• 한국재난정보학회 논문집
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• 제20권1호
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• pp.156-168
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• 2024

연구목적: 고속도로 교통사고의 추세는 증감을 반복하며 도로 종류 중 고속도로에서의 치사율은 최고치를 나타내고 있다. 따라서 국내 실정을 반영한 개선대책 수립이 필요하다. 연구방법: Random Forest를 활용해 2019년부터 2021년까지 전국 고속도로 노선 중 사고 다발 10개 노선에서 발생한 교통사고 자료로 사고 심각도 분석 및 사고 심각도에 미치는 영향요인을 도출하였다. 연구결과: SHAP 패키지를 활용해 상위 10개의 변수 중요도를 분석한 결과, 고속도로 교통사고 중 사고 심각도에 높은 영향을 미치는 변수는 가해자 연령이 20세 이상 39세 미만, 시간대가 주간(06:00-18:00), 주말(토~일), 계절이 여름과 겨울, 법규위반이 안전운전불이행, 도로 형태가 터널, 기하구조상 차로 수가 많고 제한속도가 높은 경우로 총 10개의 독립변수에서 고속도로 교통사고 심각도와 양(+)의 상관관계를 가지는 것으로 분석되었다. 결론:고속도로에서의 사고 발생은 매우 다양한 요인의 복합적인 작용으로 인해 발생하므로 사고 예측에 많은 어려움이 있지만 본 연구로 도출된 결과를 활용해 고속도로 교통사고 심각도에 영향을 주는 요인을 심층적으로 분석해 효율적이고 합리적인 대응책 수립을 위한 노력이 필요하다.

• 자동차안전학회지
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• 제13권3호
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• pp.69-77
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• 2021

Although accident data from the National Police Agency and insurance companies do not know the vehicle safety, the damage level information can be obtained from the data managed by the bus credit association or the bus company itself. So the accident severity was analyzed based on the side impact accidents using accident repair cost. K-means clustering analysis separated the cost of accident repair into 'minor', 'moderate', 'severe', and 'very severe'. In addition, the side impact accident severity was analyzed by using an ordered logit model. As a result, it is appeared that the longer the repair period, the greater the impact on the severity of the side impact accident. Also, it is appeared that the higher the number of collision points, the greater the impact on the severity of the side impact accident. In addition, oblique collisions of the angle of impact were derived to affect the severity of the accident less than right angle collisions. Finally, the absence of opponent vehicle and large commercial vehicles involved accidents were shown to have less impact on the side impact accident severity than passenger cars.

• 한국전자통신학회논문지
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• 제15권6호
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• pp.1123-1130
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• 2020

본 연구는 고속도로 교통사고 심각도 예측모델을 구축하기 위해 다섯가지 머신러닝 기반의 분류모형 적용하였다. 2015년~2017년 동안 전국 고속도로에서 발생한 사고 데이터 21,013건을 5가지의 분류 모형을 적용한 결과 LightGBM(Light Gradient Boosting Model)이 가장 좋은 성능을 나타내는 것으로 나타났다. LightGBM에서는 교통사고심각도 추정에 있어 우선순위 요인으로 사고차량 수, 사고유형, 사고지점, 사고차로유형, 사고차량 유형 순으로 나타났다. 이러한 모형의 결과를 기반으로 일관적인 사고심각도 예측 과정을 통하여 교통사고대응관리 전략 수립에 활용할 수 있다. 본 연구는 국내 기계학습을 활용한 사례가 적은 여건에서 향후 빅데이터 기반의 다양한 기계학습 기법을 활용이 가능함을 제시하고 있다.

• 한국안전학회지
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• 제30권1호
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• pp.94-103
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• 2015

This study analyzes the influence factors on elderly pedestrian accident. Elderly people are easy to be badly injured by car accidents compared to younger people. Therefore, various plans and measures are required to protect elderly pedestrian from accidents. However, pedestrian accidents studies only focused on microscopic factors such as attribute of driver, pedestrian, road design. In order to prevent pedestrian accident and reduce the severity of the accident, not only microscopic factors but macroscopic variables such as urban planning and facility should be considered. In this regard, this study develops an ordered probit model introduced the characteristics of urban facility which were not considered in the previous studies. The result shows that there is higher level of accident severity in such areas as large commercial area, well-developed area with transportation infrastructure service and non-pedestrian safety zone. Thus, various and appropriate countermeasures should be prepared in order that pedestrian accident can be prevented in the areas mentioned above. In addition to the aforementioned variables, it is revealed that other variables including vehicle speed, gender and age of pedestrian, weather condition, type of vehicle, etc. partly affect the severity of pedestrian accident.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.95-100
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• 2023

Due to Traffic accidents people faces health and economical casualties around the world. As the population increases vehicles on road increase which leads to congestion in cities. Congestion can lead to increasing accident risks due to the expansion in transportation systems. Modern cities are adopting various technologies to minimize traffic accidents by predicting mathematically. Traffic accidents cause economical casualties and potential death. Therefore, to ensure people's safety, the concept of the smart city makes sense. In a smart city, traffic accident factors like road condition, light condition, weather condition etcetera are important to consider to predict traffic accident severity. Several machine learning models can significantly be employed to determine and predict traffic accident severity. This research paper illustrated the performance of a hybridized neural network and compared it with other machine learning models in order to measure the accuracy of predicting traffic accident severity. Dataset of city Leeds, UK is being used to train and test the model. Then the results are being compared with each other. Particle Swarm optimization with artificial neural network (PSO-ANN) gave promising results compared to other machine learning models like Random Forest, Naïve Bayes, Nearest Centroid, K Nearest Neighbor Classification. PSO- ANN model can be adopted in the transportation system to counter traffic accident issues. The nearest centroid model gave the lowest accuracy score whereas PSO-ANN gave the highest accuracy score. All the test results and findings obtained in our study can provide valuable information on reducing traffic accidents.

