• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.163-175
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• 2002

Fatalities from traffic accidents constitute one of the major health issues as well as safety ones in Korea. It has been reported that traffic accident is affected by the combined effects of road. vehicle. and human factors. Over the past few decades, a number of studies have been conducted to find the impact of road geometric factors on traffic safety. The purpose of this study is to investigate the effect of road geometric factors on traffic safety on Korean expressways. Detailed geometric design data were available from Korea Highway Corporation. Five-year traffic accident data on Honam expressway were collected and analyzed. It was found that following geometric factors influence traffic safety on expressways : radius of curve, curve length, and length of straight section. Furthermore, the existence of I.C. turned out to have a significant impact on traffic safety level. Based on the data analysis several multiple regression forms that relate traffic accident frequencies and geometric factors on expressways are developed.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.63-70
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• 2003

Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.59-67
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• 2008

In this paper we propose an algorithm to extract the license plate regions from Korean car images. The idea of this paper is that we first find the four digits in the input car image and then segment the plate region using the digit information. Out method has advantage of segmenting simultaneously the plate regions and four digits regions. The first step finds and groups the connected components with proper sizes as candidate digits. The second step applies an serial alignment condition to find out probable 4-digits. In the third step, we recognize the candidate digits and assign the confidence values to each of them. The final step extracts the license plate region which has the highest confidence value. We used the Perfect Metrics classification algorithm to estimate the confidence. In our experiment, we got 97.23% and 95.45% correct detection rates, 0.09% and 0.11% false detection rates for 4,600 daytime and 264 nighttime images, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.45-58
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• 2021

It is generally known that a two-lane roundabout has some problems in safety such as increasing conflicts, typically merging and diverging conflicts and conflicts between entering traffic and exiting as well as turning traffic. To solve these problems, a turbo-roundabout had been developed and has successfully brought safer and more efficient operation in other countries. In this study, micro simulations using VISSIM were conducted to investigate the maximum value of service traffic volume. It was found that operation of turbo-roundabouts was influenced by traffic volume for each turning traffic, and the maximum values of traffic volume were values between 2,400 and 2,800 vehicles per hour as rates of traffic volume for each turning traffic. Typically, turbo-roundabouts have limited to operate in conditions with more than 30% for left-turning traffic volume.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.20-29
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• 2021

In the Industry 4.0 era, artificial intelligence has attracted considerable interest for learning mass data to improve the accuracy of forecasting and classification. On the other hand, the current method of detecting anomalies relies on traditional statistical methods for a limited amount of data, making it difficult to detect accurate anomalies. Therefore, this paper proposes an artificial intelligence-based anomaly detection methodology to improve the prediction accuracy and identify new data patterns. In particular, data were collected and analyzed from the point of view that sensor data collected at vehicle idle could be used to detect abnormalities. To this end, a sensor was designed to determine the appropriate time length of the data entered into the forecast model, compare the results of idling data with the overall driving data utilization, and make optimal predictions through a combination of various sensor data. In addition, the predictive accuracy of artificial intelligence techniques was presented by comparing Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) as the predictive methodologies. According to the analysis, using idle data, using 1.5 times of the data for the idling periods, and using CNN over LSTM showed better prediction results.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.113-130
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• 2002

In this paper, we developed DNL(Dynamic Network Loading) model based on Moving cell theory to analyze the dynamic characteristics of traffic flow in congested network. In this paper vehicles entered into link at same interval would construct one cell, and the cells moved according to Cell following rule. In the past researches relating to DNL model a continuous single link is separated into two sections such as running section and queuing section to describe physical queue so that various dynamic states generated in real link are only simplified by running and queuing state. However, the approach has some difficulties in simulating various dynamic flow characteristics. To overcome these problems, we present Moving cell theory which is developed by combining Car following theory and Lagrangian method mainly using for the analysis of air pollutants dispersion. In Moving cell theory platoons are represented by cells and each cell is processed by Cell following theory. This type of simulation model is firstly presented by Cremer et al(1999). However they did not develop merging and diverging model because their model was applied to basic freeway section. Moreover they set the number of vehicles which can be included in one cell in one interval so this formulation cant apply to signalized intersection in urban network. To solve these difficulties we develop new approach using Moving cell theory and simulate traffic flow dynamics continuously by movement and state transition of the cells. The developed model are played on simple network including merging and diverging section and it shows improved abilities to describe flow dynamics comparing past DNL models.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.38-38
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• 2011

