• Title/Summary/Keyword: Severity of accidents

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Analysis of Neighborhood Environmental Factors Affecting Bicycle Accidents and Accidental Severity in Seoul, Korea (서울시 자전거 교통사고와 사고 심각도에 영향을 미치는 근린환경 요인 분석)

  • Hwang, Sun-Geun;Lee, Sugie
    • Journal of Korea Planning Association
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    • v.53 no.7
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    • pp.49-66
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    • 2018
  • The purpose of this study is to analyze neighborhood environmental factors affecting bicycle accidents and accidental severity in Seoul, Korea. The use of bicycles has increased rapidly as daily transportation means in recent years. As a result, bicycle accidents are also steadily increasing. Using Traffic Accident Analysis System (TAAS) data from 2015 to 2017, this study uses negative binomial regression analysis to identify neighborhood environmental factors affecting bicycle accidents and accidential severity. The main results are as follows. First, bicycle accidents are more likely to occur in commercial and mixed land use areas where pedestrians, bicycle and vehicles are moving together. Second, bicycle accidents are positively associated with road structures such as four-way intersection. In contrast, three-way intersection is negatively associated with serious bicycle accidents. The density of speed hump or street tree is negatively associated with bicycle accidents and accidential severity. This finding indicates the effect of speed limit or street trees on bicycle safety. Fourth, bicycle infrastructures are also important factors affecting bicycle accidents and accidential severity. Bicycle-exclusive roads or bicycle-pedestrian mixed roads are positively associated with bicycle accidents and accidential severity. Finally, this study suggests policy implications to improve bicycle safety.

Discriminant Analysis of Factors Affecting Traffic Accident Severity During Daytime and Nighttime (판별분석을 활용한 주·야간 고속도로 교통사고 영향요인 비교연구)

  • Kim, Kyoungtae;Lee, Soobeom;Choi, Jihye;Park, Sinae;Seo, Geumyeol
    • International Journal of Highway Engineering
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    • v.18 no.3
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    • pp.127-134
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    • 2016
  • PURPOSES : Low visibility caused by dark surroundings at nighttime affects the likelihood of accidents, and various efforts, such as installing road safety facilities, have been made to reduce accidents at night. Despite these efforts, the nighttime severity index (SI) in Korea was higher than the daytime SI during 2011-2014. This study determined the factors affecting daytime and nighttime accident severity through a discriminant analysis. METHODS : Discriminant analysis. RESULTS : First, drowsiness, lack of attention, and lighting facilities affected both daytime and nighttime accident severity. Accidents were found to be caused by a low ability to recognize the driving conditions and a low obstacle avoidance capability. Second, road conditions and speeding affected only the daytime accident severity. Third, failure to maintain a safe distance significantly affected daytime accident severity and nonsignificantly affected nighttime accident severity. The majority of such accidents were caused by rear-end collisions of vehicles driving in the same direction; given the low relative speed difference in such cases, the shock imparted by the accidents was minimal. CONCLUSIONS : Accidents caused by a failure to maintain a safe distance has lower severity than do accidents caused by other factors.

The Effects of Individual Accidents and Neighborhood Environmental Characteristics on the Severity of Pedestrian Traffic Accidents in Seoul (개별 사고특성 및 근린환경 특성이 서울시 보행자 교통사고 심각도에 미치는 영향)

  • Ko, Dong-Won;Park, Seung-Hoon
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.35 no.8
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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.

Crash Severity Impact of Fixed Roadside Objects using Ordered Probit Model (도로변 수직구조물 충돌사고의 심각도 영향요인에 관한 연구)

  • Lim, Joonbeom;Lee, Soobeom;Yun, Dukgeun;Park, Jaehong
    • International Journal of Highway Engineering
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    • v.18 no.6
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    • pp.173-180
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    • 2016
  • OBJECTIVES : Fixed roadside objects are a threat to drivers when their vehicles deviate from the road. Therefore, such roadside objects need to be suitably dealt with to decrease accidents. This study determines the factors affecting the severity of accidents because of fixed roadside objects. METHODS : This study analyzed the crash severity impact of fixed roadside objects by using ordered probit regression as the analysis methodology. In this research, data from 896 traffic accidents reported in the last three years were used. These accidents consisted of sole-car accidents, fixed roadside object accidents, and lane-departure accidents on the national highway of Korea. The accident severity was classified as light injury, severe injury, and death. The factors relating to the road and the driver were collected as independent variables. RESULTS : The result of the analysis showed that the variables of the crash severity impact are the collision location (left side), gender of the driver (female), alcohol use, collision facility (roadside trees, traffic signals, telephone poles), and type of road (rural segments). Additionally, the collision location (left side), gender of the driver (female), alcohol use, collision facility (street trees, traffic signals, telephone poles), and type of road (rural segments), in order of influence, were found to be the factors affecting the crash severity in accidents due to fixed roadside objects. CONCLUSIONS : An alternative solution is urgently required to reduce the crash severity in accidents due to fixed roadside objects. Such a solution can consider the appropriate places to install breakaway devices and energy-absorbing systems.

Prediction Models for the Severity of Traffic Accidents on Expressway On- and Off-Ramps (유입·유출특성을 고려한 고속도로 연결로의 교통사고 심각도 예측모형)

  • Yun, Il-Soo;Park, Sung-Ho;Yoon, Jung-Eun;Choi, Jin-Hyung;Han, Eum
    • International Journal of Highway Engineering
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    • v.14 no.5
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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.

