• Title/Summary/Keyword: Automatic crash notification system

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Estimation of Injury Severity of Occupant based on the Vehicle Deformation at Frontal Crash Accident (자동차 정면충돌에서 자동차 영구 변형량에 따른 승객 상해 추정)

  • Kim, Seungki;Choi, Hyung Yun
    • 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.

Construction of Driver's Injury Risk Prediction in Different Car Type by Using Sled Model Simulation at Frontal Crash (슬레드 모델 시뮬레이션을 이용한 자동차 정면충돌에서 차량 형태별 운전자 상해 판정식 제작)

  • Moon, Jun Hee;Choi, Hyung Yun
    • 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.