• 한국ITS학회 논문지
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• 제20권4호
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• pp.1-12
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• 2021

최근 코로나 19의 영향으로 이륜자동차 교통사고의 발생은 이전보다 급격히 증가하게 되었고 이륜자동차 사고방지를 위한 다각적인 노력이 필요한 시점이다. 본 연구에서는 XGBoost를 활용하여 최근 10년간 발생한 이륜자동차 교통사고 자료로 사고 심각도에 영향인자를 도출하여 각 영향인자가 주는 영향력을 분석하였다. 전체 변수 중 교통사고 심각도에 영향을 주는 변수는 신호 위반을 하였을 경우가 압도적으로 높았으며, 운전자 연령대가 60대 이상일 경우, 이륜자동차 단독사고일 경우, 중앙선 침범 사고일 경우 순으로 높은 것으로 나타났다. 연구 결과를 바탕으로 이륜자동차의 심각한 교통사고의 방지와 안전관리를 강화하기 위한 합리적인 제도 개편방안을 제시하였다.

• 한국안전학회지
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• 제32권6호
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• pp.150-156
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• 2017

A frozen road surface increases traffic accidents during the winter season. Hence, information on easily-frozen road sections and their specificities are required to prevent traffic accidents. Frozen road surfaces are determined by equipment measuring road surface temperatures. However, there are limitations in investigating the entire road network. Therefore, it is imperative to develop new methods that effectively determine road surface freezing risks. Meteorologically, road surfaces are frozen when the actual temperature cools down to the dew point temperature. Under this condition, there is likely to be frost if relative humidity reaches 100% and frozen road surfaces as the temperature gets lower. Meteorological characteristics give us an alternative to a direct measurement road surface temperature to estimate risks of road surface freezing. Based on the clues, the relationship between severity of traffic accidents and temperature changes is empirically investigated using Paju weather data. The results reveal that as the temperature gets lower and changes in current temperature are relatively small, the severity of traffic accidents become higher. In addition, the same is true when the difference between current temperature and the dew point temperature is relatively small, as it increases possibilities of road surface freezing. Future studies must investigate how current temperature and the dew point temperature affect road surface freezing and thereby establish a time-space scope to estimate possible road surface freezing sections using only weather and road material type data. This would provide invaluable information for predicting and preventing frozen road accidents based on weather patterns.

• 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.

• 한국도로학회논문집
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• 제11권2호
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• pp.195-203
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• 2009

본 연구는 교통사고의 발생 유형과 교통사고 심각도(Severity)와의 관계를 규명함으로써 위험유형을 제시하고, 운전자 특성과 교통사고의 관계를 규명하고자 하였다. 교통사고 유형을 여덟 가지로 세분하고, 결과의 객관성 확보를 위해 안전벨트 착용여부를 추가하여 상해정도와의 관계를 분석하였으며, 위험그룹의 분류를 위한 운전자의 특성은 성별, 차종, 연령 등을 대상으로 하였다. 카테고리 자료의 분석을 위하여 로그-선형 모형 및 로짓 모형을 사용하였다. 분석결과 사고유형과 심각도와의 관계에서는 정면충돌 사고와 앞지르기시, 우회전시 사고가 부상 또는 사망사고에 연루될 가능성이 높았다. 위험그룹 분석에서는 20세 미만의 이륜차 운전자, 41세에서 50세까지의 택시 운전자가 가장 위험한 집단으로 분석되었으며 또한 남자보다는 여자가 승용차와 중형화물 등에 관계되었을 때 더 위험한 것으로 분석되었다. 따라서 교통사고 발생시 인명 피해를 줄이기 위해서는 정면충돌 사고와 앞지르기시, 우회전시 발생하는 사고를 줄일 수 있는 방안이 연구되어야 하고, 교통사고 취약계층으로 분석된 위험그룹에 대한 교통안전 교육 및 단속이 강화되어야 할 것이다.

• 가정∙방문간호학회지
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• 제25권3호
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• pp.182-190
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• 2018

Purpose: This study was conducted to identify and analyze the types, characteristics, and frequency of patient safety accidents among hospitalized children. Methods: The data were collected from patient safety reports for 0-19-year-old patients from the National Health Insurance Corporation (NHIC) from January 1, 2016 through December 31, 2017. Using Excel software, a pivot table was used to classify and analyze the safety incidents, severity frequency, and characteristics of hospitalized child patients. Results: A total of 254 accident cases were reported involving child patients. The types of reports included medication accidents, falls, test errors, and others. Medication accidents accounted for 47.2% of the total reported cases. Regarding the severity of reported risk, there were no complications nor sequelae in 80.4% of the cases. Conclusion: This study is significant for systematically analyzing and reporting data reported about safety accidents among hospitalized children. These results will contribute further to preventing safety accidents in hospitalized children and to creating a desirable patient safety culture.