• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.103-111
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• 2011

To evaluate highway safety countermeasures or identify high risk sites, the expected crashes for a site (or segment) have been estimated using the panel crash data. Past studies show that two different methods can be employed to estimate the expected crashes: observed crash based method and empirical Bayes (EB) method. This study conducts a simulation study to analyze how the estimation errors of the two estimates are affected by the different structures of the panel crash data and the presence of the change in safety over time. The results disclose that the estimation errors of the observed crash based estimates (i.e. the mean observed crash and comparative parallel estimate) are always greater than those of the EB estimates regardless of the structure of the panel crash data and the presence of the change in safety over time. Thus, it is highly recommended that the EB method be used in the study of traffic safety to obtain more reliable estimates for the expected crashes. In addition, this study corroborates that the estimation errors of the two estimates decrease as the analysis periods increase if safety does not change over time. Hence, it is also recommended that the 1-year analysis period used for identifying high risk sites in Korea be extended to produce more efficient estimates of the time-constant expected crashes.

• Korean Security Journal
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• no.55
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• pp.31-55
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• 2018

The purpose of this study is to analyze the precedence analysis of traffic safety facilities installation for traffic accidents. The main results were as follows. First, the precedence of the number of traffic safety signs installation for the number of traffic accident is follows. The number of traffic safety signs[total number] (time precedent 1), the number of traffic safety signs[attention] (time precedent 7), the number of traffic safety signs[regulation] (time precedent 7), the number of traffic safety signs[indication] (time precedent 4) precede the number of traffic accidents as negative(-) relationship. Second, the number of traffic signal equipments[pedestrian lamp] (time precedent 2) precedes the number of traffic accidents as negative(-) relationship. Third, the precedence of the increase/decrease rate of traffic safety facilities installation for the increase/decrease rate of traffic accident is follows. The increase/decrease rate of traffic safety signs[total number] (time precedent 1), the increase/decrease rate of traffic safety signs[attention] (time precedent 1), the increase/decrease rate of traffic safety signs[indication] (time precedent 1), the increase/decrease rate of traffic safety signs[auxiliary] (time precedent 1) precede the increase/decrease rate of traffic accidents as negative(-) relationship. Fourth, the increase/decrease rate of traffic signal equipments[pedestrian lamp] (time precedent 0) accompanies the increase/decrease rate of traffic accidents as positive (+) relationship.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.89-98
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• 1998

교통사고의 원인은 인적 요인, 차량적 요인, 도로 환경적 요인으로 분류된다. 주어진 도로 환경과 차량 조건하에서는 운전자가 마지막으로 안전을 제어할 책임을 지고 있다. 따라서, 교통사고를 사전에 예방하기 위하여 운전자의 교통법규 위반 행위에 대하여는 도로교통법에 근거하여 징역, 벌금, 구류, 과료, 과태료, 범칙금에 처하고 있다. 교통법규 위반 행위 단속 시에는 교통사고 유발 가능성과 위험도에 따라 단속의 강약을 포함하여 차등화된 처벌이 이루어져야 한다. 교통 범칙금 기준 제시를 위하여 1991~1995년의 5년간 교통사고 및 교통법규 위반을 분석한 결과 전체 교통법규 위반 단속 중 교통사고를 야기하는 동적 위반 행위인 사고관련 위반 행위 단속의 비율이 44%로 일본의 61%에 비해 매우 낮은 수준이다. 따라서 사고유발 가능성에 근거한 교통법규 위반 행위 단속의 강화가 필요하다. 한편 범칙금 부과방안으로 피해도 모형과 빈도 모형을 비교한 결과 교통법규 위반 행위로 인해 발생된 교통사고 비용을 고려한 피해도 모형은 범칙금의 차등화가 분명하지 않고 변별력이 뚜렷이 나타나지 않아 적합하지 않은 것으로 분석되었다. 교통법규 위반 행위에 따른 빈도 모형은 교통사고 건수와 사망사고 건수의 가중치(w)설정을 위해 동적 위반행위가 우리나라와 유사한 일본 자료와 비교한 결과 가중치가 한국=0.7, 일본=0.8일 때 상대적으로 $x^2$가 31.71로 가장 낮게 나타났다. 따라서, 사고건수에 대한 가중치는 0.7로 사망사고에 대한 가중치는 0.3을 적용하였다. 마지막으로 현행 범칙금과 제안된 범칙금을 비교분석하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.453-459
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• 2010

