• 정보통신설비학회논문지
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• 제8권4호
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• pp.170-181
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• 2009

When a slow-moving vehicle occupies one of the lanes of a multi-lane highway, it often causes queuing behind, unlike one is caused by an actual stoppage on that lane. This happens when the traffic flow rate upstream from the slow vehicle exceeds a certain critical value. This phenomena is called as the Moving Bottleneck, defined by Gazis and Herman (1992), Newell (1998) [3], and Munoz and Daganzo (2002), who conducted the flow estimates of upstream and downstream and considered slow-moving vehicle speed and the flow ratio exceeding slow vehicle and the microscopic traffic flow characteristics of moving bottleneck. But, a study of delay on moving bottleneck was not conducted until now. So this study provides a average delay time model related to upstream flow and the speed of slow vehicle. We have chosen the two-lane highway and homogeneous traffic flow. A slow-moving vehicle occupies one of the two lanes. Average delay time value is a result of AIMSUN[9], the microscopic traffic flow simulator. We developed a multiple regression model based on that value. Average delay time has a high value when the speed of slow vehicle is decreased and traffic flow is increased. Conclusively, the model is formulated by the negative exponential function.

• 산업공학
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• 제23권4호
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• pp.349-356
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• 2010

The role of Intelligent Transportation System (ITS) is to efficiently manipulate the traffic flow and reduce the cost in logistics by using the state of the art technologies which combine telecommunication, sensor, and control technology. Especially, the hardware part of ITS is rapidly adapting to the up-to-date techniques in GPS and telematics to provide essential raw data to the controllers. However, the software part of ITS needs more sophisticated techniques to take care of vast amount of on-line data to be analyzed by the controller for their decision makings. In this paper, the authors develop a traffic congestion prediction model based on several different parameters from the sensory data captured in the Vehicle Detection System (VDS). This model uses the neural network technology in analyzing the traffic flow and predicting the traffic congestion in the designated area. This model also validates the results by analyzing the errors between actual traffic data and prediction program.

• 산업공학
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• 제12권4호
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• pp.625-634
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• 1999

On this study we selected some variable which affect on the estimated of the voice traffic, and estimated daily average traffic by years according to the variables. We applied nonlinear growth curve model to future traffic forecast with estimated historical traffic data. As a result of the forecasting, this study investigates the year in which the internet traffic goes far than the voice traffic.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.1931-1936
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• 2007

Demand forecasting for railroad traffic is fairly important to establish future policy and plan. The future demand of railroad traffic can be predicted by analyzing the demand of air, marine and bus traffic which influence the demand of railroad traffic. In this study, forecasting the demand of railroad traffic is implemented through neural network using the demand of air, marine and bus traffic. Estimate accuracy of the demand of railroad traffic was shown about 84% through neural net model proposed.

• 한국소음진동공학회논문집
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• 제25권4호
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• pp.284-290
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• 2015

Road traffic noise is closely related with urban forms and urban components, such as population, building, traffic and land-use, etc. Hence, it is possible to minimize the noise exposure problem depending on how to plan new town or urban planning alteration. This paper provides ways to apply for urban planning in consideration of noise exposure through road traffic noise estimation for alteration of small-scale urban form. Spatial autoregressive model from the former study is used as statistical model for noise simulation. The simulation results by the spatial statistical model are compared with those by the engineering program-based modeling for 5 scenarios of small-scale urban form alteration. The error from the limitation of containing informations inside the grid cell and the difficulties of reflecting acoustic phenomena exists. Nevertheless, in the stage of preliminary design, the use of the statistical models that have been estimated well could be useful in time and economically.

