• Title/Summary/Keyword: road network structure

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A Position Revision Method by Path-Loss Factor in GIS based Wireless Sensor Node Deployments (GIS기반 무선 센서노드 배치에서 경로손실을 고려한 위치 보정 방법)

  • Bae, Myung-Nam;Kwon, Hyuk-Jong;Kang, Jin-A;Lee, In-Hwan
    • Spatial Information Research
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    • v.19 no.6
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    • pp.111-121
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    • 2011
  • In this paper, we proposes a sensor node positioning algorithm that utilizes the geo-spatial elements and considers the factors to represent the propagation loss generated by the various obstacles in the urban wireless environments. First, we measures the propagation loss about the radio frequencies in major road of the urban, and defines the correlation between the measured loss and the environment information for the road and its surrounding get from Urban GIS. Secondly, through the utilization of the loss-environment correlation, we describes the detailed instruction for requiring the radio coverage decision and deploy system implementation for the wireless sensor node in urban. By the consideration of interference factor by the building and the linear structure of road, we can evaluate the path loss below 5dB RMS error. And, we proposes the way to revise the sensor node deployment based on the corelation and the measured path loss.

Selection method of public transportation vulnerable area using GIS buffering analysis (GIS Buffering기법을 이용한 대중교통취약지구 선정방법)

  • Kim, Yeon-Woong;Chang, Sung-Bong;Jang, Gwang-Woo;Park, Min-Kyu
    • Proceedings of the KSR Conference
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    • 2011.10a
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    • pp.1739-1742
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    • 2011
  • Public transportation network in our country is concentrated and advanced focusing on urban area in order to secure economic feasibility. As a result, as dependence on private vehicles is relatively getting higher in public transportation vulnerable area, traffic problem occurs since the average running speed in urban area is 22.5km/h. This paper has an objective to suggest an improvement plan by selecting public transportation vulnerable area, and defining according to urban structure, formation and function, and understand traffic characteristics and draw problems. As a method selecting public transportation vulnerable area, an area with high division rate of vehicle was selected as a primary proposed site by calculating division rate of means of public transportation according to area. Final proposed site was selected by using GIS Buffering technique aiming at selected proposed site, and selecting non-benefit area 500m outside, which is the road limit distance from each subway and bus station. Lastly, the degree of improvement effect was studied by constructing imaginary public transportation network aiming at final proposed site and comparing to the amount of change in division rate of means of transportation.

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A Traffic Flow Micro-simulation System Using Cellular Automata (CA모형을 이용한 미시적 교통류 시뮬레이션 시스템 개발에 관한 연구)

  • 조중래;고승영;김진구;김채만
    • Journal of Korean Society of Transportation
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    • v.19 no.3
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    • pp.133-144
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    • 2001
  • The purpose of this study is to develop micro simulation model for large-scale network with driver's behavior model. This study is performed for uninterrupted flow road section. And this model is developed to simulate traffic flow of the real network with unique geometric structure. The vehicle transmission and drivers' behavior model based on the exiting Cellular Automata approach.

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Improvement of Multivariable, Nonlinear, and Overdispersion Modeling with Deep Learning: A Case Study on Prediction of Vehicle Fuel Consumption Rate (딥러닝을 이용한 다변량, 비선형, 과분산 모델링의 개선: 자동차 연료소모량 예측)

  • HAN, Daeseok;YOO, Inkyoon;LEE, Suhyung
    • International Journal of Highway Engineering
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    • v.19 no.4
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    • pp.1-7
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    • 2017
  • PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

A Historical Review of Socio-economic Changes of Railroad (철도가 가져온 사회경제적 변화에 관한 정성적 연구)

  • Lee, Yong-Sang
    • Journal of the Korean Society for Railway
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    • v.12 no.5
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    • pp.778-787
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    • 2009
  • This paper illustrates some examples of socio-economic changes brought about by railroads in Korea. The Korean railroad network has been running for 110 years since it started operation in 1899. The opening of railroad system in Korea has had a huge influence on its society, not only transportation but also in the development of infrastructure and formation of new cities, such as Daejeon Metropolitan City, which were built along with the rail network. This paper will examine some examples of the influence that railroads have had on Korean society: the changes of transport route from road to railroad, the emergence of new cities, industries and culture. Also, this paper will look over the various functions of railroads in Korea, and then it compares with those of foreign countries. It gives us chance to examine a specificity as well as universality in the function of railroads.

A Method of Data Transmission for Performance Improvement of Real Time GNSS Data Processing in Multi-Reference Network Station (다중 수신국 실시간 위성항법데이터 처리 성능향상을 위한 데이터 송·수신 설계)

  • Kim, Gue-Heon;Son, Minhyuk;Lee, Eunsung;Heo, Moon-Beom
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.20 no.4
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    • pp.39-44
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    • 2012
  • This paper propose a transmission method for "Transportation system" that can decide precise position under wide area road traffic environment. For precise position detecting, central station collect multiple receiver station's satellite navigation data and generate correction information. In this process, we need efficient real time transmission method for satellite navigation message that has variable data size. We propose real time data transmission method. This real time transmission method offer efficient processing structure for multiple receiver station's satellite navigation message. This paper explains proposed real time transmission method and proofs this transmission method.

