• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.93-99
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• 2020

A majority of car crash is affected by careless driving that causes extensive economic and social costs, as well as injuries and fatalities. Thus, the research of precise crash detection systems is very significant issues in automotive safety. A lot of crash detection algorithms have been developed, but the coverage of these algorithms has been limited to few scenarios. Road scenes and situations need to be considered in order to expand the scope of a collision detection system to include a variety of collision modes. The proposed algorithm effectively handles the x, y, and z axes of the sensor, while considering time and suggests a method suitable for various real worlds. To reduce nuisance and false crash detection events, the algorithm discriminated between driving mode and parking mode. The performance of the suggested algorithm was evaluated under various scenarios, and it successfully discriminated between driving and parking modes, and it adjusted crash detection events depending on the real scenario. The proposed algorithm is expected to efficiently manage the space and lifespan of the storage device by allowing the vehicle's black box system to store only necessary crash event's videos.

• Journal of Auto-vehicle Safety Association
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• v.16 no.2
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• pp.27-33
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• 2024

In this study, an analysis was conducted on internal and external factors related to fires in electric vehicles in order to improve the safety of electric vehicles against fire accidents. To conduct the analysis, field survey data conducted on actual electric vehicle fire accidents were used, and accident-related statistical data was used. Among them, as a result of analyzing the internal factors related to fire accidents in electric vehicles, it was confirmed that high-voltage batteries are an important factor in fire accidents caused by internal factors of electric vehicles. An analysis of external factors for fire accidents of electric vehicles was also conducted in this study. The largest number of electric vehicle accidents that occurred on public roads were mainly caused by physical external forces such as collisions. Therefore, strengthening the safety of this road infrastructure could be an additional solution to improve the fire safety of electric vehicles. As a result, based on car accident cases, two crash scenarios based on road infrastructure were derived, each of which simulates a high-speed frontal collision situation and a lower-end collision situation. Additionally, detailed test methods for these scenarios were developed.

• Journal of Auto-vehicle Safety Association
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• v.8 no.2
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• pp.11-16
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• 2016

The objective of this study was to construct the spring-mass models for the car-to-car offset frontal impact crash. The SISAME software was utilized to extract the spring-mass models using the data from the offset frontal crash test. The spring-mass model of the passenger car could effectively approximate the crash characteristics for the offset frontal barrier impact and the car-to-car offset frontal impact scenarios.

• Journal of Auto-vehicle Safety Association
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• v.7 no.2
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• pp.8-14
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• 2015

The objective of this study was to construct the spring-mass models for the car-to-car frontal impact crash. The SISAME software was utilized to extract the spring-mass models using the data from US-NCAP frontal crash tests. The spring-mass models of a compact car and a midsize car could effectively approximate the crash characteristics for the full frontal barrier impact and the car-to-car frontal impact scenarios. Compared to the barrier crash tests, the dummy injuries of midsize car decreased, while the dummy injuries of compact car increased, under the frontal car-to-car crash circumstances.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.167-182
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• 2022

The accident data attributes of the traffic accident report are used not only in traditional traffic safety-related research to identify the cause of traffic accidents, but also as basis data for the development of the automated vehicle driving performance verification scenarios. However, since the data attributes of the traffic accident report are limited for the purpose of reconstructing the traffic situation and developing scenarios, this study aims to provide the directions for improvement of traffic accident report, ultimately for its expanded usability for the automated vehicle test scenarios. The directions for improvement of the traffic accident report are provided by categorizing the traffic situation before the accident (pre-crash), the situation immediately before or during the accident (on-crash), and the situation after the accident (post-crash), respectively. Additional data items or data processing methods are presented. Furthermore, data elements that can be extracted from the traffic accident process data in the unstructured narrative form are explored and provided.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.134-145
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• 2024

The purpose of this study was to propose a framework for developing test scenarios for issuance of conditional driver's licenses. The framework was composed of five stages. Initially, we reviewed the literature on traffic crash characteristics in terms of accident frequency and severity regarding the main factors of crashes caused by older drivers. In the second stage, the characteristics of crashes attributed to non-elderly, early elderly, and late elderly drivers were analyzed using data obtained from the Traffic Accident Analysis System (TAAS), and crash types for elderly drivers were derived. In the third stage, black box videos of high-risk crash types were analyzed to derive crash stories that described the circumstances in which crashes occurred. In the fourth step, crash situations were classified by rating the types of crash stories derived to develop various scenarios. Step 5 involved creating a scenario by applying the PEGASUS 5-Layer format, which has recently been used to develop test scenarios for autonomous vehicles. The results of this study are expected to be used as a basis for developing driving ability evaluation scenarios for the issuance of conditional driver's licenses.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.39-47
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• 2023

