• Title/Summary/Keyword: 교통사고심각도

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A Study on the Analysis of Driver Behavior in Traffic Accidents using Driving Video Recorder (차량용 영상기록장치를 통한 운전자 행태에 따른 교통사고분석에 관한 연구)

  • CHA, Yun-Chul;Yoon, Byoung-Jo;Park, Hyung-Geun;Yang, Sung-Ryong
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2015.11a
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    • pp.197-198
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    • 2015
  • 우리나라의 자동차 역사는 주요 선진국에 비해 60년 정도 짧지만 자동차와 일어나는 교통사고의 발생률이나 심각도를 고려한다면 교통사고를 줄이기 위한 여러 가지 원인을 분석해 보는 것이 중요하다. 본 연구는 방송프로그램에 방송한 차량용 영상기록장치(VDR) 제보영상을 통해 다양한 교통사고의 원인을 수집하여 운전자의 행태를 분석하여 교통사고를 발생을 감소 시킬 수 있는 방안을 제시하는 연구목적이다. 방송된 차량용 영상 전체 1,262건에 대해 운전자 행태 분석을 실시하여 DB를 구축하고 이를 교통사고 분석 시스템 TAAS 통계를 비교 분석 결과 전체 1,262건 중 노면상태가 건조 할 때가 1,153건, 기상상태가 맑을 때 1,176건, 주야별 운전시 주간이 1,0,13건으로 높게 분석되었다. 또한 사고유형으로는 차대차 860건이 68.1%로 높게 분석 되었다. 따라서 운전에 장애가 되는 요소가 없는 경우 운전자 개인이 과속과 전방주시 태만이 발생할 가능성이 높으므로 운전자들에 대한 교육을 통해 의식개혁이 필요하다.

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Influence of Urban Built Environment on Severity of PM-Pedestrian Accidents in Seoul (서울시 PM 대 보행자 교통사고 심각도에 대한 도시건조환경의 영향)

  • Songhyeon Shin;Sangho Choo;Danbi Lim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.4
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    • pp.114-131
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    • 2023
  • Personal Mobility (PM)-related accidents have increased rapidly since PM use was activated. In response to the increase in these accidents, the government strengthened regulations for PM users on May 13, 2021. The number of the accidents in which the PM user was a victim decreased significantly. In contrast, the increasing number of accidents in which PM user was the offender did not decrease significantly. In most of these accidents, the PM user was the offender who crashed into pedestrians. Hence, the safety of pedestrians is threatened. Therefore, this study analyzed the factors, such as the regulations, urban built environment, and personal characteristics, affecting the severity of PM-pedestrian accidents by focusing on PM-pedestrian crashes. This study analyzed the PM-pedestrian accidents in Seoul from 2020 to 2021 using binary logistic regression model. Through these results, this study proposed the policy implications.

Development of a Traffic Accident Prediction Model for Urban Signalized Intersections (도시부 신호교차로 안전성 향상을 위한 사고예측모형 개발)

  • Park, Jun-Tae;Lee, Soo-Beom;Kim, Jang-Wook;Lee, Dong-Min
    • Journal of Korean Society of Transportation
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    • v.26 no.4
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    • pp.99-110
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    • 2008
  • It is commonly estimated that there is a much higher potential for accidents at a crossroads than along a single road due to its plethora of conflicting points. According to the 2006 figures by the National Police Agency, the number of traffic accidents at crossroads is greatly increasing compared to that along single roads. Among others, crossroads installed with traffic signals have more varied influential factors for traffic accidents and leave much more room for improvement than ones without traffic signals; thus, it is expected that a noticeable effect could be achieved in safety if proper counter-measures against the hazards at a crossroads were taken together with an estimate of causes for accidents This research managed to develop models for accident forecasts and accident intensity by applying data on accident history and site inspection of crossroads, targeting four selected downtown crossroads installed with traffic signals. The research was done by roughly dividing the process into four stages: first, analyze the accident model examined before; second, select variables affecting traffic accidents; third, develop a model for traffic accident forecasting by using a statistics-based methodology; and fourth, carry out the verification process of the models.

Development of Severity Model for Rural Unsignalized Intersection Crashes (지방부 비신호 교차로 교통사고 심각도 예측모형 개발 - 수도권 주변 및 전라북도 지역의 3지 비신호 교차로를 중심으로 -)

  • Lee, Dong-Min;Kim, Eung-Cheol;Sung, Nak-Moon;Kim, Do-Hoon
    • International Journal of Highway Engineering
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    • v.10 no.3
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    • pp.47-56
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    • 2008
  • Generally, accident exposure at intersections is relatively higher than that at roadway segments due to more possibility of merging, diverging, turning, crossing, and weaving maneuver. Furthermore, the traffic accident rate at intersections has been rapidly increasing since 1990's. Since there is more opportunity of conflict at unsignalized intersection, frequency and severity of traffic accident are more severe than signalized intersections. The purpose of the study is to analyze factors causing vehicle crashes and provide intersection design guidelines to improve intersection safety. For this study, vehicle to vehicle crash data of 116 rural 3 legs unsignalized were collected and field surveys were conducted for traffic and geometric conditions. Ordered probit models were developed to analyze the severity of crashes. It was found that weather, obstacles in minor roadsides, presence of major exclusive right lane, presence of major road crosswalk, difference between posted speed of major road and minor road, land-use around intersections, shoulder width of major road, ADT of major road are significant factors for intersection safety.

