PURPOSES: The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS: Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.

PURPOSES: This study deals with the traffic accidents classified by the traffic analysis zone. The purpose is to develop the accident density models by using zonal traffic and socioeconomic data. METHODS : The traffic accident density models are developed through multiple linear regression analysis. In this study, three multiple linear models were developed. The dependent variable was traffic accident density, which is a measure of the relative distribution of traffic accidents. The independent variables were various traffic and socioeconomic variables. CONCLUSIONS : Three traffic accident density models were developed, and all models were statistically significant. Road length, trip production volume, intersections, van ratio, and number of vehicles per person in the transportation-based model were analyzed to be positive to the accident. Residential and commercial area ratio and transportation vulnerability ratio obtained using the socioeconomic-based model were found to affect the accident. The major arterial road ratio, trip production volume, intersection, van ratio, commercial ratio, and number of companies in the integrated model were also found to be related to the accident.

PURPOSES : This study tries to develop the accident models of 4-legged signalized intersections in Busan Metropolitan city with random parameter in count model to understanding the factors mainly influencing on accident frequencies. METHODS: To develop the traffic accidents modeling, this study uses RP(random parameter) negative binomial model which enables to take account of heterogeneity in data. By using RP model, each intersection’s specific geometry characteristics were considered. RESULTS : By comparing the both FP(fixed parameter) and RP modeling, it was confirmed the RP model has a little higher explanation power than the FP model. Out of 17 statistically significant variables, 4 variables including traffic volumes on minor roads, pedestrian crossing on major roads, and distance of pedestrian crossing on major/minor roads are derived as having random parameters. In addition, the marginal effect and elasticity of variables are analyzed to understand the variables’impact on the likelihood of accident occurrences. CONCLUSIONS :This study shows that the uses of RP is better fitted to the accident data since each observations’specific characteristics could be considered. Thus, the methods which could consider the heterogeneity of data is recommended to analyze the relationship between accidents and affecting factors(for example, traffic safety facilities or geometrics in signalized 4-legged intersections).

PURPOSES: The purpose of this study is to verify traffic accident injury severity factors for elderly drivers and the relative relationship of these factors. METHODS: To verify the complicated relationship among traffic accident injury severity factors, this study employed a structural equation model (SEM). To develop the SEM structure, only the severity of human injuries was considered; moreover, the observed variables were selected through confirmatory factor analysis (CFA). The number of fatalities, serious injuries, moderate injuries, and minor injuries were selected for observed variables of severity. For latent variables, the accident situation, environment, and vehicle and driver factors were respectively defined. Seven observed variables were selected among the latent variables. RESULTS: This study showed that the vehicle and driver factor was the most influential factor for accident severity among the latent factors. For the observed variable, the type of vehicle, type of accident, and status of day or night for each latent variable were the most relative observed variables for the accident severity factor. To verify the validity of the SEM, several model fitting methods, including , GFI, AGFI, CFI, and others, were applied, and the model produced meaningful results. CONCLUSIONS: Based on an analysis of results of traffic accident injury severity for elderly drivers, the vehicle and driver factor was the most influential one for injury severity. Therefore, education tailored to elderly drivers is needed to improve driving behavior of elderly driver.

PURPOSES : The purposes of this study are to compare the day and night characteristics and to develop the models of traffic accidents. in Rural Signalized Intersections METHODS : To develop day and night traffic accident models using the Negative Binomial Model, which was constructed for 156 signalized intersections of rural areas, through field investigations and casualty data from the National Police Agency. RESULTS : Among a total of 17 variances, the daytime traffic accident estimate models identified a total of 9 influence factors of traffic accidents. In the case of nighttime traffic accident models, 11 influence factors of traffic accidents were identified. CONCLUSIONS: By comparing the two models, it was determined that the number of main roads was an independent factor for daytime accidents. For nighttime accidents, several factors were independently involved, including the number of entrances to sub-roads, whether left turn lanes existed in major roads, the distances of pedestrian crossings to main roads and sub-roads, lighting facilities, and others. It was apparent that if the same situation arises, the probability of an accident occurring at night is higher than during the day because the speed of travel through intersections in rural areas is somewhat higher at night than during the day.

