• Korea Trade Review
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• v.47 no.2
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• pp.175-193
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• 2022

This study analyzes the effects of road transportation networks on the local economy in korea. The analysis methods are SNA and spatial panel regression model. The subjects of this study are inland areas of Korea, and the research period is from 2010 to 2019. The network analysis showed that the connection centrality of Gyeongg-do was high internally and externally. Gyeonggi-do has played a central role in the domestic road freight transportation industry. The results of spatial panel regression analysis showed that there was economic competition between regions. Domestic road transportation industry has been competitive among regions and has economic ripple effect. And Internal cargo has been shown to boost the economy of the region. But internal cargo has been shown to lower the economy of surrounding regions, but external cargo has been shown to increase the economy. In order to revitalize the local economy, it is necessary to increase road cargo.

• Journal of the military operations research society of Korea
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• v.11 no.2
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• pp.40-52
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• 1985

This paper presents an algorithm to develop network models for road intersections. These models represent microscopic traffic movement in the intersections, and thus can be used to computerize the road data for a detailed analysis or simulation.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.43-52
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• 2023

The paper aims to clarify how to make a decision using geographic information systems and how to choose the best route between two cities to suit the expectations of the driver and his sense of safety and comfort on the road. Use a special model for network analysis, where the network analysis tool relied on the following data (maximum speed of the road - number of intersections - road width - peak period) in choosing the best safe path. The paper concluded that the best safe route for refugees between the cities of Khartoum - Arqin crossing is ( Khartoum - Shendi - Atbara - Meroe - Abu Hamad - Wadi Halfa). We advise all GIS users to use the theories of spatial analysis when creating a new model.

• Korean Journal of Remote Sensing
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• v.20 no.1
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• pp.57-64
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• 2004

In GIS-based network analysis, topological measure of network structure can be considered as one of important factors in the urban transportation analysis. Related to this measure, it is known that the connectivity indices such as alpha index and gamma index, which mean degree of network connectivity and complexity on a graph or a circuit, provide fundamental information. On the other hand, shimbel index is one of GIS-based spatial metrics to characterize degree of network concentration. However, the approach using these quantitative indices has not been widely used in practical level yet. In this study, an application program, in complied as extension, running on ArcView- GIS is implemented and demonstrated case examples using basic layers such as road centerline and administrative boundary. In this approach, geo-spatial imagery can be effectively used to actual applications to determine the analysis zone, which is composed of networks to extract these indices. As the results of the implementation and the case examples, it is notified that alpha and gamma indices as well as shimbel index can be used as referential data or auxiliary information for urban planning and transportation planning.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3369-3385
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• 2019

There are various research challenges in vehicular ad hoc networks (VANETs) that need to be focused until an extensive deployment of it becomes conceivable. Design and development of a scalable routing algorithm for VANETs is one of the critical issue due to frequent path disruptions caused by the vehicle's mobility. This study aims to provide a novel road-aware routing protocol for vehicular networks named as Two-level hierarchical Hybrid Road-Aware (THERA) routing for vehicular ad hoc networks. The proposed protocol is designed explicitly for inter-vehicle communication. In THERA, roads are distributed into non-overlapping road segments to reduce the routing overhead. Unlike other protocols, discovery process does not flood the network with packet broadcasts. Instead, THERA uses the concept of Gateway Vehicles (GV) for the discovery process. In addition, a route between source and destination is flexible to changing topology, as THERA only requires road segment ID and destination ID for the communication. Furthermore, Road-Aware routing reduces the traffic congestion, bypasses the single point of failure, and facilitates the network management. Finally yet importantly, this paper also proposes a probabilistical model to estimate a path duration for each road segment using the highway mobility model. The flexibility of the proposed protocol is evaluated by performing extensive simulations in NS3. We have used SUMO simulator to generate real time vehicular traffic on the roads of Gangnam, South Korea. Comparative analysis of the results confirm that routing overhead for maintaining the network topology is smaller than few previously proposed routing algorithms.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.273-279
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• 2022

Owing to the need to establish a cooperative-intelligent transport system (C-ITS) environment in the transportation sector locally and abroad, various research and development efforts such as high-tech road infrastructure, connection technology between road components, and traffic information systems are currently underway. However, the current central control center-oriented information collection and provision service structure and the insufficient road infrastructure limit the realization of the C-ITS, which requires a diversity of traffic information, real-time data, advanced traffic safety management, and transportation convenience services. In this study, a network construction method based on the existing received signal strength indicator (RSSI) selected as a comparison target, and the experimental target and the proposed intelligent edge network compared and analyzed. The result of the analysis showed that the data transmission rate in the intelligent edge network was 97.48%, the data transmission time was 215 ms, and the recovery time of network failure was 49,983 ms.

• Journal of the Korean Geographical Society
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• v.44 no.6
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• pp.797-812
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• 2009

The purpose of this study is to analyze cause-and-effect relationships between patterns of the road network and socio-economic factors such as population, industry, and land use of Seoul during the period of 1970~2000. In this study, Structural Equation Model (SEM) is used to estimate simultaneously the cause-and-effect relationships between many independent variables and dependent variables. For the observed variables, variables related to population, industry, land price, land use, and road variables were included; these variables were classified by exploratory factor analysis. The analysis using the SEM showed that the structure of the model changed around the 1980's. In general, socio-economic factors such as population, industry, and land use affected construction of the road network of the city during the 1970's and the 1980's. Especially, it was analyzed that the industrial development had the greatest impact on formation of the road network. In the 1990's, the effect that the road network exerts on socio-economic factors proved to be more appropriate than the other way round. At that time, the road-related factors had the greatest effect on the land price and industrial development, and that tendency has continued until now.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.3
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• pp.61-70
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• 2001

This paper presents a new method to extract semi-automatically roads from high spatial resolution satellite imagery. This method is based both on wavelet transform and on multiresolution analysis combined in the "$\grave{a}$ trous" algorithm. As an urban road network consists on different classes of streets, multiresolution processing allows to extract the streets class by class. The method was applied to a KVR-1000 image on a part of Busan Metropolitan City. The method was carried out for the road extraction of three different widths and it succeeded in extracting good fitted strips. The accuracy analysis for three types of streets was also performed. The overall accuracy in 4 pixels of width is 80.5%. The result suggests that this method can be used to update road networks in the studied urban network. In summary, the multiresolution approach based on the wavelet transform, used in this study, is regarded as one of effective methods to extract urban road network from high spatial resolution satellite images.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.526-532
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• 2003

This paper describes a recognition method of a road direction for an autonomous vehicle based on magnetic sensors. Using the sensors mounted on a vehicle and the magnetic markers embedded along the center of road, the autonomous vehicle can recognize a road direction and control a steering angle. Using the front lateral deviation of a vehicle and the rear one, the road direction is calculated. The analysis of magnetic field, the acquisition technique of training data, the training method of neural network and the computer simulation are presented. According to the computer simulation, the proposed method is simulated, and its performance is verified. Also, the experimental test is confirmed its reliability.