• 전자공학회논문지A
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• 제32A권8호
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• pp.31-38
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• 1995

In this paper, we consider the leaky bucket parameter dimensioning problem in the presence of the cell delay variation(CDV) which arises at the customer premises network dud to the multiplexing with other traffic streams. We consider an ATM multiplexer in which a single CBR stream and several heterogeneous VBR traffic streams are multiplexed. Choosing an MMPP model for the bursty traffic streams, we derive an (MMPP+DD)/D/1/K queueing model for the evaluation of the CDV experienced by the CBR stream. We first evaluate the equilibrium queue length distribution embedded at tagged-cell arrival-time instants, based on whcih we calcuate the inter-cell time distribution and the distribution kof the number of tagged-cell departures in an arbitrary interval. Then we apply the analysis to the dimensionging problem of the leaky bucket parameters, examining how the employed traffic model affects the determination of the bucket size. Through numerical examples, we confirm that the Poisson traffic model can underestimate the bucket size, thus causing a considerable blocking probability for compliant use cells while the MMPP model can optimally design the bucket size which keeps the blocking probability under the target value.

• 한국도로학회논문집
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• 제17권3호
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• pp.117-124
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• 2015

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 ${\chi}^2/df$, 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.

• 한국콘텐츠학회논문지
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• 제10권5호
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• pp.351-359
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• 2010

최근 들어, 유비쿼터스 기술을 활용한 U-시티의 관심이 증대되고 있는 가운데 많은 산업분야에서 이를 활용하여 사람들의 삶의 질을 향상시키고 있다. 다양한 U-시티 서비스 중에서도 교통 분야 서비스는 다른 U-시티 서비스 중에서도 가장 활발히 적용되고 있다. 본 연구에서는 교통 분야 중에서도 유비쿼터스 기술을 이용하여 교통정보제어 서비스를 위한 비즈니스모델과 비즈니스 모델 프로세스를 제안하고자 한다. 이를 위해, 기존의 비즈니스 모델에 대해 살펴보고 교통정보제어서비스가 무엇인지를 알아보았다. 또한, 비즈니스 모델을 도출하기 위해 대표 서비스를 이용하여 시나리오를 제시하였다. 제시한 시나리오를 기반으로, 유비쿼터스 기술을 활용한 U-교통정보제어서비스의 비즈니스 모델 프로세스를 도출하였다. 본 연구 결과, 교통정보제어서비스에서 4개의 대표 서비스를 도출하였다. 도출된 세부 서비스에서 이해 관계자, 수익자, 수익가치 모델을 도출하여 유비쿼터스 기술을 활용한 U-교통정보제어서비스의 비즈니스 모델을 도출하였다.

• 대한토목학회논문집
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• 제29권3D호
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• pp.329-334
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• 2009

차량들의 차량추종과 차로변경에 행태에 의해 차량 교통류는 다양한 형태를 보이게 되며, 차로변경의 행태에 따라 차로이용률은 매우 다양하게 나타난다. 따라서 미시적 차량 모의실험을 이용하여 다양한 교통류를 설명하기 위해서는 차량추종과 더불어 다양한 차로이용 행태를 구현하는 차로변경 모형이 필수적이다. 국내의 경우 차량추종모형에 대한 연구는 보고되고 있으나 차로변경모형에 대한 연구는 미흡한 실정이다. 따라서 본 연구에서는 대규모 고속도로망 모의실험에 적합한 CA(Cellular Automata)모형을 기반으로 미시적 2차로 차로변경모형을 개발하였다. 개발된 모형을 기존의 CA 차량추종모형과 결합하여 모의실험을 수행한 결과, 다양한 차로이용률 행태를 설명하는 것으로 분석되었다. 개발된 차로변경모형은 보다 다양한 고속도로 교통류의 모의실험에 활용될 것으로 기대된다.

• 대한안전경영과학회지
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• 제13권1호
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• pp.91-98
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• 2011

We develop a model to predict traffic accidents in Korea. In contrast to the classical approach that mainly uses regression analysis, Bayesian approach is adopted. A dependent model that incorporates the data from different kinds of accidents is introduced. The rate of severe accident can be updated even with no data of the same kind. The data of minor accident that can be obtained frequently is efficiently used to predict the severe accident.