• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.605-613
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• 2010

In this study, Impact factors are represented and barrier height of compact car road of safety barrier is suggested through the investigation of applying problems of existed standard of general car road. For this, traffic accidents analysis is performed and based on the analysis, impact vehicle weight, impact Angle, crash velocity, and barrier height are investigated. For the decision of impact angle, analysis is carried out by comparison of RISER and 2-lines expressway accidents data. Through this, higher-impact angle is suggested. Vehicle weight data of sub-compact car, small vehicle, medium and large vehicle, SUV, small truck is surveyed and analyzed. Based on the accident accumulation rate, regression analysis of vehicle weight impact and impact velocity is performed. Also, based on the cumulative rate of vehicle weight on expressways near Seoul, barrier height of compact car road is calculated. It is noted that the results of this study will be contributed to the decision of barrier type.

• Spatial Information Research
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• v.23 no.4
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• pp.79-89
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• 2015

This study aims to design and implement a traffic model that can simulate the traffic behavior on the microscopic level by using the GIS. In the design of the model, the vehicle in the simulation environment recognizes the GIS road centerline data as road network data reflecting number of lanes, speed limit and so on. In addition, the behavior model was designed by dividing functions into the environmental perception model, time headway distribution model, car following model, and lane changing model. The implemented model was applied to Jahamun-road of Jongno-gu district to verify the accuracy of the model. As a result, the simulation results on the Jahamun-road had no great error compared with the actual observation data. In the aspect of usability of model, it is judged that this model will be able to effectively contribute to analysis of amount of carbon emission by traffic, evaluation of traffic flow, plans for location of urban infrastructure and so on.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.108-120
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• 2008

This paper discusses the prediction of deforestation areas using probability models from forest census database, Geographic information system (GIS) database and the land cover database. The land cover data was analyzed using remotely-sensed (RS) data of the Landsat TM data from 1989 to 2001. Over the analysis period of 12 years, the deforestation area was about 40ha. Most of the deforestation areas were attributable to road construction and residential development activities. About 80% of the deforestation areas for residential development were found within 100m of the road network. More than 20% of the deforestation areas for forest road construction were within 100m of the road network. Geographic factors and vegetation change detection (VCD) factors were used in probability models to construct deforestation occurrence map. We examined the size effect of area partition as training area and validation area for the probability models. The Bayes model provided a better deforestation prediction rate than that of the regression model.

• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.42-48
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• 2023

In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.

• Journal of Environmental Science International
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• v.26 no.4
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• pp.521-527
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• 2017

Solar radiation forecasts are important for predicting the amount of ice on road and the potential solar energy. In an attempt to improve solar radiation predictability in Jeju, we conducted machine learning with various data mining techniques such as tree models, conditional inference tree, random forest, support vector machines and logistic regression. To validate machine learning models, the results from the simulation was compared with the solar radiation data observed over Jeju observation site. According to the model assesment, it can be seen that the solar radiation prediction using random forest is the most effective method. The error rate proposed by random forest data mining is 17%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.587-598
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• 2012

Successful implementation of infrastructure asset management system can be started with rich and reliable data. However, measurement errors in the data have always existed in the real world caused for many unknown reasons. It disturbs maintenance activities of agencies, and makes negative effects to reliability of research results on forecasting deterioration process and life cycle cost. Above all, it makes a contradiction that road agencies cannot believe their inspection data surveyed by their hands. It is particularly serious in the road pavement management field. Although road agencies are well recognized the fact, inspecting without measurement error would be a great challenge. Considering the facts, this paper aimed to suggest statistical error processing methods to correct latent error included in pavement surface inspection data. As alternatives, this paper suggested two methods based on probability distribution to consider structure of error and reliability of the data. The suggested methods were empirically tested by using pavement inspection data from Korean National Highway. As the result, this paper confirmed that conventional error processing that just removes only visible errors is not enough to cover uncertainty in pavement deterioration process. The suggested methods would be useful for improving reliability of analysis results required for road infrastructure asset management.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.152-161
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• 2022

Recently, it is recognized as a high-cost and inefficient logistics system that increases traffic congestion and environmental problems due to an increase in traffic volume due to the activation of the online market. In order to solve inefficient problems such as unavoidable traffic congestion and environmental problems caused by the increase in traffic volume, it is necessary to develop a freight transport system technology using the existing urban railway infrastructure and freight-only urban railway. The urban subway logistics system is a logistics system that requires a combination of various technologies to solve the nationwide demand for urban logistics and road traffic problems. This paper recognized the existing traffic congestion and environmental pollution of road traffic as problems, and supplemented the contact point requirements presented above by identifying the sub-systems constituting the target system and supplementary points for each part-level contact point. In this study, as a complex system operated for one purpose by grafting various technologies, a plan is required to secure the reliability and safety of operation from various viewpoints. The results of this study can contribute to the initial configuration and basic data to solve the interface bottleneck of the urban subway logistics system to be promoted in the future.

• Journal of Forest and Environmental Science
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• v.32 no.1
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• pp.1-9
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• 2016

Accessibility of urban green space, as an important index of evaluating the service level of urban green space, not only shows the resident's access to green space, but also reflects the environment quality of urban living. Since the quantity, area and space distribution of the patches in urban green space directly affect the function of urban green space and the quality of urban environment, the research on the accessibility of urban green space holds great significance to improve the service of urban green space and the living environment quality. Based on GIS software, this research uses the road network and the population distribution data of Nanjing's city proper to conduct quantitative analysis of the accessibility of park green space and the convenience for residents to travel under different forms of transportation. After the case analysis, the author tests the application of road network in studying the accessibility of urban park green space and proposes a GIS-based method to study the accessibility and the rational layout of urban green space.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1D
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• pp.73-82
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• 2011

Generally, an unsaturated condition was not considered to predict the long-term strength and drainage behaviors on compacted road foundations. However, it is logical way to consider the unsaturated condition and hysteresis behavior on road foundations like subbase and subgrade. For more quantitative analysis, rational experimental approach requires proper laboratory tool and material model, and hydraulic properties of pavement geomaterials under unsaturated conditions. In this study, therefore, laboratory data from the soil-water characteristic curve tests were used to predict suction and unsaturated permeability on pavement foundations and the results were analyzed based on the nonlinear fitting model considered. In addition to that, the unsaturated moisture capacity of each material is discussed.

• Journal of Forest and Environmental Science
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• v.18 no.1
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• pp.7-14
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• 2001

On the basis of data obtained from forest road collapsed due to a heavy rainfall, this study carried out to evaluate the cutting slope failure factors of forest road by using Quantification theory(II). The results were summarized as follows. The factors on cutting slope failure was ranked in the order of cutting slope length, soil type, aspect, cutting slope gradients and slope gradients. And the slope failure was mainly occurred under such conditions as cutting slope length longer than 8m, soil type with soil, aspect of N, cutting slope gradients steeper than 600 and slope gradients greater than $35{\sim}40^{\circ}$.