• International Journal of Highway Engineering
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• v.11 no.2
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• pp.151-158
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• 2009

This study deals with the rear-end collisions in the rural aiea. The objectives of this study are 1) to analyze the characteristics of rear-end accidents of signalized intersections, and 2) to develop the accident models for Cheongju-Cheongwon. In pursing the above, this study gives the particular attentions to comparing the characters of urban and rural area. In this study, the dependent variables are the number of accidents and value of EPDO(equivalent property damage only), and independent variables are the traffic volumes and geometric elements. The main results analyzed are the followings. First, the statistical analyses show that the Poisson accident model using the number of accident as a dependant variable are statistically significant and the negative binomial accident model using the value of EPDO are statistically significant. Second, the independent variables of Poisson model are analyzed to be the ratio of high-occupancy vehicles, total traffic volume and the sum of exit/entry, and those of negative binomial regression are the main road width, total traffic volume and the ratio of high-occupancy vehicles. Finally, the specific independent variables to the rural area are the main road width, the ratio of high occupancy vehicle, and the sum exit/entry.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.31-39
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• 2008

Preventing the traffic accident by accurately predicting it in advance can greatly improve road traffic safety. The accurate traffic accident prediction model requires not only understanding of the factors that cause the accident but also having the transferability of the model. So, this paper suggest the traffic accident diagram using CART(Classification And Regression Tree) analysis, developed Model is compared with the existing accident prediction models in order to test the goodness of fit. The results of this study are summarized below. First, traffic accident prediction model using CART analysis is developed. Second, distance(D), pedestrian shoulder(m) and traffic volume among the geometrical factors are the most influential to the traffic accident. Third. CART analysis model show high predictability in comparative analysis between models. This study suggest the basic ideas to evaluate the investment priority for the road design and improvement projects of the traffic accident blackspots.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.69-77
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• 2007

This study presents comparison results for pedestrian accident reconstruction models representing the relationship between collision speed and horizontal distance that a body travels while falling and sliding. A set of 49 reliable pedestrian accident cases are applied to compare the existing reconstruction models. In addition, the authors investigate the effects of a set of parameters associated with the effects of the frontal shape of a vehicle on the horizontal distance a pedestrian travels while falling and sliding. It has been revealed that the length of the bumper is the most dominant factor to affect the horizontal distance of pedestrian travel after collision. Further analyses utilizing more accident data need to conducted to develop a more accurate and reliable reconstruction model.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.65-76
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• 2013

Traffic accidents at signalized intersections have been increased annually so that it is required to examine the causation to reduce the accidents. However, the current existing accident models were developed mainly by using non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal the complicated causation for traffic accidents, though they are the right choice to study randomness and non-linearity of accidents. Therefore, it is required to utilize another statistical method to make up for the lack of the non-linear regression methods. This study developed accident prediction models for 4 legged signalized intersections with Poisson methods and compared them with structural equation models. This study used structural equation methods to reveal the complicated causation of traffic accidents, because the structural equation method has merits to explain more causational factors for accidents than others.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.106-106
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• 2017

우리나라는 현재 재난의 유형을 자연재난과 사회재난으로 구분하여 관리하고 있다. 하지만 최근 재난 사고 사례를 살펴보면 단일재난으로 인한 피해보다 자연재난이 발생한 이후 사회재난으로 재난이 전파되는 복합재난의 형태가 종종 나타나고 있다. 복합재난은 단일 재난에 의한 피해(인적, 물적) 보다 크게 나타나고 복합재난의 발생원인 및 전파과정을 분석하기 어려워 이에 대한 다각적인 분석과 동시에 재난상호간의 연관성을 도출하는 연구가 필요한 시점이다. 과거 재난사고정보를 분석하는 연구는 일반적인 통계기법을 활용한 분석에 머물러 있으며 수집된 재난사고사례가 많지 않아 분석에 신뢰성을 보장할 수 없었다. 이에 본 연구에서는 복잡하게 나타나는 재난 사고를 분석하기 위하여 최근 각광받고 있는 인공지능 분석기법을 연구에 고려하였다. 본 연구의 과정은, 첫째로 재난사고정보 분석에 인공지능을 활용한 사례를 조사하고 여타 연구분야에서 적용되고 있는 인공지능 분석기술을 재난사고정보 분석에 활용할 수 있는 방안을 모색하였다. 둘째로 수집가능 한 재난사고정보를 수집하고 인공지능 모형에 적용가능 한 형태로 변환하는 과정을 수행하였다. 셋째로 변환된 재난사고정보를 대표적인 인공지능 알고리즘을 활용하여 다양한 질문(목적)에 부합하는 재난사고정보 분석모형을 구축하고자 하였다. 마지막으로 다양한 인공지능 알고리즘을 적용한 모형의 신뢰성을 비교하였으며 이를 통하여 재난사고정보 분석에 적용가능 하며 질문(목적)에 부합하는 최적 인공지능 알고리즘을 도출하고자 하였다.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.97-105
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• 2011

