• 대한건축학회논문집:계획계
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• 제35권8호
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• pp.101-109
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• 2019

Korea's transportation paradigm is shifting from a vehicle-oriented transportation plan to a pedestrian-friendly environment that emphasizes walking safety. However, the level of pedestrian traffic accidents in Korea is still high and serious. The purpose of this study is to investigate factors affecting the severity of pedestrians traffic accidents using the multilevel logistic regression model based on 2015-2017 pedestrian accidents data provided by the Traffic Accident Analysis System(TAAS). The main results of the multilevel logistic regression model showed that 89% of pedestrian traffic accidents in Seoul were explained by individual characteristics such as drivers and pedestrians, and 11% were explained by neighborhood environmental characteristics. The results are as follows : In the individual characteristics such as pedestrians and drivers, the older the pedestrians and the drivers, the higher the traffic accident severity. The severity of traffic accidents was high when the pedestrians were female and the drivers were male. In the case of accident types, traffic accidents were more serious in the cases of heavy vehicles, inclement weather, and occurring at intersections and crosswalks. The results of the neighborhood environmental characteristics are as follows. The intersection density and the crosswalk density tended to reduce the severity of traffic accidents. On the other hand, the traffic light density and the school zones were founded to related to the higher level of traffic accident severity. This study suggests that both individual and neighborhood environmental characteristics should be considered together to prevent and reduce the severity of pedestrian traffic accidents.

• 한국도로학회논문집
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• 제14권5호
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• pp.101-111
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• 2012

PURPOSES: Because expressway ramps are very complex segments where diverse roadway design elements dynamically change within relatively short length, drivers on ramps are required to drive their cars carefully for safety. Especially, ramps on expressways are designed to guarantee driving at high speed so that the risk and severity of traffic accidents on expressway ramps may be higher and more deadly than other facilities on expressways. Safe deceleration maneuvers are required on off-ramps, whereas safe acceleration maneuvers are necessary on onramps. This difference in required maneuvers may contribute to dissimilar patterns and severity of traffic accidents by ramp types. Therefore, this study was aimed at developing prediction models of the severity of traffic accidents on expressway on- and off-ramps separately in order to consider dissimilar patterns and severity of traffic accidents according to types of ramps. METHODS: Four-year-long traffic accident data between 2007 and 2010 were utilized to distinguish contributing design elements in conjunction with AADT and ramp length. The prediction models were built using the negative binomial regression model consisting of the severity of traffic accident as a dependent variable and contributing design elements as in independent variables. RESULTS: The developed regression models were evaluated using the traffic accident data of the ramps which was not used in building the models by comparing actual and estimated severity of traffic accidents. Conclusively, the average prediction error rates of on-ramps and offramps were 30.5% and 30.8% respectively. CONCLUSIONS: The prediction models for the severity of traffic accidents on expressway on- and off-ramps will be useful in enhancing the safety on expressway ramps as well as developing design guidelines for expressway ramps.

• 한국안전학회지
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• 제23권2호
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• pp.65-71
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• 2008

As the interest in traffic safety has been increasing recently, social movement is being made to reduce the number of traffic accidents and the view on improving the mobility of the existing roads is being converted into on establishing traffic safety as a priority. The increase of traffic accidents related to an intersection in a state that traffic accidents are decreasing overall may suggests the necessity to investigate the specific causes. In addition, we have to consider them when establishing the measures against traffic accidents in a intersection by investigating and analyzing the influences and factors that may affect traffic accidents. To induce the accident severity model, we collected the factors that affect accidents and then applied the Poisson Regression Model among nonlinear regression analysis by verifying the distribution of variables. As a result of the analysis, it turned out that the volume of traffic on main roads, the right turn ratio on sub-roads, the number of ways out on sub-roads, the number of exclusive roads for a left turn, the signals for a right turn on main roads, and an intersect angle were the factors that affect the accident severity.

