• Journal of Auto-vehicle Safety Association
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• v.11 no.1
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• pp.30-35
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• 2019

KIDAS (Korean In-Depth Accident Study) is a data structure of accident investigation type, vehicle breakage and human injury database. A consortium of research institutes, universities, and medical institutions has been established and operated. KIDAS has the strongest difference from the TAAS (Traffic Accident Analysis System), which is the data of the National Police Agency, that it can grasp the injury information of passengers. In this study, the mean age and weight of the most frequent accident types in the KIDAS accident statistics were calculated to determine the degree of injury according to gender. Through the MADYMO analysis, it is aimed to grasp the difference of dummy injury using commercial dummy models and scaling models are currently used.

• Journal of Auto-vehicle Safety Association
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• v.12 no.2
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• pp.40-46
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• 2020

Modern traffic accidents are a complex occurrence. Various indicators are needed to analyze traffic accidents. Countries that have been investigating traffic accidents for a long time accumulate various data to analyze traffic accidents. The Korean In-Depth Accident Study (KIDAS) database collected damaged vehicles and severity of injury caused by Collision Deformation Classification code (CDC code), Abbreviated Injury Scale (AIS), and Injury Severity Score (ISS). As a result of the investigation, data relating to the injuries of the occupants can be easily obtained, but it was difficult to analyze human severity based on the information of the damaged vehicle. This study suggests a method to measure the speed change at the time of an accident, which is one of the most important indicators in the vehicle crash database, to help advance KIDAS research.

• Journal of Auto-vehicle Safety Association
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• v.7 no.2
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• pp.15-18
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• 2015

The availability of in-depth accident data is a prerequisite for each efficient traffic safety management system. Identification and definition of the relevant problem together with knowledge of the data and parameters describing this problem is essential for its successful solution. Comprehensive, up-to-date, accident data is needed for recognition of the scope of road safety problems and for raising public awareness. Reliable and relevant data enable the identification of the contributory factors of the individual accidents, and an unveiling of the background of the risk behaviour of the road users. It offers the best way to explore the prevention of accidents, and ways to implement measures to reduce accident severity. In this study, reviewing the existing iGlad and GIDAS system, KIDAS data format can be finalized through feasibility evaluation. The progressive approach is proposed to successful settlement of Korea in-depth accident study. As the initial stage of in-depth investigation DB construction, the KIDAS is not repetition of the current police based TAAS. It is essential part of improving vehicle safety and reduction of traffic fatality in Korea. 72 Contributing factors like road and traffic characteristics, vehicle parameters, and information about the people involved in the accident have to be investigated and registered as well in the KIDAS.

• Journal of Auto-vehicle Safety Association
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• v.10 no.3
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• pp.7-12
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• 2018

The Korean New Car Assessment Program (KNCAP) is a program to evaluate the safety of automobiles. In the safety assessment method, there are frontal collision, partial frontal collision, side collision, pillar collision, and left stability in the collision safety category. Among them, Korean in-depth analysis data shows that there are a lot of side collision accidents and it is necessary to protect them. This study will analyze the side collision accident that occurred in actual traffic accident based on Korea In-Depth Accident Study (KIDAS) and investigate the effect of center airbag on passenger in under side collision. In addition, with simulated side collision scenarios in the various side impact directions, it was investigated how the center airbag affects the driver and passenger in terms of kinematic and injury levels.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.7-12
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• 2019

AEB (Autonomous Emergency Braking system), a system in which vehicles automatically recognize forward objects or pedestrians and actively brake when forward collisions are expected, has been mandated by NHTSA (National Highway Traffic Safety Administration) and IIHS (Insurance Institute for Highway Safety) for all vehicles sell in the United States since 2022, and AEB research is also actively underway in korea. In this study, it can be confirmed that the passenger injury is reduced according to the AEB detection distance when it is assumed that the AEB is mounted in the actual event generated from KIDAS (Korea New Car Assessment Program) data through various analysis programs.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.43-47
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• 2019

Developed countries are operating an in-depth database in motor vehicle crashes nationwide. They do not rely solely on the police investigation reports that are responsible for motor vehicle crashes in each country but are developing into a useful database by expanding the categories of data through more indicators addition. In Korea, after implementing comprehensive measures to reduce traffic accident deaths in 2013, the medical centers participated in establishing the actual accident investigation system, which was called as the Korean In-Depth Accident Study (hereinafter KIDAS). This KIDAS database included more in-depth indicators as the types of accidents, types of vehicles, the injury severity, adequacy of safety devices, seating position of passengers. Although there are difficulties in establishing an actual accident investigation system including data collection due to various restrictions, if the system can cooperate with each other such as medical centers, insurance companies, police, fire and rescue services, towing companies, and car repair shops in the future, It would be expected to contribute to the development of safer vehicle, treatment system and traffic safety policy that lower the injury severity of occupant in the event of a motor vehicle crashes.

