• 한국측량학회지
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• 제36권3호
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• pp.153-164
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• 2018

Calculating the relevant length of left turn storages in urban intersections is very crucial in road designs. A left turn lane consists of deceleration lanes and left turn storages. In this study, we developed methods for calculating relevant lengths of left turn storages that vary at each intersection using UAV (Unmanned Aerial Vehicle) spatial images. Problems of conventional design techniques are applying the same number of left turn vehicles (N) using Poisson distribution without considering land use types, using a vehicle length that may not be measurable when applying the length of waiting vehicles (S), and using same storage length coefficient (${\alpha}$), 1.5, for every intersections. In order to solve these problems, we estimated the number of left turn vehicles (N) using an empirical distribution, suggested to use headways of vehicles for (S) to calculate the length of waiting vehicles (S) with a help of using UAV spatial images, and defined ranges of storage length coefficient (${\alpha}$) from 1.0 to 1.5 for flexible design. For more convenient design, it is suitable to classify two cases when possible to know and impossible to know about ratio of large trucks among vehicles when planning an intersection. We developed formula for each case to calculate left turn storage lengths of a minimum and a maximum. By applying developed methods and values, more efficient signalized intersection operation can be accomplished.

• 한국도로학회논문집
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• 제14권6호
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• pp.121-129
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• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

• 대한교통학회지
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• 제8권1호
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• pp.25-40
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• 1990

This study was undertaken to develop a traffic signal timing method for interconnected and semi-protected-left-turn intersections(the intersections which have left-turn signal but not exclusive left-turn lanes) on four-lane streets for energy saving and to computerize the method for the practical use. For this study, a probability model which could estimate the utilized time of the shared left-turn lane by through traffic during green period was developed based on field studies. The two left-turn treatments, leading and lagging left-turns, were tested for the intersections, and it can be concluded that the leading left-turn was more efficient for the normal urban streets on which through traffic is major traffic. Adopting the leading left-turn macro-models to estimate vehicular average delay and proportions of vehicles stopped at the intersections were developed. Using the two models as well as the idling fuel consumpution rate and the excess fuel consumption per stop-go speed change, a traffic signal timing method for the intersections for energy saving was developed and computerized. The method can be used for more than four-lane streets and for other measures of effectiveness such as minimum delay, minimum stop rates, etc.

• 지능정보연구
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• 제4권2호
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• pp.23-34
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• 1998

Travel time forecasting, especially public bus travel time forecasting in urban areas, is a difficult and complex problem which requires a prohibitively large computation time and years of experience. As the network of target area grows with addition of streets and lanes, computational burden of the forecasting systems exponentially increases. Even though the travel time between two neighboring intersections is known a priori, it is still difficult, if not impossible, to compute the travel time between every two intersections. For the reason, previous approaches frequently have oversimplified the transportation network to show feasibilities of the problem solving algorithms. In this paper, forecasting of the travel time between every two intersections is attempted based on travel time data between two neighboring intersections. The time stamps data of public buses which recorded arrival time at predetermined bus stops was extensively collected and forecast. At first, the time stamp data was categorized to eliminate white noise, uncontrollable in forecasting, based on wavelet conversion. Then, the radial basis neural networks was applied to remaining data, which showed relatively accurate results. The success of the attempt was confirmed by the drastically reduced relative error when the nodes between the target intersections increases. In general, as the number of the nodes between target intersections increases, the relative error shows the tendency of sharp increase. The experimental results of the novel approaches, based on wavelet conversion and neural network teaming mechanism, showed the forecasting methodology is very promising.

