self-perception characteristics in terms of driving behavior and function with Korean elderly drivers. A self-reporting assessment was conducted on 500 elderly drivers living in the community and the characteristics of driving risk perception were analyzed. As a result, it was confirmed that many elderly drivers are aware of the driving risk when their vision and hearing are impaired or when they find it difficult to adapt to changes in driving conditions. On the other hand, the characteristics of insensitive reactions to changes in medical health conditions, such as drug use or epilepsy, seizures, and loss of consciousness, were identified. The researcher hopes this study will contribute to the safety management of elderly drivers in Korea, where aging is accelerating.

• Journal of Arbitration Studies
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• v.31 no.4
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• pp.119-136
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• 2021

Due to the restriction of movement caused by the Corona epidemic and the expansion of the "big face" through human distance, the "unmanned system" based on artificial intelligence and the Internet of Things has been widely used in modern life. "Self-driving," one of the transportation systems based on artificial technology, has taken the initiative in the transportation system as the spread of Corona has begun. Self-driving technology eliminates unnecessary contact and saves time and manpower, which can significantly impact current and future transportation. Accidents may occur, however, due to the performance of self-driving technology during transportation albeit the U.S. allows ordinary people to drive automatically through experimental operations, and the product liability law will resolve the dispute. Self-driving has become popular in the U.S. after the experimental stage, and in the event of a self-driving accident, product liability should be applied to protect drivers from complicated self-driving disputes. The purpose of this paper is to investigate whether disputes caused by defects in ordinary cars can be resolved through arbitration through U.S. precedents and to investigate whether disputes caused by defects in autonomous cars can be arbitrated.

• Journal of the Korea Society for Simulation
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• v.24 no.3
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• pp.97-105
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• 2015

This paper is to analyze the efficiency of power consumption in logistic systems that are based on self-driving roller conveyors by the simulation technology. The improvement of the efficiency brings advantages for reducing greenhouse gas emission and logistics costs. A self-driving roller conveyor is operated only when products are loaded on itself. Thus, the self-driving roller conveyor systems consume less electric power than continuous-driving roller conveyor systems. In this paper, we design a DEVS (Discrete-Event based System) based simulation model and construct self-driving roller and continuous-driving roller conveyor models. For the verification and validation of the designed simulation system and conveyor models, we model a corresponding logistic model for the experimental environment and compare between the model and a real system. The main objective of this paper is to describe the power consumption advantage of self-driving roller conveyor based logistic systems using a simulation method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.31-42
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• 2021

In the modern era, radio wave analysis is necessary for various fields of engineering, and interpretation of this is also indispensable. Self-driving cars need multiple different electronic components, and thus accurate and fast electromagnetic simulator for this kind of complex radio environment is required for self-driving simulations. Accordingly, the demand for self-driving simulators as well as existing electromagnetic analysis software has increased. This paper briefly describes the characteristics of numerical analysis techniques for electromagnetic analysis, self-driving simulation software, and conventional electromagnetic simulation software and also summarizes the characteristics of each software. Finally, the verification of the result from in-house code compared to HFSS is demonstrated.