PURPOSES: This study suggests the application of glow line marking technology for reducing traffic accidents at nighttime. METHODS: In this study, using a statistical analysis, we analyzed the characteristics of traffic accidents occurring at nighttime. Next, the strength, weakness, opportunity, and threat (SWOT) factors were derived based on a current-status analysis of glow line marking technology and road environments. An SO strategy, ST strategy, WO strategy, and WT strategy were established in accordance with the four SWOT factors. RESULTS : This study suggests that the following strategies should be promoted to apply glow line marking technology to a road environment: 1) an activation strategy for the technological development of glow line markings for a new paradigm in reducing traffic accidents, 2) a benefit enhancement strategy applying glow line marking technology in places where nighttime traffic accidents frequently occur, 3) a strategy for the expansion of glow line marking by replacing streetlights, and 4) a strategy for enhancing road applications through the development of various line marking methods in consideration of both performance and costs. CONCLUSIONS : The application of glow line markings in a road environment can contribute to a reduction of traffic accidents at nighttime, and aid energy savings from the replacement of streetlights.

The traffic accidents in Korea have been increasing every year due to various reasons and simultaneously causing socioeconomic cost at the national level. This study has analyzed the correlation between meteorological factors and the traffic accidents in Seoul during 2013. Especially, we have selected season, rain and temperature among the meteorological factors to identify their significance with the traffic accidents. In addition, analysis of variance, t-test and a multiple regression technique is applied. Major findings from the analyses are discussed at the district point of view, including the different effect of weather condition and the interaction effect of rain and temperature in winter. The results of this study would be useful for developing management strategies to reduce car crashes and injury severity in Seoul.

최근 10년간(2004~2013) 이륜차 교통사고 현황을 분석한 결과 승용차의 교통사고 비율은 연평균 0.1% 의 증가한 반면 자전거와 이륜차 교통사고는 5.7%에 해당하는 증가율을 보이고 있다. 이러한 자전거 및 이륜차 교통사고의 경우 승용차에 비해 치사율이 2.7배 높은 것으로 분석되어 사고감소를 위한 대책이 필 요하다. 본 연구에서는 자전거 및 이륜차 교통사고 중 사망사고 이력자료를 바탕으로 사고 발생 원인과 사고특성을 분석한다. 분석에는 도로교통공단에서 제공하는 교통사고 통계자료(교통사고분석시스템(TASS))를 이용하였다. 단순 통계분석이 아닌 교통사고GIS 자료를 이용하여 개별 사고에 대한 특성을 파악하여 사고의 원인을 분석하였다. 자전거 및 이륜차 사고 특성 분석결과 교차로와 단일로 모두 차량과의 측면 직각 충돌에 의한 사고가 많이 발생하는 것으로 분석되었다. 이러한 측면 충돌에 대한 사고 원인을 분석한 결과 교차로와 단일로 모두 전방주시 태만, 핸들 과대조작과 같은 안전운전 불이행으로 인한 측면 충돌에 의한 사망사고가 가장 높은 것으로 분석되었다. 이어서 신호위반, 과속 등과 같은 원인이 높게 분석되었다. 연령별로는 65세 이 상의 노인 운전자의 교통사고가 다른 연령층에 비해 높게 나타났다. 2013년도 기준 65세 이상의 노인 사 망자수는 전체 사망자수 중 43.2%로 분석되었고 중상자 및 경상자수 또한 전체의 22%에 해당하는 결과 를 보여 다른 연령대에 비해 사고심각도 또한 높게 분석되었다. 사고 유형별로는 도로이탈, 공작물 충돌 과 같은 사고의 치사율이 높게 분석되었으며 이는 조금만 속도가 높아도 도로를 이탈하거나 공작물 충돌 사고를 야기할 수 밖에 없는 자전거와 이륜차의 구조적 특성에 의한 원인으로 분석된다. 본 연구에서는 자전거 및 이륜차 교통사고 발생원인 및 특성분석 연구를 수행하였다. 향후연구로 자전 거 및 이륜차의 교통사고를 예방하기 위한 ʻ자전거 대 차ʼ, ʻ차 대 자전거ʼ의 사고를 미연에 경고할 수 있는 ʻB2Xʼ 서비스 개발을 제안한다.

교통사고는 2013년 한 해 동안 총 215,354건이며, 최근 5년간 교통여건 및 교통안전정책의 발전으로 평균 1.84%로 감소하는 추세에 있다. 그러나 OECD 통계에 따르면 우리나라는 인구 10만 명당 교통사고 발생건수가 2012년 기준으로 OECD평균인 310.4건에 비해 약 1.4배 많은 447.3건이 발생하는 실정이다. 이는 교통사고가 아직 심각한 문제로 자리 잡고 있으며, 교통사고를 줄이기 위한 근본적인 원인 규명과 대안이 필요하다. 기존 진행되어 왔던 교통사고에 대한 연구는 단순히 인적요인, 차량요인, 도로환경 요 인과 같은 점, 선적인 여건들을 중점으로 연구가 대부분이었다. 교통사고를 줄일 수 있는 근본적이 해결 책을 마련하기 위해서는 다양한 여건들이 반영되어야 한다. 이 점에 착안하여 본 연구는 다양한 여건들을 아우르는 지역적 특성과 함께 복합적인 요인의 관계를 분석하는데 목적이 있다. 연구를 수행하기 위해 공 간적 범위 대상지를 청주시로 하고, 면적인 차원에서의 토지이용변수를 활용하여 존별 특성을 반영한 교 통사고 모형을 개발하는 것이다. 이를 위해 청주시의 30개의 행정동을 존으로 구분하여 각 존별 토지이용 과 교통여건, 사회경제적 특성을 변수로 활용하여 다중선형회귀분석을 실시하였다.