• Journal of Trauma and Injury
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• 제34권4호
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• pp.263-269
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• 2021

Purpose: There have been increasing concerns about serious traffic accidents on highways. The purpose of this study was to analyze factors affecting traffic accidents on highways and the severity of the resulting injuries. Methods: This retrospective study was conducted at a regional trauma center. We reviewed 594 patients who had been in 114 traffic accidents on highways from January 2018 to June 2020. We collected demographic data, clinical data, accident-related factors, and meteorological data (weather and temperature). Results: Environmental risk factors were found to be significantly associated with the incidence of traffic accidents on highways. Injury severity and the death rate were higher in sedans than in any other type of vehicle. Tunnels were the most common location of accidents, accounting for 47 accidents (41.2%) and 269 injured patients (45.3%). The injury severity of individuals riding in the driver's seat (front seat) was high, regardless of vehicle type. Three meteorological risk factors were found to be significantly associated with traffic accidents: rainy roads (odds ratio [OR] 2.08; 95% confidence interval [CI] 1.84-3.29; p=0.01), icy or snowy roads (OR 5.12; 95% CI 2.88-7.33; p<0.01), and foggy conditions (OR 2.94; 95% CI 2.15-4.03; p<0.05). Conclusions: The injury severity of patients was affected by seat position and type of vehicle, and the frequency of accident was affected by the location. The incidence of traffic accidents was strongly influenced by meteorological conditions (rain, snow/ice, and fog).

• 한국안전학회지
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• 제28권6호
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• pp.84-89
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• 2013

The main causes of traffic accidents can be classified by 3 factors - human error, vehicle deficiency and road environmental problem and most accidents occurs not only 1 factor but combination of 2 or 3-factors. Among these factors, road environmental factor is the most important factor due to influence the behavior of cars and road users and road environmental factor affects 30% of total accidents approximately. The 5 years traffic accidents data analyzed to verify the accidents severity on Korea National Highways. In order to analyze the severity, Ordered Probit Model was used. As a independent variables of this model the number of lane, neighbor road environments, sight distance, vertical grade, lane width, shoulder width and traffic volume were used and as a dependent variables the minor injuries, serious injuries and fatalities were used. Research results shows that sight distance and lane width are identified as significant factors for the traffic accident severity and lesser sight distance and lane width shows greater traffic accident severity.

• 한국안전학회지
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• 제32권6호
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• pp.143-149
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• 2017

According to traffic accidents statistics, the number of fatalities, injuries and the rate of increase of traffic accidents have been decreasing over last 5-years. The fatality rate is 1.9 for total accidents but the fatality rate for single vehicle accidents shows a 7.9, which is 4 times greater than the average for all accidents. Single vehicle accidents, usually occur as a vehicle impacts a fixed objects on the roadside as the vehicle runs-off from the road. However, few researches have been conducted considering the accident severity of single vehicle accidents which impact to the fixed objects on the road. The single vehicle accident is directly related to the composition of road cross section, (since it is the required the minimum width of a road for all run-off-the-road vehicles to recover or come to a safe stop). Therefore, this study analyzes the influence of road cross section on traffic accidents to find out the severity of single vehicle accident. To analyze the road elements which are related to the accident severity, the Ordered Probit Model was used. As variables, the element of road cross section such as the radius(m), vertical curve(%), cross sectional grade(%), road width(m). number of climbing lane, median, and curb, were used (as was the 3-years of accidents data). This study found out that cross slope(%), road width(m), and the number of climbing lane are related to the severity of accident. The result of this study could be expected to improve the road safety and to be used as the base data for further road safety research.

• 한국재난정보학회 논문집
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• 제20권2호
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• pp.440-447
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• 2024

연구목적: 국내의 차량 등록 대수는 계속 증가하고 있다. 삶의 질 향상으로 인한 교통량 또한 점진적으로 증가하므로 사고 심각도가 증가 및 혼잡문제 또한 야기될 것으로 예상된다. 따라서, 첨두 교통사고와 비첨두 교통사고의 사고 요인을 분석할 필요가 있다고 판단된다. 연구방법:인천광역시의 첨두 및 비첨두 교통사고의 심각도를 첨두와 비첨두로 나누어 분석하여 사고에 영향을 미치는 요인을 알아보고자 한다. XGBoost 머신러닝 기법을 적용하여 첨두 및 비첨두 교통사고 심각도를 분석하였으며 결과를 통하여 plot으로 시각화하였다. 연구결과:첨두시 피해운전자 차종_승합인 경우 등 비 첨두시는 피해운전자 차종_건설기계 등이 사고 심각도를 높이게 되는 변수인 것으로 분석되었다. 결론: 첨두와 비첨두 사고 심각도의 요인을 도출한 것에 의의가 있고 추후 첨두 및 비첨두시의 사고 심각도를 낮추고 국내 교통의 혼잡 요인을 분석하여 혼잡 비용을 줄일 수 있는 것에 활용되기를 바란다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제10권8호
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• pp.301-310
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• 2021