Research on the safety of autonomous vehicle is being conducted in various countries, including the European Union, and computer simulation techniques so called 'Virtual Tool Chain' are mainly used. As part of the crash safety study of autonomous vehicle, 25 car to car collision scenarios were provided as a result of a real accident-based accident reproduction analysis study conducted by a domestic research institution, and a vehicle crash analysis was performed using the FE car to car model of the Honda Accord. In order to analyze the results of the car to car simulation and to construct a database, major crash parameters were selected as impact speed, angle, location, and overlap, and a method of defining them in an indexed form was presented. In order to compare the crash severity of each scenario, a value obtained by integrating the resultant acceleration measured by the ACU of the vehicle was applied. The equivalent collision test mode was derived by comparing the crash severity of the regulation test mode, 30 deg rigid barrier mode, in the same way.

• Journal of Auto-vehicle Safety Association
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• v.10 no.1
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• pp.27-31
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• 2018

This paper reports an analysis of cyclist accident cases with respect to passenger vehicles on Korean roads. A typology based on Initiative for the Global Harmonization of Accident Data (iGLAD) code book is applied to a traffic accident analysis system(TAAS), which has the real-world crash data on Korea roads, to understand the accident scenarios in more detail and efficiently. Similarly this typology has been used for Germany In-Depth Accidents Study (GIDAS) as well. The accident data analysis with consideration of the typology of Korean road conditions may prioritize traffic safety issues regarding cyclists and is aimed to develop an Automatic Emergency Braking (AEB) system for cyclist. In summary, this paper characterizes and analyzes the scenarios of cyclist crashes with passenger car. The most common accident scenarios on Korean roads are Car-to-Bicyclist Nearside Adult (CBNA) and Car-to-Bicyclist Longitudinal Adult (CBLA), which are more than 86% of total accidents cases. Therefore, it is inferred that AEB cyclist system should include these accident types in the operational design domain to reduce more fatality in Korea.

• Composites Research
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• v.24 no.5
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• pp.9-16
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• 2011

This paper describes the crashworthiness evaluation and performance improvement of tilting train made of sandwich composites. The applied sandwich composite of carbody structure was composed of aluminum honeycomb core and glass/epoxy & carbon/epoxy laminate composite facesheet. Crashworthiness analysis of tilting train was carried out using explicit finite element analysis code LS-DYNA 3D. The 3D finite element model and 1D equivalent model were applied to save the finite element modeling and calculation time for crash analysis. The crash conditions of tilting train were conducted according to four crash scenarios of the Korean railway safety law. It found that the crashworthiness analysis results were satisfied with the performance requirements except the crash scenario-2. In order to meet the crashworthiness requirements for crash scenario-2, the stiffness reinforcement for the laminate composite cover and metal frames of cabmask structure was proposed. Consequentially, it has satisfied the requirement for crash scenario-2.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.1-7
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• 2020

This study is a study on the development of AEBS test scenarios for traffic accidents in Korea, and was compared and analyzed using the Traffic Accident Analysis Program. To ensure the safety of passengers and pedestrians in traffic accidents, the number of cars equipped with ADAS is increasing rapidly at all car manufacturers in each country. For traffic accidents used in this study, the domestic traffic accident database (ACCC) produced by SAMSONG was used. Domestic traffic accidents differ from overseas traffic accidents in terms of road type, signal system, driver's seat location and number of vehicles. ACCC databases, which supplemented and reinforced these differences, built a database based on the PC-CRASH program. In the study, we analyze the types of accidents to develop comparative scenarios for each type of road and collision type of traffic accidents. When the road types of traffic accidents in Korea were divided into five types and the collision types were divided into six, it was confirmed that the most types of FRONT-SIDE crashes appeared at the intersection. It is expected that the frequency of possible traffic accidents and collision types can be predicted according to the road type in the accident database, we that it can be used as an AEBS test scenario development suitable for the domestic road environment.