일반적으로 레일마모는 열차의 주행안전 및 승차감에 미치는 영향이 크고, 소음 진동의 주요원인으로 작용한다. 또한 레일마모가 발생할 경우 궤도구조의 파괴를 촉진시킴으로써 차량 및 궤도유지보수비를 크게 증가시킨다. 따라서 구간 특성 및 환경 영향 인자 등 현장에서 발생하는 마모 원인을 체계적으로 분석함으로써 마모를 저감할 수 있도록 차량운행 조건과 선로선형 및 궤도구조를 설계하는 것은 중요한 과제이다. CART(Classification And Regression Tree; 분류와 회귀나무) 분석은 패키지화된 좋은 분류 및 예측도구 기법으로 나무의 상위 분리수준에서 일반적으로 나타나는 가장 중요한 입력변수들을 사용하는 등의 입력변수를 선정하는 경우 매우 유용하다. 본 연구에서는 다변수 구간특성 및 환경인자를 고려한 검측 자료 상관관계 분석을 위한 회귀 나무기반 모델(TBM: Tree Based Model) 분석 수행을 위해 지하철 2호선 마모 데이터와 마모 데이터에 영향을 미치는 각종 다변수 구간특성 및 환경인자를 사용하였다. 2호선 지하철의 구간특성 인자 및 환경인자는 레일의 종류, 레일의 위치, 도상, 곡률반경, 캔트 슬랙 및 운행 일수 등으로 구분하였다. 레일의 종류는 ks-50kg과 ks-60kg 두 종류의 레일이 있으며, 레일의 위치는 지상과 지하로 크게 구분할 수 있다. 도상은 콘크리트 도상, 자갈 도상과 일부 구간의 방진상 콘크리트 도상으로 구분할 수 있으며, 곡률반경은 직선구간과 완화곡선 구간 및 최소 250m부터 627m까지 분포된 원 곡선 구간으로 구분할 수 있다. 캔트 간격은 최소 96cm 부터 120cm 간격으로 구분하며, 슬랙은 5~9cm에 분포하고, 운행 기간은 해당 기간 동안 유지보수 이력이 없는 구간을 선정하여 2005년부터 2006년까지 4번에 걸쳐 검측된 지하철 2호선 내선 마모데이터를 사용하였다. 총 X1부터 X7까지 총 7개의 구간특성 또는 환경특성을 영향인자로 선정하였으며, 이러한 영향인자에 의해 결정되는 종속 인자로 Y1인 직마모와 Y2인 측마모를 선정하여 이 중 실질적으로 지하철 궤도의 성능 평가에 주요 판단인자로 사용되는 측마모와 구간특성 및 환경영향인자와의 상관관계 분석을 수행하였다. 해당 마모 데이터가 검측되는 기간 동안 유지보수 이력이 없는 12272 point의 데이터를 검출하였고 CART 프로그램을 이용하여 데이터를 분석하였으며, CART 프로그램의 해석을 위해 종속변수인 직마모량은 각 검측 지점의 마모량에 해당하는 등급으로 변환하여 분석을 수행하였다. 레일의 마모에 영향을 미치는 구간특성 및 환경인자와 종속 변수로 사용된 레일의 마모량 사이의 CART를 이용한 상관관계 분석은 실제 구조물에서 영향인자간의 상관 관계와 유사하며, 추후 연구에서는 이를 바탕으로 하여 정량화된 검측 데이터를 종속변수로 하여 구간특성 또는 환경인자 등 외부 영향인자를 고려한 궤도 검측데이터와의 상관관계 분석을 수행할 계획이다.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.85-97
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• 2003