TATI 모델이란 Traffic Accident Text to RGB Image 모델로, 교통사고 심각 정도 예측을 위한 본 논문에서 제안하는 방법론이다. 교통사고 치사율은 매년 감소하는 추세이나 OECD 회원국 중 하위권에 속해있다. 교통사고 치사율 감소를 위해 많은 연구들이 진행되었고, 그 중에서 교통사고 심각 정도를 예측하여 발생 및 치사율을 줄이기 위한 연구가 꾸준하게 진행되고 있다. 이와 관련하여 최근에는 통계 모델과 딥러닝 모델을 활용하여 교통사고 심각 정도 예측을 하는 연구가 활발하다. 본 논문에서는 교통사고 심각 정도를 예측하기 위해서 교통사고 데이터를 컬러 이미지로 변환하고, CNN 모델을 통해 이를 수행한다. 성능 비교를 위해 제안하는 모델과 다른 모델들을 같은 데이터로 학습시키고, 예측결과를 비교하는 실험을 진행했다. 10번의 실험을 통해 4개의 딥러닝 모델의 정확도와 오차 범위를 비교하였다. 실험 결과에 따르면 제안하는 TATI 모델의 정확도가 0.85로 가장 높은 정확도를 보였고, 0.03으로 두 번째로 낮은 오차 범위를 보여 성능의 우수성을 확인하였다.

• 대한교통학회지
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• 제12권1호
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• pp.137-149
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• 1994

The objective of study is to evaluate the effect of speed control hump on traffic operation and accidents. Three sites were investigated for the change of traffic accidents before and after the hump installation. Vehicle speeds approaching the hump were also analyzed. The study revealed that not only the number of traffic accidents but also the accident severity were significantly reduced by the installation of hump. Further, different types of traffic accidents with lower severity were observed after the hump installation. For the effect of speed reduction by hump, it was found that the speeds observed at 15m upstream of hump were in the range of 36~50 percent of approaching speeds which were not affected by (ie, without) the hump. Economic analysis of hump installation showed the benefit-cost ratio of 4.3 and 11.2 at two sites. Further analysis revealed that the benefit by the accident reduction exceeds the cost by speed reduction and installation capital if AADT is below 43,150 vehicles on two lane highways. It is recommended from the study that humps should be considered on two lane highways of high accident locations for excessive speeds to reduce traffic accidents and severity.

• Journal of Trauma and Injury
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• 제35권4호
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• pp.240-247
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• 2022

Purpose: Studies on the relationship between obesity and injuries, especially those sustained in pedestrian traffic accidents, are lacking. We aimed to assess the effects of obesity on the severity of injury at the time of admission to the emergency room in patients who experienced pedestrian traffic accidents. Methods: This study included trauma patients registered in the Korean Trauma Database from July 1, 2018 to December 31, 2020, whose mechanism of injury was pedestrian traffic accidents and who were treated at a single institution. Those aged below 15 years were excluded. Patients were assigned to nonobese and obese groups based on a body mass index of 25 kg/m². An Injury Severity Score of 25 or greater was considered to indicate a critical injury. Results: In total, 679 cases of pedestrian traffic accidents were registered during the study period, and 543 patients were included in the final analysis. Of them, 360 patients (66.3%) and 183 patients (33.7%) were categorized as nonobese and obese, respectively. The median age was significantly higher in the nonobese group than in the obese group (60 vs. 58 years). Multivariate analysis demonstrated that the odds ratio for critical injury in obese patients was 1.59 (95% confidence interval, 1.01-2.48) compared with nonobese patients. Conclusions: Obesity affected the likelihood of sustaining severe injuries in pedestrian traffic accidents. Future studies should analyze the effects of body mass index on the pattern and severity of injuries in patients with more diverse injury mechanisms using large-scale data.