• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.12-28
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• 2019

Road geometry is one of the many factors that cause crashes, but the effect on traffic accident depends on weather conditions even under the same road geometry. This study identifies the variables affecting the crash severity by matching the highway accident data and weather data for 14 years from 2001 to 2014. A hierarchical ordered Logit model is used to reflect the effects of road geometry and weather condition interactions on crash severity, as well as the correlation between individual crashes in a region. Among the hierarchical models, we apply a random intercept model including interaction variables between road geometry and weather condition and a random coefficient model including regional weather characteristics as upper-level variables. As a result, it is confirmed that the effects of toll, ramp, downhill slope of 3% or more, and concrete barrier on the crash severity vary depending on weather conditions. It also shows that the combined effects of road geometry and weather conditions may not be linear depending on rainfall or snowfall levels. Finally, we suggest safety improvement measures based on the results of this study, which are expected to reduce the severity of traffic accidents in the future.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.17-29
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• 2010

The main objective of this study is to consider the necessity of introducing owner expenses in estimating the cost of traffic accidents, as is done in some advanced countries. It is known as "owner cost" in the U.S, "enterprise project price" in Japan, and "human cost" in the U.K. To achieve this, the seriousness and present state of post-traumatic stress disorder (PTSD) of traffic accident offenders, which is generally not observed when traffic accidents occur, are evaluated; countermeasures reflecting personal characteristics are prepared according to degree of affliction. The results could be summarized as follows. First, the present condition and seriousness of PTSD from traffic accidents that has been estimated only within the accidents offenders are evaluated through a survey. Second, a distinction analysis model is developed. 'Insomnia caused by accidents' and 'mental daunting in accident situations or similar ones during driving' are chosen as the variables of the discriminant. Third, as a result of the construction of an Ordered Probit Model to comprehend the seriousness of PTSD, the variables turns out in the order of 'seriousness of the most damaged victim, 'nightmare about the accident', 'insomnia experience', 'mental daunting during driving', 'gender', and 'major driving area'. Finally, the cures reflecting characteristics of gender and region are suggested, which are preferred for degree of seriousness of PTSD. The analysis shows that the method to minimize the damage, such as decline of work efficiency, by moving ahead the rehabilitation of the offenders would be suggested and this could minimize the direct and indirect damages that could happen to business owners for whom the drivers work.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.13-29
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• 2020

Automobiles have long been an essential part of daily life, but the social costs of car traffic accidents exceed 9% of the national budget of Korea. Hence, it is necessary to establish prevention and response system for car traffic accidents. In order to present a model that can classify and predict the degree of injury in car traffic accidents, we used big data analysis techniques of K-nearest neighbor, logistic regression analysis, naive bayes classifier, decision tree, and ensemble algorithm. The performances of the models were analyzed by using the data on the nationwide traffic accidents over the past three years. In particular, considering the difference in the number of data among the respective injury severity levels, we used down-sampling methods for the group with a large number of samples to enhance the accuracy of the classification of the models and then verified the statistical significance of the models using ANOVA.

• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.597-600
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• 2000

계속적인 증가 추세를 보이고 있는 교통량으로 인해 환경 문제뿐 아니라 교통사고로 인한 사상자 및 물적피해가 상당량으로 집계되고 있다. 본 논문에서는 데이터융합 및 앙상블 클러스터링방법을 이용한 교통사고 심각도 분류분석방법을 제안함으로서 교통사고예방에 기여하고자 한다. 이를 위하여 신경망과 Decision-Tree기법을 이용하여 얻은 물적피해와 신체상해가 발생할 확률을 융합하는 전형적인 데이터 융합기법(템스터-쉐퍼, 베이지안 방법, 로지스틱융합방법)을 사용하였다. 또한, 분류정확도를 향상시키고자 Bootstrap 재추출 방법을 이용해 얻어진 여러 개의 분류예측 결과 중 다수의 분류결과를 선택하는 앙상블 (arcing, bagging)기법을 적용하였다. 더불어, 본 연구에서는 클러스터링 방법을 제시하고, 이 방법이 기존의 융합기법, 앙상블기법과 비교한 결과, 분류예측면에서 정확도가 향상됨을 보였다.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.841-851
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• 2019

This study presents risk ranking by accident types at intersections, crosswalk and tunnel sections. An ordered logit model was used to estimate the accident severity of traffic accidents based on 58,868 accident records that have occurred on the Seoul and Gyeonggi-do over the period 2014-2017. The factors affecting the injury severity were identified by the estimated model first, and risk ranking was proposed according to conditions of accident occurrence using relative ratio analysis later. The analysis results showed that the injury severity dramatically depends on the location and time of the accident. The analysis results showed that the injury severity dramatically depends on the location and time of the accident. Furthermore, there are severe injury cases in terms of the injury severity despite the small number of occurrence of traffic accident, or there are severe injury cases in terms of the injury severity despite the high frequency of occurrence of traffic accident.

• International Journal of Highway Engineering
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• v.9 no.4
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• pp.83-92
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• 2007

In 2004, the number of traffic crashes and deaths in Korea are 220,755 and 6,563, respectively. Korea Road Traffic Safety Authority reported that the number of traffic accidents occupies over 25% out of total accidents, and found that traffic crash probability is extremely high at intersections since intersections have various traffic conflict points. A Safety study using Traffic Conflict Technique is much more useful than a study using reported traffic accident data. Existing traffic conflict research hardly considered conflict severity occurring at intersections. So, the study developed new criteria considering conflict severity. Analytic methods precisely detecting crashing points using field surveying data, and applied an application of our new criteria. Opposing left-turn conflict criteria was devided by three groups(high severe conflict, middle severe conflict, and less severe conflict) based on conflict boundary by means of a standard vehicle length. After analyzing field surveying data(3hours), we found totally 41 opposing left-turn conflicts. 3 cases are high severe conflict, and another 10 cases are middle severe conflicts, and the other cases are less severe. Studies related in conflict severity are considerably important to evaluate intersection's detailed safety index, and existing studies(purely conflict counting does not consider severity) have a limitation to clearly determine the level of safety of intersections for an application.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.1-14
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• 2020

The aim of this study is to analyze effects of factors on the number of vehicles involved in traffic accidents on freeway sections. In previous studies about traffic accident severity, the analysis of accidents involving multiple vehicles was insufficient. However, multiple-vehicle accidents are likely to cause casualties and are the main reasons increasing accident duration and social costs. In this study, the number of vehicles involved in an accident was interpreted as the result of the accident, not as the cause of the accident, and the impacts of each accident factor were analyzed using a multinomial logit model. The results indicate that multiple-vehicle accidents are mainly related to following factors: nighttime, driver's faults, obstacles on the road, a downhill slope, heavy vehicles, and freeway mainline sections including tunnels and bridges.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.261-262
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• 2023

보행자 교통사고는 보행자와 운행 중인 차량 간 발생한 충돌사고로 도로 및 주변 환경 등에 영항을 받는다. 이 연구에서는 2018년부터 2022년까지 서울특별시에서 발생한 노인 보행자 교통사고 자료를 수집하여 보행자 교통사고의 사고 요인을 분석하였다. 분석에 있어서 고려된 연구모형은 랜덤포레스트, Gradient Boosting regression(GBR)이다. 분석 결과 서울특별시의 지리적 특성과 교통 통행 패턴을 반영하여 교통약자를 대상으로 하는 교통정책을 보완하고, 보행 안전을 강화하는 것이 필요하다.