• Title/Summary/Keyword: Road Model

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Development of Life Cycle Cost Model & System of the Road Tunnel (지하도로시설물의 LCC예측 모델 및 시스템 개발)

  • 조효남;선종완;김충완;민대홍
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2004.10a
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    • pp.157-162
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    • 2004
  • Recently, Life Cycle Cost (LCC) for civil infrastructures, such as pavements, bridges, and dams, has been emphasized. However there are few cost models for road tunnel especially for maintenance phase. The road network is composed of highways, bridges, and road tunnels. Thus it is as important as for road tunnels to keep safe for traffic. The maintenance strategies for road tunnels can be achieved based on the minimization of LCC in maintenance phase. For this purpose, in this paper, cost model and cost classification for road tunnel in maintenance phase are suggested.

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A CFD Study of Roadside Barrier Impact on the Dispersion of Road Air Pollution

  • Jeong, Sang Jin
    • Asian Journal of Atmospheric Environment
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    • v.9 no.1
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    • pp.22-30
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    • 2015
  • This study evaluated road shape and roadside barrier impact on near-road air pollution dispersion using FLUENT computational fluid dynamics (CFD) model. Simulated road shapes are three types, namely at-grade, depressed, and filled road. The realizable k-${\varepsilon}$ model in FLUENT CFD code was used to simulate the flow and dispersion around road. The selected concentration profile results were compared with the wind tunnel experiments. The overall concentration profile results show good agreement with the wind tunnel results. The results showed that noise barriers, which positioned around the at-grade road, decrease the horizontal impact distance (In this study, the impact distance was defined as the distance from road surface origin coordinate to the position whose mass fraction is 0.1.) lower 0.33~0.65 times and change the vertical air pollution impact distance larger 2.0~2.27 times than those of no barrier case. In case of filled road, noise barriers decrease the horizontal impact distance lower 0.24~0.65 times and change the vertical air pollution impact distance larger 3.33~3.55 times than those of no barrier case. The depressed road increase 1.53~1.68 times the vertical air pollution impact distance. It contributes the decrease of horizontal air pollution impact distance 0.32~0.60 times compare with no barrier case.

Optimal Demand for Road Investment (도로부문의 적정 투자규모 추정)

  • 김의준
    • Journal of the Korean Regional Science Association
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    • v.13 no.2
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    • pp.75-92
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    • 1997
  • This paper is concerned with an estimation of optimal investment of road sector in 1996-2005. The main method is a Computable General Equilibrium (CGE) Model for Korea in which the optimal solution is derived in a recursively dynamic path. The model is composed of three main modules: the supply, the demand and the price. In this paper, the investment demand for the road is optimized with subject to national economic growth and price inflation. If the annual inflation level and the economic growth rate during 1996-2005 are set to 4.5%-5.0% and 6.0%-6.5% respectively, the optimal demand for the road investment is estimated as 155.1-180.1 trillion Won or 3.33%-3.89% of the GDP for ten years. It implies that the additional increase of the road investment by 0.61%-1.15% of the GDP is required for sustainable economic development, since the share of the road investment in the GDP of the latest 5 years has stayed around 2.27%. However, it is necessary to reduce construction investments on housing as well as to promote private financing of the road in order to maximize an efficiency of resource allocation.

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Optimal Road Maintenance Section Selection Using Mixed Integer Programming (혼합정수계획법을 활용한 도로포장 보수구간 선정 최적화 연구)

  • Cho, Geonyoung;Lim, Heejong
    • International Journal of Highway Engineering
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    • v.19 no.3
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    • pp.65-70
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    • 2017
  • PURPOSES : Pavement Management System contains the data that describe the condition of the road. Under limited budget, the data can be utilized for efficient plans. The objective of this research is to develop a mixed integer program model that maximizes remaining durable years (or Lane-Kilometer-Years) in road maintenance planning. METHODS : An optimization model based on a mixed integer program is developed. The model selects a cluster of sectors that are adjacent to each other according to the road condition. The model also considers constraints required by the Seoul Metropolitan Facilities Management Corporation. They select two lanes at most not to block the traffic and limit the number of sectors for one-time construction to finish the work in given time. We incorporate variable cost constraints. As the model selects more sectors, the unit cost of the construction becomes smaller. The optimal choice of the number of sectors is implemented using piecewise linear constraints. RESULTS : Data (SPI) collected from Pavement Management System managed by Seoul Metropolitan City are fed into the model. Based on the data and the model, the optimal maintenance plans are established. Some of the optimal plans cannot be generated directly in existing heuristic approach or by human intuition. CONCLUSIONS:The mathematical model using actual data generates the optimal maintenance plans.

