• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.101-107
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• 2012

With the foot-and-mouth disease problems emerging as a serious social issue, this study set out to analyze the problems with the current setting of preventive zones against epidemics and find ways to minimize damage through preventive measures. For those purposes, the study analyzed the outbreaks of the foot-and-mouth disease and assumed that the disease would be transmitted via vehicles along the roads based on the network map of national roads and boundaries among administrative districts to conduct network analysis. The analysis results were then used to estimate spread time, whose results were then categorized according to lineal road distance and actual road distance. Then lineal moving speed and actual moving speed on the road were obtained according to the national roads and administrative districts to analyze the problems with the current method of setting preventive zones against the foot-and-mouth disease. As for spread speed around the areas where the foot-and-mouth disease broke out, the average lineal spread speed was 53.9km/day, and the average spread speed on the road was 71.1km/day, which indicates there are problems with the current method of setting preventive zones against epidemics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.147-150
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• 2008

The real road network is regarded as a grid, and the grid is divided by fixed-sized cells. The path-finding is composed of two step searching. First searching travels on the abstract graph which is composed of a set of psuedo vertexes and a set of psuedo edges that are created by real road network and fixed-sized cells. The result of the first searching is a psuedo path which is composed of a set of selected psuedo edges. The cells intersected with the psuedo path are called as valid cells. The second searching travels with $A^*$ algorithm on valid cells. As pruning search space by removing the invalid cells, it would be possible to reduce the cost of exploring on real road network. In this paper, we present the method of creating the abstract graph and propose a path-finding algorithm on the abstract graph for extracting search space before traveling on real road network.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.39-46
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• 2009

Generally, Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost in case of that there is no way determined by heuristic function or there are 2 way more which have almost same cost. In this paper, we propose an abstract graph for path-finding with dynamic information. The abstract graph is a simple graph as real road network is abstracted. The abstract graph is created by fixed-size cells and real road network. Path-finding with the abstract graph is composed of two step searching, path-finding on the abstract graph and on the real road network. We performed path-finding algorithm with the abstract graph against A* algorithm based on fixed-size cells on road network that consists of 106,254 edges. In result of evaluation of performance, cost of exploring in path-finding with the abstract graph is about 3~30% less than A* algorithm based on fixed-size cells. Quality of path in path-finding with the abstract graph is, However, about 1.5~6.6% more than A* algorithm based on fixed-size cells because edges eliminated are not candidates for path-finding.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.3 s.49
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• pp.135-147
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• 2006

The essential information elements for the Earthquake Damage Evaluation System (EDES) of highway bridges are defined in this study, and a database construction method, which fits the circumstances of Korea, is proposed. The information elements for the EDES of highway bridges are categorized in two groups: structure related information, location related information. The structure related information is composed of the fragility curve information which is necessary for earthquake damage evaluation of highway bridges. The data structure of road network, which represents the location related information, is defined in more detail than the existing GIS-based data structure of road network for modeling of junctions. A pilot GIS-based EDES subjected to 110 bridges on expressway in Korea is developed, and it is verified that the proposed database construction method for the EDES can be used to develop a decision making system for quick retrofitting of the seismic damages of highway bridges and road network.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.70-85
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• 2021

Deep learning methodology, which has been actively studied in recent years, has improved the performance of artificial intelligence. Accordingly, systems utilizing deep learning have been proposed in various industries. In traffic systems, spatio-temporal graph modeling using GNN was found to be effective in predicting traffic speed. Still, it has a disadvantage that the model is trained inefficiently due to the memory bottleneck. Therefore, in this study, the road network is clustered through the graph clustering algorithm to reduce memory bottlenecks and simultaneously achieve superior performance. In order to verify the proposed method, the similarity of road speed distribution was measured using Jensen-Shannon divergence based on the analysis result of Incheon UTIC data. Then, the road network was clustered by spectrum clustering based on the measured similarity. As a result of the experiments, it was found that when the road network was divided into seven networks, the memory bottleneck was alleviated while recording the best performance compared to the baselines with MAE of 5.52km/h.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.51-62
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• 2022

AI-based speed prediction studies have been conducted quite actively. However, while the importance of explainable AI is emerging, the study of interpreting and reasoning the AI-based speed predictions has not been carried out much. Therefore, in this paper, 'Explainable Deep Graph Neural Network (GNN)' is devised to analyze the speed prediction and assess the nearby road influence for reasoning the critical contributions to a given road situation. The model's output was explained by comparing the differences in output before and after masking the input values of the GNN model. Using TOPIS traffic speed data, we applied our GNN models for the major congested roads in Seoul. We verified our approach through a traffic flow simulation by adjusting the most influential nearby roads' speed and observing the congestion's relief on the road of interest accordingly. This is meaningful in that our approach can be applied to the transportation network and traffic flow can be improved by controlling specific nearby roads based on the inference results.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.9
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• pp.838-844
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• 2004

In a long road tunnel, a tunnel ventilation system may be used in order to reduce the pollution below the required level. To develop control algorithms for a tunnel ventilation system, a dynamic simulation program may be used to predict the pollution level in a tunnel. Research was carried out to develop better pollution models for a tunnel ventilation control system. A neural network structure was adopted and compared by using actual poilution data. Simulation results showed that the dynamic model developed by a neural network may be effective for the development of tunnel ventilation control algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.4
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• pp.331-339
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• 2003

It is difficult for the road management system to give a correct road information because road facilities are differently managed according to each object. In this study, we have solved this problem of road information management and, developed a system which is able to integrate various data of facilities and to maintain the latest property of data by introducing server-client network structure for managing road facilities more efficiently. And, we have shown the affairs of the road information management could be achieved scientifically, by the integration of graphic, attribute and photograph information relevant to road. This enabled the connection of graphic data and the stereo drawing composition, and enhanced the feeling of real world experience using the dynamic image data of the road.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.301-303
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• 2003

The extraction of 3D road network from high-resolution aerial images is still one of the current challenges in digital photogrammetry and computer vision. For many years, there are many researcher groups working for this task, but unt il now, there are no papers for doing this with TLS (Three linear scanner), which has been developed for the past several years, and has very high-resolution (about 3 cm in ground resolution). In this paper, we present a methodology of road extraction from high-resolution digital imagery taken over urban areas using this modern photogrammetry’s scanner (TLS). The key features of the approach are: (1) Because of high resolution of TLS image, our extraction method is especially designed for constructing 3D road map for next -generation digital navigation map; (2) for extracting road, we use the global context of the intensity variations associated with different features of road (i.e. zebra line and center line), prior to any local edge. So extraction can become comparatively easy, because we can use different special edge detector according different features. The results achieved with our approach show that it is possible and economic to extract 3D road data from Three Linear Scanner to construct next -generation digital navigation road map.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.55-66
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• 2005

Association of South East Asian Nations(ASEAN) has recently decided to develop ASEAN Highway Network to connect member countries by road in an attempt to achieve a goal of closer economic integration in the region. This entailed the necessity to newly construct or upgrade some 5,481 km of road sections to make ASEAN Highway Network functional. This study offers haw we can prioritize development of these road sections using the Analytic Hierarchy Process. Particularly, it shows how individual road sections can be prioritized considering the importance of corridor or road group where the individual road section lies. It also develops how values of different evaluation criteria can be compared in the same scale. This new approach can be useful in prioritizing highway development in such cases where candidate road sections are widely scattered around the region, so detailed benefit and cost analysis is practically too demanding to carry out.