• Journal of Auto-vehicle Safety Association
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• v.9 no.1
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• pp.32-36
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• 2017

In order to reduce the damage of life and property caused by an automobile accident, we should design new car models and safety standard with reference to the data analysis and in-depth investigation of the accident. In-depth research and analysis of the current world other than the police investigation team (GIDAS, iGLAD, NHTSA, etc.) and collect in-depth data. Going to develop a safety policy to make it much safer cars based on this data. However, the country still does not have the advantage of KIDAS data Safety Policy Direction. In KNCAP tests, there is nothing in order to protect far side passengers even if far side impact causes approximately 50% injured people. Based on DBs like KIDAS (Korean In-Depth Accident Study) and GIDAS, far side passengers got injured as much as near side passengers did. So as to protect far side passengers, KNCAP has to change the test method of side crashes. In this study, injury severities to compare with ES-2, World SID and Thor dummies and the movements of far and near side passengers, SLED TEST was used.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.29-36
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• 2014

The accident statistics use the data from police accident reports and statistics. Although the official accident statistics are useful, they provide very limited information about how accidents occur, the cause of the accident and the injury mechanisms. This limitations could be overcome by carrying out the in-depth accident study and analysing investigations, collecting more detailed information. Meanwhile a net of in-depth investigation teams are operating worldwide, such as NASS (National Accident Sampling System) and CIREN (Crash Injury Research and Engineering Network) in US, OTS (On the spot investigation) in UK. In this study, the database structure and variables of Korea in-depth accidents investigation system would be proposed through considering the database structure of GIDAS (Germany In-Depth Accidents Study). GIDAS is one of the best system on the in-depth accident study system in the world. GIDAS was established in 1999 as a cooperation project between Federal Highway Research Institute of Germany (BASt) and research association on automotive engineering of German Car Industry(FAT). The iGLAD (Initiative for the Global Harmonization of Accident Data) was also considered to introduce into the database variables of Korea in-depth accident study. Current police reports were compared with GIDAS and iGLAD. To collaborate of the Worldwide in-depth accident data, this paper proposed that the database of Korea in-depth accident study would be introduced the structure of GIDAS and the core variables of iGLAD. Harmonization of the structures and core variables of Korea in-depth accident study will be better than the making unique ones. The database structure and core variables of KIDAS(Korea In-Depth Accident Study) introduced of GIDAS and iGLAD.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.530-537
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• 2016

This study investigates frontal crashes, analyzes the driver's action related to the change of the collision direction and determines the severity of (bodily injury). This study was conducted from August, 2013, to January, 2014, and the data for the car damage and human body damage were collected by emergency medical teams. In terms of data collection, we collected the accident vehicle, crash direction, body damage, etc., based on the Korea In-depth Accident Study (KIDAS) and Injury Severity Score (ISS). We used Minitab 17 and SPSS 22.0 to do the frequency analysis and ANOVA. In the analysis results, the prevalence of frontal collisions was 55.8% and mostly occurred in the 12 o'clock direction. In the analysis of the frontal crash direction according to age, the average ages for the 11, 12 and 1 o'clock directions were $46.46{\pm}13.47$, $44.43{\pm}13.40$ and $52.46{\pm}12.04$, respectively, so the older age drivers had a high probability of the accident occurring in the 1 o'clock direction. In the analysis of men's frontal collision direction according to age, the average ages in the 11, 12 and 1 o'clock directions were $47.10{\pm}13.88$, $45.24{\pm}13.78$ and $55.73{\pm}13.38$, respectively, so older aged men had a high probability of having collisions in the 1 o'clock direction. However, the statistical analysis of the frontal crash direction according to age in women didn't show any meaningful trend. When comparing the ISS according to age of the men and women in the collision direction, the men were less likely to have a 12 o'clock collision when $ISS{\geq}9$ and more likely to have a 1 o'clock collision when ISS<9. As a result, frontal crashes are more likely to occur in the 12 o'clock direction and the ISS decreases because the likelihood of frontal crashes in the 1 o'clock direction increases with increasing age. Therefore, when men recognize that they are heading for a 12 o'clock direction collision, they try to steer to the left to reduce the body damage.

• Journal of Auto-vehicle Safety Association
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• v.10 no.3
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• pp.20-26
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• 2018

It was a pilot study for developing an algorithm to determine the presence or absence of cervical spine injury by analyzing the severity factor of the patients in motor vehicle occupant accidents. From August 2012 to October 2016, we used the KIDAS database, called as Korean In-Depth Accident Study database, collected from three regional emergency centers. We analyzed the general characteristics with several factors. Moreover, cervical spine injury patients were divided into two groups: Group 1 for from Quebec Task Force (hereinafter 'QTF') grade 0 to 1, and group 2 for from QTF grade 2 to 4. The score was assigned according to the distribution ratio of cervical spine injured patients compared to the total injured patients, and the cut-off value was derived from the total score by summation of the assigned score of each factors. 987 patients (53.0%) had no cervical spine injuries and 874 patients (47.0%) had cervical spine injuries. QTF grade 2 was found in 171 patients (9.2%) with musculoskeletal pain, QTF grade 3 was found in 38 patients (2.0%) with spinal cord injuries, and QTF grade 4 was found in 119 patients (6.4%) with dislocation or fracture, respectively. We selected the statistically significant factors, which could be affected the cervical spine injury, like the collision direction, the seating position, the deformation extent, the vehicle type and the frontal airbag deployment. Total score, summation of the assigned each factors, 10 was presented as a cut-off value to determine the cervical spine injury. In this study, it was meaningful as a pilot study to develop algorithms by selecting limited influence factors and proposing cut-off value to determine cervical spine injury. However, since the number of data samples was too small, additional data collection and influencing factor analysis should be performed to develop a more delicate algorithm.