A Study on Optimal Planning of Sustainable Rural Road Path based on Infrastructure for Green-Tourism and Public Service (그린투어리즘 및 공공서비스 기반의 지속가능한 농촌도로노선의 최적계획에 관한 연구)

  • Kim, Dae-Sik;Chung, Ha-Woo
    • Journal of Korean Society of Rural Planning
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    • v.11 no.1 s.26
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    • pp.1-8
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    • 2005
  • The purpose of this study is to develop a simulation model of rural road path for infrastructure of green-tourism and public service in rural areas. This study makes an objective function for moving cost minimization considering car travel time according to road characteristics, which can route the optimal shortest road paths between the center places and all rear villages, based on GIS coverages of road-village network for connecting between center places and rural villages as input data of the model. In order to verify the model algorithm, a homogeneous hexagonal network, assuming distribution of villages with same population density and equal distance between neighborhood villages on a level plane area, was tested to simulate the optimal paths between the selected center nodes and the other rear nodes, so that the test showed reasonable shortest paths and road intensity defined in this study. The model was also applied to the actual rural area, Ucheon-myun, which is located on Hoengsung-gun, Kangwon-do, with 72 rural villages, a center village (Uhang, 1st center place) in the area, a county conte. (Hoengsung-eup, 2nd center place), and a city (Wonju, 3rd center place), as upper settlement system. The three kinds of conte. place, Uhang, Hoengsung-eup, and Wonju, were considered as center places of three scenarios to simulate the optimal shortest paths between the centers and rural villages, respectively. The simulation results on the road-village network with road information about pavement and width of road show that several spans having high intensity of road are more important that the others, while some road spans have low intensity of road.

Developing Models for Patterns of Road Surface Temperature Change using Road and Weather Conditions (도로 및 기상조건을 고려한 노면온도변화 패턴 추정 모형 개발)

  • Kim, Jin Guk;Yang, Choong Heon;Kim, Seoung Bum;Yun, Duk Geun;Park, Jae Hong
    • International Journal of Highway Engineering
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    • v.20 no.2
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    • pp.127-135
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    • 2018
  • PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

A Study on Estimating Techniques of Road Traffic Capacity (가로교통용량 산정기법에 관한 연구)

  • 김대웅;임영길
    • Journal of Korean Society of Transportation
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    • v.6 no.1
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    • pp.43-53
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    • 1988
  • This study is to find the proper method of estimating urban road traffic capacity. To estimate road traffic capacity, the following methods are chosen ; 1) crossing point of Q-V and S-V, 2) critical velocity and density of Q-V-K model, 3) V-K model with density parameter. The density estimated through S-V relation is 174 veh./km. The methods used in this paper yields more stable values with 2286 veh./h/ in average. The estimated average capacity by three methods are 2272 veh./h. in multilane road. 2411 veh./h in three lane road and 2185 veh./h. in two lane road.

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Real Time Road Lane Detection with RANSAC and HSV Color Transformation

  • Kim, Kwang Baek;Song, Doo Heon
    • Journal of information and communication convergence engineering
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    • v.15 no.3
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    • pp.187-192
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    • 2017
  • Autonomous driving vehicle research demands complex road and lane understanding such as lane departure warning, adaptive cruise control, lane keeping and centering, lane change and turn assist, and driving under complex road conditions. A fast and robust road lane detection subsystem is a basic but important building block for this type of research. In this paper, we propose a method that performs road lane detection from black box input. The proposed system applies Random Sample Consensus to find the best model of road lanes passing through divided regions of the input image under HSV color model. HSV color model is chosen since it explicitly separates chromaticity and luminosity and the narrower hue distribution greatly assists in later segmentation of the frames by limiting color saturation. The implemented method was successful in lane detection on real world on-board testing, exhibiting 86.21% accuracy with 4.3% standard deviation in real time.

A Study on the Vehicle Dynamics and Road Slope Estimation (차량동특성 및 도로경사도 추정에 관한 연구)

  • Kim, Moon-Sik
    • Journal of the Korean Society of Industry Convergence
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    • v.22 no.5
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    • pp.575-582
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    • 2019
  • Advanced driving assist system can support safety of driver and passengers which may require vehicle dynamics states as well as road geometry. It is essential to have in real-time estimation of related variables and parameters. Among the road geometry parameters, road slope angle which can not be measured is essential parameter in pose estimation, adaptive cruise control and others on sag road. In this paper, Kalman filter based method for the estimation of the vehicle dynamics and road slope angle using a nonlinear vehicle model is proposed. It uses a combination of Kalman filter as Cascade Extended Kalman Filter. CEKF uses measured vehicle states such as yaw rate, longitudinal/lateral acceleration and velocity. Unknown vehicle parameters such as center of gravity and inertia are obtained by 2 D.O.F lateral model and experimentally. Simulation and Experimental tests conducted with commercialized vehicle dynamics model and real-car.

Estimation of Tire-Road Friction Coefficient using Observers (관측기를 이용한 노면과 타이어 간의 마찰계수 추정)

  • 정태영;이경수;송철기
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.6
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    • pp.722-728
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    • 1998
  • In this paper real-time estimation methods for identifying the tire-road friction coefficient are presented. Taking advantage of the Magic Formula Tire Model, the similarity technique and the specific model for the vehicle dynamics, a reduced order observer/filtered-regressor-based method is proposed. The Proposed method is evaluated on simulations of a full-vehicle model with an eight state nonlinear vehicle/transmission model and nonlinear suspension model. It has been shown through simulations that it is possible to estimate the tire-road friction from measurements of engine rpm, transmission output speed and wheel speeds using the proposed identification method. The proposed method can be used as a useful option as a part of vehicle collision warning/avoidance systems and will be useful in the implementation of a warning algorithm since the tire-road friction can be estimated only using RPM sensors.

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