• Title/Summary/Keyword: 차대사람 사고

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Factor Analysis of Accident Types on Urban Street using Structural Equation Modeling(SEM) (구조방정식모형을 활용한 단속류 시설의 교통사고 유형별 유발요인 분석)

  • Kim, Sang-Rok;Bae, Yun-Gyeong;Jeong, Jin-Hyeok;Kim, Hyeong-Jin
    • Journal of Korean Society of Transportation
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    • v.29 no.3
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    • pp.93-101
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    • 2011
  • In 2008, Korea has observed total 215,822traffic accidents Although the number has decreased since then, the crash rate is still higher than those of other advanced countries. In particular, high rate of pedestrian accidents occurred on urban streets is recognized as a serious problem. The previous studies, however, are not entirely considerate of accident factors by accident type. Inspired by the fact, this study analyzes factors affecting traffic accident by accident type. Using the accident data collected on urban streets in Seodaemun-gu, this paper classifies the accidents into two groups (i.e., vehicle-vs-vehicle and vehicle-vs-person crashes), and analyzes relationships between severity and exogenous variables. For the analysis, Structural Equation Modeling (SEM) is employed to estimate relationships among exogenous factors of traffic accident by each type on urban streets. The resulting model reveals that roadway related factors are highly correlated with the severity of vehicle-vs-vehicle crashes whereas environment factors are with vehicle-vs-person crashes.

Effects of Road Networks on Vehicle-Pedestrian Crashes in Seoul (도로네트워크 특성과 차대사람 사고발생 빈도간의 관련성 분석 : 서울시를 사례로)

  • Park, Sehyun;Kho, Seoung-Young;Kim, Dong-Kyu;Park, Ho-Chul
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.2
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    • pp.18-35
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    • 2020
  • Many human, roadway, and vehicle factors affect vehicle-pedestrian crashes. Especially, the roadway factors are easily defined and suitable for suggesting countermeasures. The characteristics of the road network are one of the roadway factors. The road network significantly influences behaviors and conflicts of drivers and pedestrians. A metropolitan city such as Seoul contains various types of road networks, and crash prevention strategy considering characteristics of the road network is required. In this study, we analyze the effects of road networks on vehicle-pedestrian crashes. In the study, high order road ratio, intersection ratio, high-low intersection ratio are considered as road network variables. Using Geographically Weighted Poisson Regression, crash frequencies in Dongs of Seoul are analyzed based on the road network variable as well as socioeconomic variables. As a result, Dongs are grouped by coefficient signs, and each group is suggested about improvement directions considering conflict situations.

The Study on the Severity of Children Traffic Accident using Ordinal Logistic Regression Analysis (순서형 로지스틱 회귀분석을 이용한 어린이 사고심각도 분석 연구)

  • Yoon, Byoung-Jo;Ko, Eun-Hyeck;Yang, Sung-Ryong
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2016.11a
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    • pp.259-260
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    • 2016
  • 어린이의 경우 다른 연령층에 비해 신체적, 정신적으로 완성되지 못하여 교통사고의 가능성이 높으며, 특히 전국의 어린이 교통사고는 점진적으로 감소 추세이나 인천의 어린이 교통사고는 감소하다가 다시 증가 추세에 들어선 실정이다. 따라서 본 연구의 목적은 어린이 교통사고 심각도에 영향을 미치는 주요 요인들을 발견하고 제시하고자 하였다. 순서형 로지스틱 회귀분석을 활용하여 순서척도인 반응변수에 대한 설명변수의 오즈(Odds)를 확인하고자 하였으며 안전운전불이행, 차대사람(횡단중), 차대차(측면직각충돌)사고가 유의한 결과로 나타났다. 안전운전불이행으로 인한 사망사고와 기타사고의 오즈차이는 1.35배, 측면직각충돌로 인한 사망사고와 기타사고의 오즈차이는 1.76배 증가하는 것으로 나타났고, 횡단중인 경우에는 오히려 사망 위험도의 오즈값이 0.58배로 감소하는 것으로 나타났다.