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Effect Analysis of Public Data-Based Automatic Traffic Enforcement Camera Installation Using the Comparison Group Method (비교그룹방법을 이용한 공공데이터 기반 교통단속장비 사고감소 효과분석)

  • Yunseob Lee;Yohee Han;Youngchan Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.6
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    • pp.168-181
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    • 2023
  • This study analyzed the effects of traffic enforcement on accident reduction. The results revealed a significant reduction in both overall accidents (28.53%) and fatal accidents (39.44%). Notably, enforcement equipment targeting speed limits of 30 km/h and 50 km/h demonstrated similar accident reduction rates of 42.23% and 25.85%, respectively. However, variations were observed based on accident types and types of traffic violations. Therefore, it is evident that enforcement equipment yields distinct accident reduction effects depending on speed limits and types of traffic accidents. This finding underscores the potential for making informed policy decisions to enhance traffic safety measures.

The Relationship between Violation of Designated Lane Usage and Accident Severity on Freeways (고속도로 지정차로제 위반과 교통사고 심각도와의 관계분석: 화물차량을 대상으로)

  • Kim, Joo-Hee;Lee, Soo-Beom;Kim, Da-Hee;Hong, Ji-Yeon
    • Journal of Korean Society of Transportation
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    • v.30 no.3
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    • pp.119-127
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    • 2012
  • For traffic safety, it is imperative for motorists to secure their clear view and to maintain a similar speed with others while driving in a lane. Large-sized vehicles at lower speeds, however, are likely to increase the risk of accident when they share a lane with cars. Although to overcome this complication the Korean Road Traffic Act established rules for the safe use of roads, the reality is that the rules are seldom observed strictly. In this light, this study was designed to analyze the severity of truck-involved accidents, thereby providing justification for the need of truck-designated lanes and thus contributing to measuring road safety more precisely. A binomial logistic regression model was applied to analyze the severity of truck-involved accidents. The analysis showed that several variables affect the severity of truck-involved accidents on freeways; i.e., violation against the rule of truck-designated lanes, weather, difference between daytime and nighttime, and parking on road shoulder. Moreover, the strong enforcement will be needed to make motorists observe the rule, because a Wald statistical test showed that the violation against the rule of truck-designated lanes has the largest influence on the severity.

The Effects of Driving Behavior Determinants on Dangerous Driving and Traffic Accidents in the Reckless Drivers Group: A Path Analysis Study (사고 및 음주운전자들의 운전행동결정요인 특성이 위험행동 및 교통사고에 미치는 영향: 경로분석 연구)

  • O, Ju-Seok;Lee, Sun-Cheol
    • Journal of Korean Society of Transportation
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    • v.25 no.2 s.95
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    • pp.95-105
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    • 2007
  • Speeding and drunken driving make drivers fail to detect hazards and cope with various driving situations. These behaviors also raise the possibility of being involved in traffic accidents and tend to increase the number of fatalities. The authors compared the driving behavior determinants of a rockless drivers group, consisting of individuals who have committed traffic accidents or offended regulations through drunken driving, with a normal drivers group. In the results, the reckless drivers group showed high scores of 'speeding' and 'drunken driving', and they also stated that they had more experiences of speeding, drunken driving and traffic accidents. In the path analysis study, it was found that the impacts of the rockless drivers group's 'risk sensitivity' and 'situational adaptability' on traffic accidents were stronger than those of normal drivers. This means 'risk sensitivity' and 'situational adaptability' can explain the origins of traffic accidents better in the reckless drivers group than accidents of the normal drivers group.

Effects of maximum speed limit on Gyeongbu Expressway (경부고속도로 최고제한속도 상향에 따른 교통사고 영향 분석)

  • Song, Yinhua;Seong, Byeongchan
    • The Korean Journal of Applied Statistics
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    • v.30 no.5
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    • pp.719-731
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    • 2017
  • In September 2010, the Korea government increased the speed limit on the Gyeongbu Expressway (Cheonan IC.-Yangjae IC) from 100 to 110 km per hour. This paper considers ARIMA-Intervention model to analyze the effects of the speed limit change on the incidences of traffic accidents and injuries. In addition, in order to investigate the effects more clearly, we also analyze the difference between the two lines of Cheonan IC-Yangjae IC and Busan IC-Cheonan IC. As a result, we observe that the numbers of accidents and injuries have increased after the speed limit change. The increases are strikingly distinctive in comparison to other lines (Busan IC-Cheonan IC) where there have been no changes in the maximum speed limit.

Accident Conversion Effect Analysis of Installing Median Barriers (중앙분리대 설치에 따른 사고전환효과 분석)

  • Park, Min-Ho;Park, Gyu-Yeong;Jang, Il-Jun;Lee, Su-Beom
    • Journal of Korean Society of Transportation
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    • v.24 no.2 s.88
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    • pp.113-124
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    • 2006
  • Among tile traffic safety facilities, median barriers are installed above 4-lane national roads due to the awareness of haying an effect on preventing the front collision. Studies about the installation effect analysis of median harrier have been carried out through both at home and outside, mainly indicating total accident reduction effect on pertinent sections. In sum, study about how the accident occurrence form is changed at the point classified by the accident type or severity is insignificant. In the case of outside the country, calculating the accident reduction effect according to the type of median barriers is main research and in domestic, though there is a part of researches assessing reduction effect by accident types, it is not reliable in the view or statistics because of using only 1year's before-aftev data installing the facility, So in this Paper. it is the main purpose to presume the accident conversion effect. For this, we conduct an investigation and collect data about 7-year's accident data containing before-after Project, safety facilities foundation records and index of road alignment on the subject of 4-1ane national roads(108.6km) existing median barrier. Next. using the empirical bayes method, we estimate a model construction and accident conversion effect of accident type severity. We expect the result or this Paper will be applied for a policy execution and Presentation of facility standard related to median barrier from now on.

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.