In the study of traffic safety, it is utmost important to obtain more reliable estimates of the expected crashes for a site (or a segment). The observed crashes have been mainly used as the estimate of the expected crashes in Korea, while the empirical Bayes (EB) estimates based on the Poisson-gamma mixture model have been used in the USA and several European countries. Although numerous studies have used the EB method for estimating the expected crashes and/or the effectiveness of the safety countermeasures, no past studies examine the difference in the estimation errors between the two estimates. Thus, this study compares the estimation errors of the two estimates using a Monte Carlo simulation study. By analyzing the crash dataset at 3,000,000 simulated sites, this study reveals that the estimation errors of the EB estimates are always less than those of the observed crashes. Hence, it is imperative to incorporate the EB method into the traffic safety research guideline in Korea. However, the results show that the differences in the estimation errors between the two estimates decrease as the uncertainty of the prior distribution increases. Consequently, it is recommended that the EB method be used with reliable hyper-parameter estimates after conducting a comprehensive examination on the estimated negative binomial model.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.135-144
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• 2009

This study estimates the expected number of accidents in Kyungbuk Province to capitalize on experience gained from four years of accident history using the Empirical Bayes (EB) Method. The number of accidents of each site in Kyungbuk Province is recalculated using the Equivalent Property Damage Only (EPDO) method to reflect the severities of the accidents. A cluster analysis is performed to determine similar sites and a unique Safety Performance Function (SPF) is established for each site. The overdispersion parameter is built to correct the difference between the actual number of accidents and the underlying probability distribution. To adjust for varying traffic characteristics of each site, a relative weight is applied and eventually estimates the expected number of accidents. The results show that the highest accident sites are Kimcheon, Youngcheon, and Chilgok, but on the other hand the lowest is Gunwi.

• Journal of the Korean Society for Railway
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• v.6 no.4
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• pp.11-18
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• 2003

우리는 복잡한 현상을 하나의 수치로 표현하는 각종 지표(index)를 생활에서 많이 접하고 있다. 종합주가 지수, 불쾌지수, 소비자 물가지수, 년간 교통사고 건수, 인구 10만명당 교통사고 사망자수 등도 일종의 지표라 할 수 있다. 철도에서도 위험을 평가하는 지표로는 "년간 사고건수", "열차운행 100만-km당 사고건수"와 같이 발생빈도에 초점을 둔 경우와 "년간 사망자수", 혹은 "피해액", "운행지장"과 같이 사고피해에 초점을 둔 경우가 있다. (중략)

• Journal of Korean Society of Transportation
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• v.15 no.1
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• pp.5-15
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• 1997