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보행자 안전을 고려한 자동차 설계 방안

  • Kim, Tae-Ho;Koh, Jae-Ho;Son, Wan-Il;Kang, Kyung-Sik
    • Proceedings of the Safety Management and Science Conference
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    • 2007.04a
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    • pp.223-234
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    • 2007
  • 자동차를 설계할 때에는 예술적, 기술적으로 뛰어나다 하더라도 공학적으로 실현이 가능하여야 한다. 또한 비용이라든가 품질도 중요한 고려사항이다. 하지만 이것들 보다 자동차 설계에서 더욱더 중요시되는 것은 안전이다. 사고 시 사람의 생명을 최대한 안전하게 보호할 수 있는가이다. 이번 연구는 'Design for Safety' 중에서도 보행자 안전을 고려한 자동차 설계에 관해 연구하고자 한다. 2005년 교통사고 통계에 따르면 차대사람의 사고발생건수는 총 46,594건에 사망자 2,457명 부상자 47,282명이다. 이는 한 해 전체 교통사고 발생건수에 21.8%를 차지하고 있다. 본 연구는 자동차 사고 중 보행자와 차량의 사고 유형과 상해부위를 파악하여 사례를 중심으로 살펴본 후 이를 자동차 설계에 반영하는 방법에 대한 연구이다.

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

  • Kim, Seunghoon;Lym, Youngbin;Kim, Ki-Jung
    • Journal of Digital Convergence
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    • v.19 no.4
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    • pp.25-31
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    • 2021
  • Moving toward an aged society, traffic accidents involving elderly drivers have also attracted broader public attention. A rapid increase of senior involvement in crashes calls for developing appropriate crash-severity prediction models specific to senior drivers. In that regard, this study leverages machine learning (ML) algorithms so as to predict the severity of vehicle-pedestrian collisions induced by elderly drivers. Specifically, four ML algorithms (i.e., Logistic model, K-nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM)) have been developed and compared. Our results show that Logistic model and SVM have outperformed their rivals in terms of the overall prediction accuracy, while precision measure exhibits in favor of RF. We also clarify that driver education and technology development would be effective countermeasures against severity risks of senior driver-induced collisions. These allow us to support informed decision making for policymakers to enhance public safety.

Accident Models of Circular Intersections by Type in Korea (사고유형에 따른 원형교차로 사고모형)

  • Han, Su-San;Kim, Kyung-Hwan;Park, Byung-Ho
    • International Journal of Highway Engineering
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    • v.13 no.3
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    • pp.103-110
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    • 2011
  • This study deals with the traffic accidents by type. The objectives are to analyze the characteristics of 2 accident types, and to develop the models by type. In pursuing the above, this paper gives particular attentions to testing the differences between by type two groups, and developing the models (Poisson and negative binomial regressions) using the data of domestic circular intersections. The main results are as follows. First, the number of accidents in vehicle vehicle was analyzed to account for about 73.41% of total and to be higher than vehicle people. Second, two Poisson models and two negative binomial models which were all statistically significant were developed using vehicle people accidents and vehicle vehicle accidents as dependant variables. Finally, the traffic volume as common variable was selected in the models, and right-turn slip lane, speed hump, the number of driveways, the number of pedestrian crossings as specific variables of the models were selected.

Building bicycle management system using Blockchain (블록체인을 활용한 자전거 관리 시스템 구축)

  • An, Kyu-hwang;Seo, Hwajeong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.8
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    • pp.1139-1145
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    • 2018
  • According to the prosecutors' office's statistics for 2014, 53% of a bicycle users have experienced theft. The reason for the high rate of bicycle stolen in Korea is that there is no bicycle management system. This is because they do not use bicycle numbers to manage bikes like cars do. Most people do not know if they have a VIN(Vehicle Identification Number) on their bike. If the buyer registers the bicycle in the bicycle management blockchain system, anyone can view the information registered in the chain, so that if the bicycle number is filled in, the bicycle can be identified. In addition, when an accident occurs, blockchain will record what kind of equipment it is replacing, like an automobile, to manage all the information about the bicycle. In this way, consumers can inquire whether they have a history of accident when they make a second-hand transaction. In this paper, we propose a method to construct bicycle management system using bicycle VIN.