• 한국도로학회논문집
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• 제18권4호
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• pp.83-92
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• 2016

PURPOSES : The purpose of this study was to develop safety performance functions (SPFs) that use zero-inflated negative binomial regression models for urban intersections in central business districts (CBDs), and to compare the statistical significance of developed models against that of regular negative binomial regression models. METHODS : To develop and analyze the SPFs of intersections in CBDs, data acquisition was conducted for dependent and independent variables in areas of study. We analyzed the SPFs using zero-inflated negative binomial regression model as well as regular negative binomial regression model. We then compared the results by analyzing the statistical significance of the models. RESULTS : SPFs were estimated for all accidents and injury accidents at intersections in CBDs in terms of variables such as AADT, Number of Lanes at Major Roads, Median Barriers, Right Turn with an Exclusive Turn Lane, Turning Guideline, and Front Signal. We also estimated the log-likelihood at convergence and the likelihood ratio of SPFs for comparing the zero-inflated model with the regular model. In he SPFs, estimated log-likelihood at convergence and the likelihood ratio of the zero-inflated model were at -836.736, 0.193 and -836.415, 0.195. Also estimated the log-likelihood at convergence and likelihood ratio of the regular model were at -843.547, 0.187 and -842.631, 0.189, respectively. These figures demonstrate that zero-inflated negative binomial regression models can better explain traffic accidents at intersections in CBDs. CONCLUSIONS : SPFs that use a zero-inflated negative binomial regression model demonstrate better statistical significance compared with those that use a regular negative binomial regression model.

• 한국도로학회논문집
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• 제13권4호
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• pp.143-150
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• 2011

원형교차로 중 회전교차로는 기존에 존재하였던 로터리의 형태와 유사한 형태의 교차로로서 최근 세계적으로 많이 설치되고 있으며 우리나라에서도 회전교차로에 대한 관심이 증가하고 있다. 그러나 도시부의 경우 회전교차로 운영 효율에 큰 영향을 미치는 요소 중 하나인 보행량에 대한 영향 분석은 미미하다. 따라서 본 연구에서는 보행량에 따른 회전교차로의 효율 분석 및 보행신호를 제시하였다. 첫째, 도시부 1차로 회전교차로의 용량을 분석하기 위해 VISSIM 시뮬레이션을 구성하였다. 둘째, VISSIM 시뮬레이션을 통해 보행량에 따라 신호가 없는 회전교차로와 신호가 있는 원형교차로로 구분하여 교차로의 평균차량 지체를 산정하였다. 끝으로, 이 연구에서 나타난 분석결과 도시부 회전교차로 설치시 보행량이 200명/시 이하인 경우 회전교차로가 적합하며 보행량이 200명/시 이상인 경우는 펠리컨 신호가 있는 원형교차로, 보행량이 600명/시가 높으면서 교통량이 1,500대/시 이상인 경우는 정주기식 신호가 있는 신호교차로가 적합한 것으로 나타났다.

• 대한교통학회지
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• 제29권5호
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• pp.79-89
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• 2011

최근에 들어 우리나라에서는 회전교차로에 대한 연구가 많이 진행되고 있으나, 대부분 회전교차로의 교통운영측면에서의 효과에 대한 연구가 주를 이루고 있고, 국외에 비해 교통안전측면 혹은 연속적인 회전교차로 설치를 포함한 다양한 회전교차로 도입방안 등에 대한 연구는 미흡한 실정이다. 더욱이 대부분의 회전교차로 건설이 개별교차로 별 개선을 위해 적용되고 있어 회전교차로의 축간 혹은 네트워크 차원에서의 운영효과는 간과되고 있다. 따라서 본 연구에서는 회전교차로 도입 시 교차로 운영상의 효과를 극대화시킬 수 있는 인접 교차로사이의 적정거리를 도출하고, 그 결과를 바탕으로 실제 도로네트워크에서 연속적인 회전교차로 도입 시의 네트워크 차원의 운영 효과를 분석하였다. 분석결과, 150m이내에 신호교차로가 있을 경우 회전교차로의 교통소통효과는 급격히 감소함이 분석되어 회전교차로 도입 시의 인접교차로와의 거리는 약 150m가 확보되어야 인접신호교차로의 영향을 감소시킬 수 있는 것으로 나타났다. 또한 인천시 논현지구를 대상으로 수행된 현장조사결과를 토대로 시뮬레이션 분석한 결과, 하나의 교차로만을 회전교차로로 전환할 경우보다 연속적으로 다수의 교차로를 회전교차로로 전환할 경우에 운영효과는 매우 높게 나타남을 확인할 수 있었다.

