• Title/Summary/Keyword: 심각도 모형

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Data Mining for Road Traffic Accident Type Classification (데이터 마이닝을 이용한 교통사고 심각도 분류분석)

  • 손소영
    • Proceedings of the KOR-KST Conference
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    • 1998.10a
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    • pp.373-381
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    • 1998
  • 본 연구는 교통사고 심각도와 관련된 중요변수를 찾고 이들 변수를 바탕으로 신경망, Decision Tree, 로지스틱 회귀분석을 이용하여 사고 심각도 분류 예측모형을 추정하였다. 다수의 범주형 변수로 이루어진 교통사고 통계원표상의 설명변수 들로부터 사고 심각도변화에 영향력 있는 변수선택을 위하여 $X^2$ 독립성 검정과 Decision Tree를 이용하였고, 선택된 변수들은 신경망과 로지스틱 회귀분석의 기초로 이용되었다. 분석결과 세가지기법간에 분류정확도에는 유의한 차이가 없는 것으로 나타났다. 그러나 decision Tree가 설명변수 선택능력과 분석수행시간, 사고 심각도 결정요인 식별의 용이함 측면에서 범주형 종속변수인 사고 심각도의 분석에 적합합 것으로 보이며 사고 심각도에는 보호장구가 가장 큰 영향을 미치는 것으로 재입증되었다.

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njury Severity Analysis of Cyclists in Two Wheeler to Taxi Crashes: An Application of Vehicle Black Box Data in Incheon, Korea (차량 블랙박스 자료를 활용한 택시-이륜차 사고에서의 이륜차 이용자 사고 심각도 분석)

  • Kim, Seonjung;Chung, Younshik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.38 no.6
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    • pp.917-923
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    • 2018
  • In recent, technological advancement including a vehicle black box (VBB) has led to reducing such underreporting issues and errors of crash data. The objective of this study is to analyze the injury severity of cyclists on taxi-to-two wheeler crashes based on the accurate crash data collected from the VBB in taxi. This study defined the two wheelers as bicycle and motorcycle. To perform this study, we used the VBB data collected from taxis operating in Incheon, South Korea for a two-year period (2010-2011). An ordered probit model was applied to analyze the injury severity in crashes. As a result, new injury severity factors were found: increase of the crash speed of taxi, damage of crash-involved vehicles (i.e., taxi and/or two wheeler), not standing of cyclists after crash, and second or third impact of cyclists after first crash.

The Development of Discriminant Models for Subway Inner Noise (지하철 차내 소음 판별모형 개발에 관한 연구 - 서울시 지하철 5호선을 중심으로 -)

  • Kim, Tae-Ho;Do, Hwa-Yong;Won, Jai-Mu;Yoon, Sang-Hoon
    • Journal of the Korean Society for Railway
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    • v.10 no.6
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    • pp.678-684
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    • 2007
  • This research has defined the factors of noise in cars during subway train services, which is surfacing as a new environmental trouble. It shows additional accomplishment of a discerning analysis on the standard of noise regulation as well as its seriousness. According to the Enforcement Regulations for Noise and Vibration under the Ministry of Environment and its standard noise regulation figure 70dB, we divided two groups of which train noise figures are over and under 70dB respectively, and used their 359 results about noise, geometric structures and operation elements, for this analysis. The results and suggestions are following. First of all, when we discern the seriousness of noise in a train, the track type has mattered in geometric structure and the velocity in operation elements. Therefore, when we construct subway from now on, we should take the track type in consideration and establish plans to keep proper speed in respect of operation. Secondly, the established discernment model in this research can be used in making alternative plans or improvement of subway trains hereafter, showing relatively high accuracy of estimation. Consequently, the readjustment of geometric structure and operation elements is needed, not to make it over the regulation standard of noise in case the noise in train is serious. The discriminant model of this research can be used as elementary material for comfortable and safe subway trains, making the estimation of noise seriousness possible.

Analysis of Bus Accident Severity Using K-Means Clustering Model and Ordered Logit Model (K-평균 군집모형 및 순서형 로짓모형을 이용한 버스 사고 심각도 유형 분석 측면부 사고를 중심으로)

  • Lee, Insik;Lee, Hyunmi;Jang, Jeong Ah;Yi, Yongju
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.3
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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.

