• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.182-199
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• 2023

Since 2021, government departments have been promoting Automated Driving Technology Development and Innovation Project as national research and development(R&D) project. The automated vehicles and service technologies developed as part of these projects are planned to be subsequently provided to the public at the selected Living Lab City. Therefore, it is important to determine a spatial area and operation section that enables safe and stable automated driving, depending on the purpose and characteristics of the target service. In this study, the static Operational Design Domain(ODD) elements for Level 4 automated driving services were reclassified by reviewing previously published papers and related literature surveys and investigating field data. Spatial analysis techniques were used to consider the reclassified ODD elements for level 4 in the real area of level 3 automated driving services because it is important to reflect the spatial factors affecting safety related to real automated driving technologies and services. Consequently, a total of six driving mode changes(disengagement) were derived through spatial information analysis techniques, and the factors affecting the safety of automated driving were crosswalk, traffic light, intersection, bicycle road, pocket lane, caution sign, and median strip. This spatial factor analysis method is expected to be useful for determining special areas for the automated driving service.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.90-98
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• 2020

Modern vehicles are evolving from manual to automatic driving. As the ratio of electrical equipment and software increases inside the vehicle, vehicles that support autonomous driving are becoming another open computer system that can communicate with the outside. The safety of the vehicle means the safety of both the passenger and the non-passenger. It is not clear whether the safety problem of ultimate autonomous vehicles can be solved by the current solution of computer systems related to fault tolerance and security. Autonomous vehicles should not be dangerous to people after they are released to the market, so it is necessary to proactively diagnose all the risks that can be predicted with current technology. This paper examines the current developments of autonomous vehicles and analyzes their dangers that threaten driving safety, as well as their countermeasures.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.231-241
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• 2019

This study was a descriptive survey to identify influences of nurses' professional autonomy and empathy on patient safety culture. The participants were 191 nurses working at a general hospital in Seoul. The data were collected using structured questionnaires and analyzed using the SPSS/WIN 24.0 program. Patient safety culture had a significant correlation with nurses' professional autonomy (r=.26, p<.001) and the subscales of empathy, which were perspective-taking (r=.30, p<.001) and empathic concern (r=.27, p<.001). Factors influencing patient safety culture were perspective-taking (${\beta}=.27$, p<.001), professional autonomy (${\beta}=.20$, p=.004), and a total clinical career of over ten years (${\beta}=.17$, p=.012). The results of this study could be the basic data for the development of programs that enhance the professional autonomy and empathy of nurses. In addition, it is necessary to study repeatedly in various groups in the future.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.6-13
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• 2022

The Ministry of Land, Infrastructure and Transport (MoLIT) and the Korean Automobile Testing and Research Institute (KATRI) are supporting the development of Lv.3 automated vehicle (hereinafter, AV) technology by constructing an automated driving pilot city (as known as K-City) equipped with total 5 evaluation environments (urban, motorway, suburban, community road, and autonomous parking facility) which is a test bed exclusively for AV (2017~2018). An upgrade project is in a progress to materialize harsh environments such as bad weather (rain, fog, etc.) and reproduction of communication jamming (GPS blocking, etc.) with the purpose of supporting the development of Lv.4 connected & automated vehicle (hereinafter, CAV) technology (2019~2022). We intend to proactively establish a national level standard for CAV test-bed and test road requirements, test method, etc. for establishment of a road map for the construction of the test bed which is being promoted step by step and analyze and, when required, benchmark the case of China that has announced and is utilizing it. Through this, we plan to define standardized requirements (evaluation facility, evaluation system, etc.) on the test bed for the development of Lv.4/4+ CAV technology and utilize the same for the design and construction of a test bed, establishment of a road map for the construction of a real car-based test environment related to the support for autonomous driving service substantiation, etc. through provision of an evaluation environment utilizing K-City, and the establishment of a K-City upgrade strategies, etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.221-239
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• 2022