• 한국도로학회논문집
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• 제9권2호
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• pp.1-11
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• 2007

1970년대 이후 급속한 경제성장과자동차의 증가로 인해 도심지의 극심한 교통정체와 환경파괴의 문제가 대두되었다. 이러한 도시의 부정적 문제를 해결하기 위해서는 승용차위주의 교통수단을 승용차외의 대체교통수단으로 전환하는 것이 보다 효과적인 방법이라 할 수 있다. 이러한 관점에서 자전거는 환경친화적인 그린교통수단(Green Mode)으로 세계 각국에서는 각광받고 있고, 국내에서도 자전거의 이용률을 높이기 위한 다양한 시도가 이루어지고 있다. 본 연구에서는 자전거 이용의 활성화를 위해 우선적으로 고려되어져야 하는 안전성 측면에서 자전거 사고에 영향을 미치는 영향인자들에 대한 분석을 시도하였다. 자전거 사고의 안전성 분석을 위하여 비선형 회귀분석을 통해 사고모델을 개발하였고, 이들 개발된 모델들을 이용하여 자전거사고에 영향을 미치는 주요설명변수들에 대한 분석을 시도하였다. 모델분석결과, 포아송회귀분석(poisson regression)이 모델개발에 가장 적합한 것으로 나타났으며, 자전거 사고에 영향을 미치는 변수로는 교통량, 진출입구 수, 지형, 자전거도로, 학교, 주거지역, 교차로의 크기 버스정류장 등으로 분석되었다.

• 한국도로학회논문집
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• 제18권3호
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• pp.95-107
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• 2016

PURPOSES : This study compared two measures of traffic flow effectiveness on roads with roundabouts and signalized intersections and determined the more appropriate measure. METHODS : In addition to average delay time, the conventionally used measure, average travel time was introduced to measure traffic flow effectiveness because it is able to be obtained through field survey and reflect different travel distances and speed limits of roundabouts and signalized intersections. Using the two measures, roundabouts and signalized intersections were compared through simulations in terms of traffic flow effectiveness. RESULTS : For one-way single-lane roads, the two measures indicated consistent results that roundabouts were more effective than were signalized intersections when the traffic volume was less than 300 vphpl but vice versa when it exceeded 450 vphpl; however, the measures yielded inconsistent results when the volume was 350~400 vphpl. For one-way double-lane roads, the two measures indicated consistent results that roundabouts were more effective than were signalized intersections when the volume was less than 200 vphpl but vice versa when it exceeded 400 vphpl; however, the measures yielded inconsistent results when the volume was 250~350 vphpl. The results obtained using the two measures differed substantially for double-lane roads because behaviors such as weaving and lane changing at roundabouts are more common in double-lane roads than in single-lane roads. CONCLUSIONS : The average delay time would be lower on roads with roundabouts, but average travel time would be lower on roads with signalized intersections. Thus, evaluating the relative effectiveness of roads with roundabouts and signalized intersections by using average delay time alone would be inappropriate, whereas using average travel time as the evaluation index would yield fairer results.

• 한국컴퓨터정보학회논문지
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• 제17권11호
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• pp.19-26
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• 2012

교차로에서 가변차선은 이동하는 차량들을 효율적으로 통제하고 교통 혼잡을 줄일 수 있으며 도로의 가용 능력을 증가시키기 위한 도구로 사용되고 있다. 그러나 아직까지 가변차선의 교통통제는 단순하며 수동으로 가변차로를 운용하고 있다. 따라서, 본 연구에서는 가변차로의 이동방향에 대한 변경 여부를 지능적으로 판단하여 교통 흐름을 효율적으로 개선하기 위한 3단계 방법을 제안한다. 첫 번째는 교차로에서 차량이 이동하는 방향으로 효율성을 판단하기 위한 방법으로 퍼지추론 방법, 두 번째는 이동방향으로 가변차로를 변경할 지에 대한 잠정 판단, 세 번째는 이러한 잠정판단을 최종결정하기 위한 판단기준을 제시한다. 이동방향으로의 효율성은 matlab 프로그램을 이용하여 얻는다.