This paper presents how one can investigate the effects on crash occurrence of freeway geometric design elements including the horizontal, vertical alignment and road environment. At present, the available research results for the most part involve geometric data analysis that are obtained along a relatively long section of freeway, and, because of the long section's diverse geometric conditions, the results tend to miss the specific local geometric impacts on vehicle crashes. In this regard, this research attempts to establish vehicle crash models based on a set of freeway geometric patterns whose crash generating characteristics are identical because they are homogeneous in terms of producing the same vehicle operating speeds, and subsequently their actual relationships are described by providing statistical analysis made in this research. Also each standard is comprised of part of straight, curve and continuous curve. This research has revealed that each type of model has different relation between accident and geometry structure. This research results should be useful for doing more reasonable highway designs and safety audit analysis.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.151-159
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• 2010

This paper presents a research result that was performed to develop a more accurate freeway crash prediction model than existing models. While the existing crash models only focus on developing crash relationships associated with highway geometric conditions found on a short section of a crash site, this research applies a different approach considering the upstream highway geometric conditions as well. Theoretically, crashes occur while motorists are in motion, and particularly at freeways vehicle speed at one specific point is very sensitive to upstream geometric conditions. Therefore, this is a reasonable approach. To form the analysis data base, this research gathers the geometric conditions of the West Seaside Freeway 269.3 km and six years crash data ranging 2003-2008 for these freeway sections. As a result, it is found that crashes fit well into Negative Binomial Distribution, and, based on the developed model, total number of crashes is inversely proportional to highway curve length and radius. Contrarily, crash occurrences are proportional to tangent length. This result is different from existing crash study results, and it seems to be resulted from this research assumption that a crash is influenced greatly by upstream geometric conditions. Also, this research provides the expected effects on crash occurrences of the length of downgrade sections, speed camera placements, and the on- and off- ramp presences. It is expected that this research result is useful for doing more reasonable highway designs and safety audit analysis, and applying the same research approach to national roads and other major roads in urban areas is recommended.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.281-283
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• 2020

본 연구는 2015년 교육과정에 명시된 정보교과의 운영방침과 중등학교 소프트웨어 교육 현황을 분석하고, 이에 대한 문제점을 해결 할 수 있는 방안으로 창의적 문제 해결력을 통한 소프트웨어 교육 모형을 제안한다. 창의적 문제 해결력은 확산적 사고와 수렴적 사고를 통해 학생들이 문제 해결에 필요한 사고를 키울 수 있는 모형이다. 이에 본 논문에서는 컴퓨팅 사고력을 가진 창의·융합 인재 육성이라는 소프트웨어의 교육 목표를 달성하기 위해 기존의 CPS모형과 CT의 요소간의 유사점을 확인하고 이를 바탕으로 새로운 CPS-SW 모형을 제안한다. CPS-SW 모형으로 컴퓨팅 사고력과 창의적 문제해결력을 키울 수 있으며, 이를 통해 미래 사회에 필요한 인재육성을 위한 소프트웨어 교육의 발전에 기여하고자 한다. 또한 CPS-SW 모형을 적용할 수 있는 프로그램과 학생들이 창의적 문제해결력을 키울 수 있는 학습에 대한 연구가 필요할 것으로 예상한다.

• 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.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.87-96
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• 2010

The impact speed estimation practice used in the car-bicycle accident analysis practice in Korea was mainly dependent on foreign study results which were tested with limited speed ranges and vehicle types, but the characteristics of roadway, human body, and vehicle performance were quite different. This study developed an impact speed estimation model using the car-bicycle accident field data. For this, a regression analysis was performed using the impact speed and bicycle throw distance collected from 23 real accident data, and statistical test was also conducted. For the verification of the induced model, the impact speeds derived from the model were compared with the true impact speeds estimated from skid marks of two accident cases. The result showed that the two speeds were very close to each other. It is believed that the model could be included in the car-bicycle accident analysis practice.