PURPOSES : The bridge section of the expressway has a worse driving environment than the general section. However, traffic safety countermeasures are focused only on the bridge section. Traffic safety countermeasures on the section before entry to the bridge and the section after exit from the bridge are applied only when the bridge has a long-span section. Accordingly, this study will verify the necessity of extending the application of traffic safety countermeasures to areas that are affected by the bridge. METHODS: This study determines the areas that are affected by the bridge as well as the areas that are affected by locations with frequent traffic accidents and suggests the risk factors by affected areas through canonical discriminant analysis. For the analysis, traffic accident data for 3 years, which occurred on bridge sections in six major expressway lines, were used. RESULTS: The numbers of traffic accidents were 469 before the bridge, 281 on the bridge, and 468 after the bridge. The variables that have impact on the seriousness of accidents are as follows: speeding, excess manipulation of the steering wheel, and failure to secure safety distance for accidents that occurred before the bridge section; speeding, excess manipulation of the steering wheel, and dozing off for accidents that occurred on the bridge; and speeding and failure to secure safety distance for accidents that occurred after the bridge section. CONCLUSIONS : Areas affected by the bridge show higher accident rates than the bridge section; therefore, imposing traffic safety countermeasures on the integrated section of the bridge and the affected areas is required. It is believed that the results suggested in this study could be effectively used in the prevention of traffic accidents by imposing custom-made safety countermeasures for each section.

PURPOSES : The objective was to develop the advanced method which could not explain each observation’s specific characteristic in the present negative binomial method that results in under-estimation of the standard error(t-value inflation) and affects the confidence of whole derived results. METHODS : This study dealt with traffic accidents occurring within interchange segment on highway main line with RPNB(Random Parameter Negative Binomial) method that enables to take account of heterogeneity. RESULTS : As a result, AADT and lighting installation type on the road were revealed to have random parameter and in terms of other geometric variables, all were derived as fixed parameter(same effect on every segment). Also, marginal effects were adapted to analyze the relative effects on traffic accidents. CONCLUSIONS : This study proves that RPNB method which considers each observation’s specific characteristics is better fitted to the accident data with geometrics. Thus, it is recommended that RPNB model or other methods which could consider the heterogeneity needs to be adapted in accident analysis.

현재 교통사고 사망자수 줄이기를 위한 다양한 노력이 이루어지고 있으며, 이러한 노력의 결실을 맺기 위한 한 방편으로 교통사고취약구간에 대한 집중된 개선노력 및 투자가 요구되고 있다. 이러한 관점에서 본 연구는 고속도로 본선구간을 대상으로 사고유형별 교통사고취약구간 선정을 목적하고 있다. 이를 위하여 도로교통공단 교통사고분석시스템(TAAS)의 2007년에서 2013년까지 최근 7년간 고속도로 본선에서 발생한 총 21,724건을 대상으로 6가지 사고유형별로 구분된 데이터셋을 ArcMap을 활용하여 구 축한다. 교통사고취약구간 선정은 커널밀도를 활용한 KDE(Jernel Density Estimation)법을 활용하여 실 시한다. 기존 연구와의 차이점은 보다 정밀한 분석을 위하여 노선별 방향을 구분하여 접근함으로써 분석결과의 공동데이터로서의 활용도를 높였으며, 방대한 데이터셋과 더불어 사고유형별 접근을 통해 분석의 다양성 을 높였다는 점이다. 한편 KDE법을 활용하여 도출된 사고유형별 교통사고취약구간의 기하구조 및 교통특성 분석을 통하여 사고유형별로 달라질 수 있는 도로환경 요인에 대한 분석을 실시한다.