This study was aimed at suggest a proper logging method of mountain forest using geographic information system(GIS) based on digital terrain model(DTM) in the National Forest at Mt. Kumsan in Namhae-gun, Gyungsangnam-do, which has about 2,948 ha in area. The areal percentage of 201 to 250m in the elevation was about 15.5%, elevation of 251 to 300m was 14.5%, and 78.75% for higher than 400m. The accumulated areal percentage of below 30% in the gradient was 17.2%, and 81.0% for steeper than 60%. The area for tractor skidding was 17.2%(511.7ha), the area for tractor attached winch skidding was 63.8%(1,896.3ha) and 18.4%(545.5ha) for cable yarding. It is important to choose the proper logging machines for timber harvesting. In general, the selection of logging operation system was affected several major environmental factors like as terrain conditions(slope gradient, slope length) and stand factors. The rate of middle slope gradients in terrain conditions showed higher than that of steep slope gradients in this area. Therefore, it considered that the logging operation system in this area could apply to tractor+winch operating machine according to terrain conditions.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.157-164
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• 2005

Urban conditions such as underground facilities and ambient noises due to cultural activity restrict the application of conventional geophysical techniques in general. We used the refraction microtremor (REMI) technique as an alternative way to get the geotechnical information, in particular shear-wave (S-wave) velocity information, at a site along an existing rail road. The REMI method uses ambient noises recorded using standard refraction equipment to derived shear-wave velocity information at a site. It does a wavefield transformation on the recorded wavefield to produce Rayleigh wave dispersion curve, which are then picked and modeled to get the shear-wave velocity structure. At this site the vibrations from the running trains provided strong noise sources that allowed REMI to be very effective. REMI was performed along the planned new underground rail tunnel. In addition, Suspension PS logging (SPS) were carried out at selected boreholes along the profile in order to draw out the quantitative relation between the shear wave velocity from the PS logging and the rock mass rating (RMR) determined from the inspection of the cores recovered from the same boreholes, These correlations were then used to relate the shear-wave velocity derived from REMI to RMR along the entire profile. The correlation between shear wave velocity and RMR was very good and so it was possible to estimate the RMR of the total zone of interest for the design of underground tunnel,

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.108-113
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• 2006

Urban conditions, such as existing underground facilities and ambient noise due to cultural activity, restrict the general application of conventional geophysical techniques. At a tunnelling site in an urban area along an existing railroad, we used the refraction microtremor (REMI) technique (Louie, 2001) as an alternative way to get geotechnical information. The REMI method uses ambient noise recorded by standard refraction equipment and a linear geophone array to derive a shear-wave velocity profile. In the inversion procedure, the Rayleigh wave dispersion curve is picked from a wavefield transformation, and iteratively modelled to get the S-wave velocity structure. The REMI survey was carried out along the line of the planned railway tunnel. At this site vibrations from trains and cars provided strong seismic sources that allowed REMI to be very effective. The objective of the survey was to evaluate the rock mass rating (RMR), using shear-wave velocity information from REMI. First, the relation between uniaxial compressive strength, which is a component of the RMR, and shear-wave velocity from laboratory tests was studied to learn whether shear-wave velocity and RMR are closely related. Then Suspension PS (SPS) logging was performed in selected boreholes along the profile, in order to draw out the quantitative relation between the shear-wave velocity from SPS logging and the RMR determined from inspection of core from the same boreholes. In these tests, shear-wave velocity showed fairly good correlation with RMR. A good relation between shear-wave velocity from REMI and RMR could be obtained, so it is possible to estimate the RMR of the entire profile for use in design of the underground tunnel.