Risk Factors Affecting the Injury Severity of Rental Car Accidents in South Korea : an Application of Ordered Probit Model (순서형 프로빗 모형을 이용한 렌터카 사고 심각도 영향요인 분석)

  • Kwon, Yeong min;Jang, Ki tae;Son, Sang hoon
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.3
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    • pp.1-17
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    • 2018
  • Over the past five years (2010-2014), the total number of traffic accidents has decreased from 226,878 to 223,552 with decrease of 0.37 percent each year. The death toll has also decreased from 5,505 to 4,762. However, the number of rental car accidents and fatalities has been steadily increased. Despite of its growth, no previous study has been conducted on rental car accident severity. This study analyzed data of 18,050 rental car accidents in South Korea collected from 2010 to 2014 and then processed in order to identify which factors could affect the accident severity. Seventeen factors related to rental car accident severity were grouped into four categories: driver, vehicle, roadways and environment. As a result of the ordered probit model analysis, fourteen variables excluding age, intersection, and day of week were found to affect the severity of rental car accidents. The results of the study summarized as follows. First of all, violation of traffic regulations such as speeding increase the severity of rental car accidents. Secondly, rental accident severity is higher at curved sections of complicated roadway, which the driver's field of view is impaired. The results of this study can be used to reduce the severity of rental car accidents in transportation safety.

The Determination of Risk Group and Severity by Traffic Accidents Types - Focusing on Seoul City - (교통사고 위험그룹 및 사고유형별 심각도 결정 연구 - 서울시 중심 -)

  • Shim, Kywan-Bho
    • International Journal of Highway Engineering
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    • v.11 no.2
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    • pp.195-203
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    • 2009
  • This research wished to risk type and examine closely driver special quality and relation of traffic accidents by occurrence type of traffic accidents and traffic accidents seriousness examine closely relation with Severity. Fractionate traffic accidents type by eight, and driver's special quality for risk group's classification did to distinction of sex, vehicle type, age etc. analyzed relation with injury degree adding belt used putting on availability for security the objectivity with wave. Used log-Linear model and Logit model for analysis of category data. A head-on collision and overtaking accident, right-turn accident are high injury or death accident and possibility to associate in relation with accident type and seriousness degree. In risk group analysis The age less than 20 years in motor-cycle driver, taxi driver in 41 years to 50 years old are very dangerous. The woman also was construed to the more risk group than man from when related to car, mini-bus, goods vehicle etc. Therefore, traffic safety education and Enforcement for risk group that way that can reduce accident that produce to reduce a loss of lives at traffic accidents appearance a head-on collision and overtaking accidents, right-turn accidents should be studied and as traffic accidents weakness class may have to be solidified.

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Classification and Prediction of Highway Accident Characteristics Using Vehicle Black Box Data (블랙박스 영상 기반 고속도로 사고유형 분류 및 사고 심각도 예측 평가)

  • Junhan Cho;Sungjun Lee;Seongmin Park;Juneyoung Park
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.6
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    • pp.132-145
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    • 2022
  • This study was based on the black box images of traffic accidents on highways, cluster analysis and prediction model comparisons were carried out. As analysis data, vehicle driving behavior and road surface conditions that can grasp road and traffic conditions just before the accident were used as explanatory variables. Considering that traffic accident data is affected by many factors, cluster analysis reflecting data heterogeneity is used. Each cluster classified by cluster analysis was divided based on the ratio of the severity level of the accident, and then an accident prediction evaluation was performed. As a result of applying the Logit model, the accident prediction model showed excellent predictive ability when classifying groups by cluster analysis and predicting them rather than analyzing the entire data. It is judged that it is more effective to predict accidents by reflecting the characteristics of accidents by group and the severity of accidents. In addition, it was found that a collision accident during stopping such as a secondary accident and a side collision accident during lane change act as important driving behavior variables.

Identification of Factors Affecting the Crash Severity and Safety Countermeasures Toward Safer Work Zone Traffic Management (공사구간 교통관리특성을 고려한 고속도로 교통사고 심각도 영향요인 분석 및 안전성 증진 방안)

  • YOON, Seok Min;OH, Cheol;PARK, Hyun Jin;CHUNG, Bong Jo
    • Journal of Korean Society of Transportation
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    • v.34 no.4
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    • pp.354-372
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    • 2016
  • This study identified factors affecting the crash severity at freeway work zones. A nice feature of this study was to take into account the characteristics of work zone traffic management in analyzing traffic safety concerns. In addition to crash records, vehicle detection systems (VDS) data and work zone historical data were used for establishing a dataset to be used for statistical analyses based on an ordered probit model. A total of six safety improvement strategies for freeway work zones, including traffic merging method, guidance information provision, speed management, warning information systems, traffic safety facility, and monitoring of effectiveness for countermeasures, were also proposed.