A Study on Data Model Migration for Transportation Digital Map to be available as a Raw Database of Car Navigation System (차량 항법용 원도로 활용하기위한 교통 주제도 데이터 모델 전환에 관한 연구)

  • Hahm, Chang-Hahk;Joo, Yong-Jin
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.3
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    • pp.67-74
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    • 2010
  • The aim of this paper is to come up with a methodology of migration for current transportation digital map in order to construct NDRM, which is the most essential map data for car navigation system. The model suggested through our study is able to efficiently produce navigable service map for route finding and guidance as well as to make the best of general road network developed by KOTI.

Lane Detection System using CNN (CNN을 사용한 차선검출 시스템)

  • Kim, Jihun;Lee, Daesik;Lee, Minho
    • IEMEK Journal of Embedded Systems and Applications
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    • v.11 no.3
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    • pp.163-171
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    • 2016
  • Lane detection is a widely researched topic. Although simple road detection is easily achieved by previous methods, lane detection becomes very difficult in several complex cases involving noisy edges. To address this, we use a Convolution neural network (CNN) for image enhancement. CNN is a deep learning method that has been very successfully applied in object detection and recognition. In this paper, we introduce a robust lane detection method based on a CNN combined with random sample consensus (RANSAC) algorithm. Initially, we calculate edges in an image using a hat shaped kernel, then we detect lanes using the CNN combined with the RANSAC. In the training process of the CNN, input data consists of edge images and target data is images that have real white color lanes on an otherwise black background. The CNN structure consists of 8 layers with 3 convolutional layers, 2 subsampling layers and multi-layer perceptron (MLP) of 3 fully-connected layers. Convolutional and subsampling layers are hierarchically arranged to form a deep structure. Our proposed lane detection algorithm successfully eliminates noise lines and was found to perform better than other formal line detection algorithms such as RANSAC

Multi-objective optimization of submerged floating tunnel route considering structural safety and total travel time

  • Eun Hak Lee;Gyu-Jin Kim
    • Structural Engineering and Mechanics
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    • v.88 no.4
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    • pp.323-334
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    • 2023
  • The submerged floating tunnel (SFT) infrastructure has been regarded as an emerging technology that efficiently and safely connects land and islands. The SFT route problem is an essential part of the SFT planning and design phase, with significant impacts on the surrounding environment. This study aims to develop an optimization model considering transportation and structure factors. The SFT routing problem was optimized based on two objective functions, i.e., minimizing total travel time and cumulative strains, using NSGA-II. The proposed model was applied to the section from Mokpo to Jeju Island using road network and wave observation data. As a result of the proposed model, a Pareto optimum curve was obtained, showing a negative correlation between the total travel time and cumulative strain. Based on the inflection points on the Pareto optimum curve, four optimal SFT routes were selected and compared to identify the pros and cons. The travel time savings of the four selected alternatives were estimated to range from 9.9% to 10.5% compared to the non-implemented scenario. In terms of demand, there was a substantial shift in the number of travel and freight trips from airways to railways and roadways. Cumulative strain, calculated based on SFT distance, support structure, and wave energy, was found to be low when the route passed through small islands. The proposed model helps decision-making in the planning and design phases of SFT projects, ultimately contributing to the progress of a safe, efficient, and sustainable SFT infrastructure.

A Character Analysis of the Woodland Edge in point of Landscape Ecology (수림가장자리의 경관생태적 특성분석)

  • Cho, Hyun-Ju;Ra, Jung-Hwa
    • Current Research on Agriculture and Life Sciences
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    • v.25
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    • pp.13-18
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    • 2007
  • The aim of this research is to set improvement guidance a character analysis of woodland edge to cope with the ecological dysfunction of woodland which was caused by massive development project and thoughtless development in country areas. The summary of research result are as follows. 1) From the result of landscape ecology characteristic analysis of woodland in all seven research sites, to begin with, in proportion of appearance by vegetation layer and condition of composition, site 5 showed to be most satisfactory. 2) A width of woodland edge was revealed 7.5m as a minimum, 17.0m as a maximum, and 11.4m as a average and minimum edge was set as 10m according to integrated analysis on each example place. 3) As a result of flexibility analysis, site 1, 2 and 5 was shown high value 3, and it is thought that curve rather than linearity should be maintained in order to increase the ecological function. Also, a phenomenon of straight was prominent, and as a woodland edge, green network and buffering system showed to be somewhat unsatisfactory. 4) Based on the result of character analysis of landscape ecology, main guidelines for improvement of woodland edge were categorized into five in parallel structure and three in vertical structure respectively. The guidelines for improvement of woodland edge suggested by the research has a deep meaning in that it is used as a basic material to induce for controling more systematically or landscape-friendly the defamed forest problems caused by road construction, various development projects, and enlargement of agricultural lands.

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