• 제목/요약/키워드: Crash severity classification

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앙상블 학습기법을 활용한 보행자 교통사고 심각도 분류: 대전시 사례를 중심으로 (Classifying the severity of pedestrian accidents using ensemble machine learning algorithms: A case study of Daejeon City)

  • 강흥식;노명규
    • 디지털융복합연구
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    • 제20권5호
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    • pp.39-46
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    • 2022
  • 교통사고와 사회·경제적 손실 간의 연계성이 확인됨에 따라 사고 데이터에 기반을 둔 안전 정책 마련 및 중상·사망 등 그 심각도가 높은 교통사고의 절감 방안의 필요성이 제기되고 있다. 본 연구에서는 인구 대비 교통사고 사망자 비율이 높은 대전시를 대상지역으로 설정하고 보행자 교통사고 데이터를 수집한 후, 기계학습을 통해 최적알고리즘과 심각도 분류의 주요 인자를 도출하였다. 연구의 결과에 따르면, 적용한 9개 알고리즘 중 앙상블 기반의 학습 기법인 AdaBoost (Adaptive Boosting)와 RF (Random Forest)가 최적의 성능을 보여주었다. 이를 기반으로 도출된 대전시 보행자 교통사고 심각도의 주요 인자는 보행자의 연령이 70대 및 20대이거나 사고유형이 횡단사고에 의한 경우로 나타남에 따라 대전시 보행자 사고 저감 대책을 위한 고려요인으로 제안하였다.

머신러닝 기반의 수도권 지역 고령운전자 차대사람 사고심각도 분류 연구 (Classifying Severity of Senior Driver Accidents In Capital Regions Based on Machine Learning Algorithms)

  • 김승훈;임영빈;김기정
    • 디지털융복합연구
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    • 제19권4호
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    • pp.25-31
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    • 2021
  • 고령화 시대에 따라 고령운전자 역시 증가하고 있으며, 이들에 의한 교통사고 심각성에 대한 관심이 높아지고 있다. 이에 고령운전자에 의한 사고심각도 예측 모형의 필요성이 점차 요구됨에 따라, 본 연구에서는 기계학습 기법을 활용하여 고령운전자에 의한 차대사람 사고심각도 예측을 위한 모형 정립 및 분석을 수행하고자 한다. 이를 위해 4개의 기계학습 알고리즘 (Logistic Model, KNN, RF, SVM)을 활용, 예측 모형을 개발하고 각 결과를 비교하였다. 연구 결과에 따르면 Logistic과 SVM 모형이 상대적으로 높은 예측력을 보였으며, 정확도 측면에서는 RF가 높은 것으로 나타났다. 추가적으로 각 중요 변수들을 이용하여 교차분석을 수행한 후 그 결과를 제시하였다. 본 연구의 결과들은 고령화시대에 고령운전자에 의한 사고심각성을 예방하기 위한 안전정책 및 인프라 개발에 활용될 것으로 판단된다.

승용차 정면충돌에서 에어백 전개가 운전자 손상에 미치는 영향 (The Effect that Air Bag Deployment in Car Head-on Collision on Injury to Driver)

  • 전혁진;김상철;이강현
    • 자동차안전학회지
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    • 제10권2호
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    • pp.13-19
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    • 2018
  • The purpose of this study was to evaluate the effect of air bag deployment in passenger car head-on collisions on injuries to the driver. The drivers in head-on collisions who were brought to the emergency rooms of two hospitals from January 2011 and October 2014 were evaluated, as were the vehicles involved. The driver injury level were assessed by utilizing Collision Deformation Classification (CDC) codes, and the Abbreviated Injury Scale (AIS) and Injury Severity Score (ISS), respectively. In this study, it was shown that the chest ISS and AIS were significantly high when an air bag only is deployed. A statistically significant difference was found in the crush extent when the driver who fastened the seatbelt was found to be affected more than the ISS 9. Even when an air bag is deployed in a head-on car collision, injury severity can vary according to accident circumstances and crash severity. Accordingly, first aid can be rapidly given, and the injured person can be quickly referred to a hospital, only if the assessment of persons involved in a vehicle accident is accurately carried out.

한국형 실사고 심층조사 데이터베이스 질향상을 위한 차량속도(ΔV) 측정방법에 관한 연구 (Research on the Investigation of ΔV (Delta-V) for the Quality Improvement of Korean In-Depth Accident Study (KIDAS) Database)

  • 추연일;이강현;공준석;이희영;전준호;박종진;김상철
    • 자동차안전학회지
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    • 제12권2호
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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.

12인승 밴 전복사고의 상해 분석 (Injury Analysis of a 12-passenger Van Rollover Accident)

  • 김상철;최형연;김병우;박관진;안성민;이강현
    • 자동차안전학회지
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    • 제10권1호
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    • pp.20-26
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    • 2018
  • The fatality of rollover accidents in motor vehicle crashes is high despite their low incidence. Through the investigation of a 12-passenger van rollover accident in which 10 passengers were involved, we intend to analyze the correlation between the severity of the injury and the position of the occupants. We collected accident information from medical records, interviews, photo-images of the damaged van, field surveys, and the results of the Korean New Car Assessment Program (KNCAP). Based on the occupants' position, we classified injury sites and estimated injury severity. Passenger injury severity was evaluated by trauma score calculation. The initiation type of the rollover accident was passenger side 'fall-over' and the Collision Deformation Classification (CDC) code for the damaged van was 00TDZO3. The crash of the van involved 10 passengers, with an average age of $16.3{\pm}4.2years$. Few of the occupants had fastened seat belts at the time of the incident, and there was no airbag installed. One patient sustained severe liver injury and another was diagnosed with a fracture of the right humerus. The most common injuries were at the upper extremities and the neck. The average of Injury Severity Score (ISS) was $4.8{\pm}5.9$, and the average ISS of right-seated, mid-seated and left-seated occupants was $7.5{\pm}9.3$, $1.5{\pm}0.7$, and $3.3{\pm}2.1$ respectively (p>0.05). In the rollover (to-passenger side) accident of occupant unfastened, the average ISS of right-seated occupants (near side) was higher, but there was no statistically significant difference.