A Study on the Application of Accident Severity Prediction Model (교통사고 심각도 예측 모형의 활용방안에 관한 연구 (서해안 고속도로를 중심으로))

  • Won, Min-Su;Lee, Gyeo-Ra;O, Cheol;Gang, Gyeong-U
    • Journal of Korean Society of Transportation
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    • v.27 no.4
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    • pp.167-173
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    • 2009
  • It is important to study on the traffic accident severity reduction because traffic accident is an issue that is directly related to human life. Therefore, this research developed countermeasure to reduce traffic accident severity considering various factors that affect the accident severity. This research developed the Accident Severity Prediction Model using the collected accident data from Seohaean Expressway in 2004~2006. Through this model, we can find the influence factors and methodology to reduce accident severity. The results show that speed limit violation, vehicle defects, vehicle to vehicle accident, vehicle to person accident, traffic volume, curve radius CV(Coefficient of variation) and vertical slope CV were selected to compose the accident severity model. These are certain causes of the severe accident. The accidents by these certain causes present specific sections of Seohaean Expressway. The results indicate that we can prevent severe accidents by providing selected traffic information and facilities to drivers at specific sections of the Expressway.

Forecasting of Probability of Accident by Analizing the Traffic Accident Data : Main Intersections on Arterial Roads in Busan (교통사고 데이터분석을 통한 교통사고 위험도 산정 : 부산시 주간선도로 주요교차로를 대상으로)

  • Jung, Kun Young;Bae, Sang Hoon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.37 no.1
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    • pp.111-117
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    • 2017
  • The purpose of forecasting the traffic accident is to reduce the traffic accident. Therefore, the goal of this study is to provide severity of the accident by Forecasting of Probability of Accident. In Korea, accident data are distributed to the public via internet that includes numbers of accident and fatality as well. And crude level of accident severity in accordance with weather information for metropolitan city level are available by weekly. However, It can not reflect personal needs at specific origin of the travel for a certain traveller. This study aims to consider 68 major intersections with precipitation data, and eventually introduces link based accident severity. In estimating the accident severity both dynamic data such as drivers' characteristics, driving conditions and static data such as geometry of road, intersection characteristics are considered. Also, we identifies accident severity according to the accident type - 'vehicle to vehicle,' 'vehicle to person.' Finally, the outcomes of this study suggests taylor-made accident severity information for a specific traveller for a certain route.

A study on the factor analysis by grade for highway traffic accident (고속도로 교통사고 심각도 등급별 요인분석에 관한 연구)

  • Lee, Hye-Ryung;Kum, Ki-Jung;Son, Seung-Neo
    • International Journal of Highway Engineering
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    • v.13 no.3
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    • pp.157-165
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    • 2011
  • With respect to the trend of highway traffic accident, highway accident is in decline, whileas, the fatality is on an increasing trend. Thus, many efforts to decrease highway traffic accidents and improve the safety, are required. In particular, in case of highway, the management standard by grade for accident black spot is designated. Thus, investing the effect factors by grade for highway traffic accident is required in detail. Thus, in this study, the factors affecting the traffic accidents among the environmental factors based on the graded data for the accident black spot in the applicable section targeting the Seoul-Pusan Express Highway, were reviewed; accident forecasting model which would analyze the characteristics of the accidents for determining the accident grade, was developed. As a result of establishing a model by using Quantification Theory of Type II, considering the characteristics of the dependent and independent variables based on the geometric structure, 'the fixed variable' among the variables relating to the accident, for the variables influencing over the accident grade, 'the type of vans, a chassis and people', 'the trailers, special vehicles and chassis people' and 'the negligence of watching and cloudy weather' were analyzed as common factors, in case of 'horizontal alignment', 'longitudinal slope' and, 'barricade' respectively.