Analysis of Factors influencing Severity of Motorcycle Accidents using Ordered Probit Model (순서형 프로빗모형에 의한 이륜차 사고심각도의 영향요인 분석)

  • Choi, Jung Woo;Kum, Ki Jung
    • International Journal of Highway Engineering
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    • v.16 no.5
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    • pp.143-154
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    • 2014
  • PURPOSES : This study drew factors affecting motorcycle accidents in Seoul by severity using an ordered probit model and aimed to analyze and verify the drawn influence factors. METHODS : As the severity of the accidents could be classified into three types (fatal injury, serious injury and minor injury), this study drew the factors affecting accidents by a comparative analysis employing an ordered probit model, removed the variables that would not secure significance sequentially to construct a model with high explanatory power regarding the factors affecting the severity of motorcycle accidents, and calculated the marginal effect of each factor to understand the degree of each factor's impact on the severity. First, Model 1 put in all variables; Model 2 was constructed by removing the variables of the road surface conditions that could not meet the level of significance (p=0.608); Model 3 was constructed by removing gender variable (p=0.423); and Model 4 was constructed finally by removing age variable (p=0.320). RESULTS : As a result of an analysis, statistically significant variables were time of occurrence, type of accident, road alignment and motorcycle displacement, and it turned out that the impacts on the severity were in the following order: a road alignment of left downhill, the type of motorcycle-to-vehicle accidents and a road alignment of a flatland on the left. The significance of the models was tested using the likelihood ratio, the level of significance and suitability statistics about them, and as a result of the test, the significance level and suitability of the constructed models were all excellent. In addition, the model accuracy indicating the accuracy of a predicted value compared to that of the value actually observed was 70.3% for minor injury; 70.1% for serious injury; and 68.6% for fatal injury, and the overall accuracy was 70.2%, which was very high. CONCLUSIONS : As a result of an analysis of motorcycle accidents in Seoul through the ordered probit model and the marginal effect, it turned out that their severity increased in nighttime accidents as compared to daytime ones and gradually increased in the order of motorcycle-to-vehicle accidents, motorcycle-to-person ones and the ones involving motorcycle only. As a result of an analysis, the severity of accidents in road alignments of left downhill, left flatland and straight downhill increased as compared to those in a road alignment of straight flatland and that the severity of accidents of motorcycles with a displacement larger than 50cc was higher than that of those with a displacement smaller than 50cc.

Evaluation of Severity Measures of Accidents Associated with Industrial Machines and Devices (산업용 기계 및 기구 관련 재해강도 지표의 평가)

  • Choi, Gi Heung
    • Journal of the Korean Society of Safety
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    • v.34 no.2
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    • pp.1-6
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    • 2019
  • This study focuses on the evaluation of severity measures used for accidents associated with industrial machines and devices. In particular, duration of medical treatment, duration of work loss, number of deaths in an individual accident associated with industrial machines and devices are evaluated in various ways to assess the severity of the accident. The number of accidents with work loss of longer than 1 year as the severity measure and the number of accidents as the frequency measure appeared to be the most discriminating information and allow risk assessment based on these frequency and severity measures for grouping of industrial machines and devices. Results of such risk assessment further confirmed the re-classification of industrial machines and devices that are currently subject to safety certification (SC) and self-declaration of conformity (SDC) or selection of those machines and devices that are newly subject to SC and SDC.

Analysis of Road Cross Section Component Affecting Traffic Accident Severity on National Highway (국도상 교통사고 심각도에 영향을 미치는 횡단구성 요소 분석)

  • Park, Jaehong;Yun, Dukgeun
    • Journal of the Korean Society of Safety
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    • v.32 no.6
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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.

Analysis of the Impact Factors of Peak and Non-peak Time Accident Severity Using XGBoost (XGBoost를 활용한 첨두, 비첨두시간 사고 심각도 영향요인 분석)

  • Je Min Seong;Byoung Jo Yoon
    • Journal of the Society of Disaster Information
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    • v.20 no.2
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    • pp.440-447
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    • 2024
  • Purpose: The number of registered vehicles in Korea continues to increase. As traffic volume increases gradually due to improved quality of life, the severity of accidents is expected to increase and congestion problems are also expected. Therefore, it is necessary to analyze the accident factors of pointed traffic accidents and non-pointed traffic accidents. Method: The severity of the apical and non-pointed traffic accidents in Incheon Metropolitan City is analyzed by dividing them into apical and non-pointed traffic accidents to investigate the factors affecting the accident. XGBoost machine learning techniques were applied to analyze the severity of pointed and non-pointed traffic accidents and visualized as plot through the results. Result: It was analyzed that during non-peak hours, such as the case of the victim's vehicle type at peak times, the victim's vehicle type and construction machinery are variables that increase the severity of the accident. Conclusion: It is meaningful to derive the seriousness factors of apical and non-pointed accidents, and it is hoped that it will be used to reduce congestion costs by reducing the seriousness of accidents in the case of apical and non-pointed in the future.

Characteristics of Traffic Accidents on Highways: An Analysis Based on Patients Treated at a Regional Trauma Center

  • Lee, Sung Yong;Sun, Kyung Hoon;Park, Chan Yong;Kim, Tae Hoon
    • Journal of Trauma and Injury
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    • v.34 no.4
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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).