공간통계분석은 공간적으로 연계된 변수들간의 관계를 분석하는 통계분야이다. 일 반적으로 공간적으로 연계된 변수들간의 관계는 각 변수간의 공간적 분포정도에 따라서 영 향을 받는다. 전통적인 통계 분석의 방법은 동질의 자료발생과정에 의하여 확률적으로 축출 된 표본자료를 가정하고 있으나, 공간적인 자료는 이와 같은 동질의 자료발생과정의 가정을 부정한다. 교통류 및 교통사고 등과 같은 교통분야의 자료는 대부분 공간적인 상관관계에 의하여 축출된 이질적인 표본자료이며 따라서 공간상관관계를 동질적으로 가정한 전통적인 통계적 분석 방법은 오류를 범할 수 있다. 본 논문은 공간적인 관계를 고려한 공간자기상관 분석기법을 이용하여 고속도로상의 교통사고에 관하여 분석하였다. 분석의 결과에 의하면 4 개 고속도로 중 경인고속도로를 제외한 3개의 고속도로상의 교통사고건수는 통계적으로 현 저한 양의 공간적 상관관계가 있음을 알 수 있었다. 이에 따라 공간적 상관관계를 고려한 교통사고분석을 위하여 종속변수로 단위구간별 교통사고건수를 그리고 설명변수로서는 단위 구간별 교통량, I.C. 유무 및 화물차량비율을 이용하여 공간 자기회귀분석을 시도하였다. 분 석의 분석에서는 구간별 교통량과 화물차량의 비율이 호남/남해 고속도로의 경우에는 구간 별 교통량과 I.C. 유무가 통계적으로 유의한 것으로 분석되었다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.249-250
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• 2017

현재 전체 교통사고 건수는 감소하는 추세이지만 보행자 교통사고는 점점 증가하고 있다. 또한 보행자 교통사고 중 고령보행자 교통사고건수 비율이 높은데 이에 따른 원인분석과 예방 대책에 관한 연구가 필요하다. 이에 본 연구는 고령보행자 다발지역을 분석하여 사고 원인을 비교분석 하는 것이다. 다발지역 분석결과 대부분 보행자가 횡단 중 일 때 사고가 발생하였고, 도로형태에서는 교차로, 신호기가 없는 일반도로에서 많이 발생했다. 이에 무단횡단을 방지하는 시설 확대 설치와, 무단횡단의 위험성을 알리는 안전교육의 필요성이 있다고 본다.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.81-90
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• 2009

The safety management of a road network comprises four basic inter-related components：identification of sites(black spot) requiring safety investigation, diagnosis of safety problems, selection of feasible treatments for potential treatment candidates, and prioritization of treatments given limited budgets(Persaud, 2001). Identification process of selecting black spot is very important for efficient investigation of sites. In this study, the accident prediction model for EB method was developed by using accident data and geometric conditions of black spots selected from four-leg signalized intersections in In-cheon City for three years (2004-2006). In addition, by comparing the rank nomination technique using EB method to that by using accident counts, we managed to show the problems which the existing method have and the necessity for developing rational prediction model. As a result, in terms of total number of accidents, both the counts predicted by existing non-linear regression model and that by EB method have high good of fitness, but EB method, considering both the accident counts by sites and total number of accident, has better good of fitness than non-linear poison model. According to the result of the comparison of ranks nominated for treatment between two methods, the rank for treatment of almost sites does not change but SeoHae intersection and a few other intersections have significant changes in their rank. This shows that, with the technique proposed in the study, the RTM problem caused by using real accident counts can be overcome.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1571-1579
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• 2014

93% of road traffic accidents result from drivers' fault and Korea has the largest number of deaths from traffic accidents among the OECD members. For this reason, the country is measuring Traffic Culture Index (TCI) in each city, gun and gu annually to improve traffic safety policies and promote safety consciousness, but the influencing relation between TCI and actual traffic accidents is only based on the assumptions and no verification has been carried out, yet. Therefore, this study aims to verify if in reality, TCI represents the traffic culture level and has an influencing relation with traffic accidents and to suggest an improvement plan of research on the present state of TCI, based on the result. For this purpose, bases on data of the report about the present state of TCI from 2010 to 2012, and the influencing relation between the number of traffic accidents and the number of deaths from traffic accidents was analyzed through structural equation model. For influencing relation analysis through structural equation, research 1 to analyze the relation among TCI in each city, gun and gu, the number of traffic accidents and the number of deaths, and research 2 to analyze the influencing relation of the increase in TCI, the number of traffic accidents and the number of deaths were carried out. When verifying the influencing relation with traffic accidents through structural equation, the goodness of fit of the model was low in research 1 and as TCI increased, the number of accidents and deaths decreased in research 2 and thus the effect of TCI was verified.