연구는 사고감소효과 평가를 하기위한 목적으로 단순사고건수 비교방법을 활용하여 사고감수 계수를 도출하고, 각각의 사고지점에 사고감수 계수를 적용하여 사고감소 편익을 산정하였다. 분석 대상지점은 2011년 08월부터 2011년 10월까지 실시되었던 천안시 교통안전진단 연구에서 선정된 사고다발지점 17개소 중 현장조사를 통해 개선사항 반영여부를 파악하여 개선사항이 한건이상 적용된 지점 10개소에 대하여 교통안전개선사업 실행 전(2009년~2011년)과 실행 후(2012년)의 교통사고 특성을 도로교통공단 교통사고분석시스템(TAAS:Traffic Accident Analysis System)의 자료를 활용하여 분석하였다. 단순사고건수 비교방법은 개선효과를 분석 대상지점의 사업 전과 후의 1년간 사고건수만을 단순 비교하는 방법으로써 현재 도로교통 공단에서「교통사고잦은곳 개선사업」을 수행하기 위해 사용되고 있고, 도로안전성을 평가하는데 가장 널리 사용되어지는 방법으로 이를 활용하여 교통사고감소계수를 산정한다. 교통사고 편익을 산정하기 위해 개선안에 의해 발생하는 교통사고감소건수의 산정과 교통사고감소에 의한 경제적 가치계산의 과정을 통하여 이루어지는데, 교통사고감소건수는 개선하지 않았을 때 예상되는 평균사고건수와 개선 전, 후의 일평균 교통량, 그리고 앞에서 도출한 교통사고감소 계수가 사용되어진다. 이때 개선하지 않았을 때 예상되는 평균사고 건수의 경우 개선 전 3년간의 자료의 평균값을 사용했으며, 전체적인 천안시의 교통량을 조사하였을 때 큰 차이가 없어 각 교차로별 개선 전, 후의 일평균 교통량은 같다고 가정하였다. 경제적 가치계산은 지점별 과거 사고자료를 기준으로 한 교통사고감소건수를 기준으로 교통개발연구원 (1997)에서 제시한 교통사고 원단위를 적용하였는데, 이에는 생산손실비용, 차량손실비용, 의료비용, 행정비용 이 포함되어 있다. 즉, 각 지점별로 교통사고감소건수를 산정하고 여기에 사고비용 원단위를 곱한 값을 합산하여 사고감소편익을 산정하였으며 다음 표. 1과 같이 나타났다. 본 연구는 교통안전개선사업 실시 후의 사고감소효과를 평가해 보았는데, 평가 결과 3개의 지점에서 개선을 했음에도 불구하고 음(-)의 편익이 발생하였는데, 이는 단순사고건수 비교법과 사고형태별 계수만을 적용하여 감소편익을 산정한 한계로 볼 수 있다. 이를 보완하기 위해서 향후 보다 장기간의 개선대안별, 도로특성별, 사고 유형별, 안전시설별 사고감소계수를 적용한 편익분석이 이루어져야 할 것으로 판단된다.

PURPOSES : This study aimed to analyze the impact the operation of pre-signals at 4-leg signalized intersections and present primary environmental factors of roads that need to be considered in the installation of pre-signals. METHODS : Shift of proportions safety effectiveness evaluation method which assesses shifts in proportions of target collision types to determine safety effectiveness was applied to analyze traffic crash by types. Also, Empirical Bayes before/after safety effectiveness evaluation method was adapted to analyze the impact pre-signal installation. Negative binomial regression was conducted to determine SPF(safety performance function). RESULTS : Pre-signals are effective in reducing the number of head on, right angle and sideswipe collisions and both the total number of personal injury crashes and severe crashes. Also, it is deemed that each factor used as an independent variable for the SPF model has strong correlation with the total number of personal injury crashes and severe crashes, and impacts general traffic crashes as a whole. CONCLUSIONS: This study suggests the following should be considered in pre-signal installation on intersections. 1) U-turns allowed in the front and rear 2) A high number of roads that connect to the intersection 3) Many right-turn traffic flows 4) Crosswalks installed in the front and rear 5) Insufficient left-turn lanes compared to left-turn traffic flows or no left-turn-only lane.

PURPOSES : This study aims to draw differences between primary and secondary crashes by comparing crash characteristics and to identify the unique characteristics of secondary crashes for making better effective countermeasures to reduce secondary crashes. METHODS : The characteristics of secondary crashes were compared to those of primary crashes through a two sample proportional test (z-test). RESULTS : The results showed that vehicle-to-vehicle crashes and vehicle-to-person crashes are dominant crash types in secondary crashes. Compared to primary crashes, secondary crashes were likely to occur during nighttime. With respect to season and weather, the proportion of secondary crashes occurred during winter and in snowy weather is relatively higher than that of primary crashes. The main causes of primary crashes were found to be drowsiness, speeding, and exaggerated steering control, whereas main factors affecting the occurrence of secondary crashes were negligence of keeping eyes forward and no keeping a safe distance as expected. CONCLUSIONS : The characteristics affecting the occurrence of secondary crashes are different from those of primary crashes, indicating that proper countermeasures should be established to prevent the occurrence of secondary crashes on highways.