Various elements such as geometry, traffic safety facilities, congestion level, weather, etc., need to be appropriately reflected in the assessment scenario evaluating the driving safety of automated vehicles. Therefore, this study first established a scenario structure and defined the layer of elements, to derive the elements to be reflected in the automated driving safety evaluation. After that, all elemental candidates that can be reflected in each layer were derived by reviewing the relevant literature. Finally, as a result of an expert survey, 77 items were selected to be reflected in the automated driving safety evaluation. The selected elements are expected to be actively utilized in developing scenarios for the driving safety evaluation of automated vehicles in simulation, proving ground, and real road assessments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.65-74
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• 2024

In recent years, image processing technology has played a critical role in the field of autonomous driving. Among them, image recognition technology is essential for the safety and performance of autonomous vehicles. Therefore, this paper aims to develop a hybrid image recognition system to enhance the safety and performance of autonomous vehicles. In this paper, various image recognition technologies are utilized to construct a system that recognizes and tracks objects in the vehicle's surroundings. Machine learning and deep learning algorithms are employed for this purpose, and objects are identified and classified in real-time through image processing and analysis. Furthermore, this study aims to fuse image processing technology with vehicle control systems to improve the safety and performance of autonomous vehicles. To achieve this, the identified object's information is transmitted to the vehicle control system to enable appropriate autonomous driving responses. The developed hybrid image recognition system in this paper is expected to significantly improve the safety and performance of autonomous vehicles. This is expected to accelerate the commercialization of autonomous vehicles.

• Product Safety
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• no.8 s.152
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• pp.26-27
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• 2006

• The Safety technology
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• no.195
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• pp.6-6
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• 2014

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1997.11a
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• pp.203-208
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• 1997

산업현장에 앗차 위험이 지속되고 있다. 그러나 근로자들은 너무나 앗차 위험 행동에 익숙하여 무감각하게 지나쳐 버리고 있다. 이러한 의식 구조 속에서는 안전이 활성화 될 수 없으며 사고 위험으로부터 헤어나지 못하는 기업이 될 것이다. 산업현장에서 중대재해가 발생되고 나면 신경을 별로 쓰지 않은 곳에서 발생했다고 말한다. 대수롭지 않게 묵인한 것이 대형재해로 싹트기까지는 오랜시간의 앗차경험을 겪어왔던 결과치다. 근로자들의 전사적인 안전의식을 강하게 느끼고 인식하여 안전행동을 추진하는 기업은 이와 같은 유사재해도 사전에 제거할 대응 자세가 갖춰지게 될 것이다. (중략)

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.172-191
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• 2023

This study was undertaken to strategize the mixed traffic operation of autonomous vehicles in the pilot zone. This was achieved by analyzing the changes expected when autonomous vehicles are mixed in the autonomous vehicle pilot zone. Although finding a safe and efficient traffic operation strategy is required for the pilot zone to serve as a test bed for autonomous vehicles, there is no available operation strategy based on the mixture of autonomous vehicles. In order to presents a traffic operation strategies for each period of autonomous vehicle introduction, traffic efficiency and safety analysis was performed according to the autonomous vehicle market percentage rate. Based on the analysis results, the introduction stage was divided into introductory stage, transition period, and stable period based on the autonomous vehicle market share of 30% and 70%. This study presents the following traffic operation strategies. Considering the traffic flow operation strategy, we suggest the advancement of the existing road infrastructure at the introductory stage, and operating an autonomous driving lane and the mileage system during the transition period. We also propose expanding the operation of autonomous driving lanes and easing the speed limit during the stable period. In the traffic safety strategy, we present a manual and legal system for responding to autonomous vehicle accidents in the introductory stage, an analysis of the causes of autonomous vehicle accidents and the implementation of preventive policies in the transition period, and the advancement of the autonomous system and the reinforcement of the security system during the stable period. Through the traffic operation strategy presented in this study, we foresee the possibility of preemptively responding to the changes of traffic flow and traffic safety expected due to the mixture of autonomous vehicles in the autonomous vehicle pilot zone in the future.