• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.77-83
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• 2022

Occupant behaviors and body contact with vehicle interior parts are main injury mechanism in far-side collisions. In vehicle side impact accident where the crash accident occurs on the opposite side of the vehicle from the a particular occupant, it is exposed in terms of relatively larger lateral motion to interact with the opposite side of the vehicle structure. The challenge of minimizing motions of upper body and injury risk according to a direct contact is a primary occupant protection research. This study has performed a data analysis of real-world accident database extracted from the 2016~2020 CISS database and a parametric investigation of impact angles and occupant kinematics in far-side lateral and oblique impact simulations. A detailed data analysis was conducted to reveal the relationship among the accident and injury data. Database analysis and computational far-side impact results proposed the fundamental vehicle design for safety improvement in far-side collisions.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.136-144
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• 2013

An extensive real world in-depth crash accident data is needed to make a precise occupant injury risk prediction at crash accidents which might be a critical information from the scene of the accident in ACNS(Automatic Crash Notification System). However it is rather unfortunate that there is no such a domestic database unlike other leading countries. Therefore we propose a numerical method, i.e., crash simulation using a sled model to make a virtual database that can substitute car crash database in real world. The proposing crash injury risk prediction is validated against a limited domestic crash accident data.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.2
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• pp.63-71
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• 2013

The estimation of occupant injury risk at crash accident is one of the most important assessments for the vehicle crashworthiness performance. The design of safety devices such as occupant restraining system also depend on the kinematics of occupant and its injury risk. The real world in-depth accident investigation provides detailed and realistic information of vehicle damage and occupant injury as well as the accident conditions. This paper introduces a statistical analysis of NASS/CDS database and domestic accident data to correlate speed change, vehicle damage extend, and occupant injury at frontal crash. The maximum crush extend shows a linear relationship with the effective impact speed. The injury risks of the occupant with and without restraining were also respectively quantified with the crush extend. This result can be effectively used for the emergent rescue of crash victims with automatic crash notification system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.133-144
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• 2017

Recently, weather information is getting closer to our real life, and it is a very important factor especially in the transportation field. Although the damage caused by the abnormal climate changes around the world has been gradually increased and the correlation between the road risk and the possibility of traffic accidents is very high, the domestic research has been performed at the level of basic research. The Purpose of this study is to develop a risk map for the road hazard forecasting service of weather situation by linking real - time weather information and traffic information based on accident analysis data by weather factors. So, we have developed a collection and analysis about related data, processing, applying prediction models in various weather conditions and a method to provide the road hazard map for national highways and provincial roads on a web map. As a result, the road hazard map proposed in this study can be expected to be useful for road managers and users through online and mobile services in the future. In addition, information that can support safe autonomous driving by continuously archiving and providing a risk map database so as to anticipate and preemptively prepare for the risk due to meteorological factors in the autonomous driving vehicle, which is a key factor of the 4th Industrial Revolution, and this map can be expected to be fully utilized.