• Structural Monitoring and Maintenance
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• v.5 no.3
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• pp.363-377
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• 2018

The proper functioning of critical points on transport infrastructure is decisive for the entire network. Tunnels and bridges certainly belong to the critical points of the surface transport network, both road and rail. Risk management should be a holistic and dynamic process throughout the entire life cycle. However, the level of risk is usually determined only during the design stage mainly due to the fact that it is a time-consuming and costly process. This paper presents a simplified quantitative risk analysis method that can be used any time during the decades of a tunnel's lifetime and can estimate the changing risks on a continuous basis and thus uncover hidden safety threats. The presented method is a decision support system for tunnel managers designed to preserve or even increase tunnel safety. The CAPITA method is a deterministic scenario-oriented risk analysis approach for assessment of mortality risks in road tunnels in case of the most dangerous situation - a fire. It is implemented through an advanced risk analysis CAPITA SW. Both, the method as well as the resulting software were developed by the authors' team. Unlike existing analyzes requiring specialized microsimulation tools for traffic flow, smoke propagation and evacuation modeling, the CAPITA contains comprehensive database with the results of thousands of simulations performed in advance for various combinations of variables. This approach significantly simplifies the overall complexity and thus enhances the usability of the resulting risk analysis. Additionally, it provides the decision makers with holistic view by providing not only on the expected risk but also on the risk's sensitivity to different variables. This allows the tunnel manager or another decision maker to estimate the primary change of risk whenever traffic conditions in the tunnel change and to see the dependencies to particular input variables.

• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.155-164
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• 2017

While many countries are implementing various policies regarding the logistics network in Eurasia, China has presented "the Belt and Road" Initiative, a development strategy that focuses on connectivity and close cooperation between China and Eurasia. With more than 60 countries participating in the project, China is expected to have a major influence on logistical infrastructure development in Eurasia. This study analyzed the railway stations network using social network analysis (SNA) methodology. We collected data from major railway lines in Eurasia (TAR, TEN-T, TRACECA, GMS) and established a network of 994 railway stations in 65 countries. This study presented the general characteristics of major railway stations from the perspective of SNA and compared the Chinese network with Eurasian networks. To review the railway networks in China and Eurasia, the top 30 stations were selected based on degree centrality and betweenness centrality. Top "degree centrality" stations included Bangkok (Thailand), Tbilisi (Georgia), Baku (Azerbaijan), Kunming (China), and Bucharest (Romania). Top "betweenness centrality" stations were Baku and Alyat (Azerbaijan), Baoji and Turpan (China), Qarshi (Uzbekistan), and Kas (Turkey). In China, Kunming, Nanning, and Gejiu stations have higher degree centrality while betweenness centrality was higher in Baoji, Kunming, and Lanzhou stations. "The Belt and Road" project advocated by China envisions expansion of transportation infrastructure connections throughout Eurasia, but more emphasis is likely to be placed on connectivity that benefits China. In this regard, studies on key bases of international logistics need to consider relative significance within the Chinese network.

• Journal of Korean Society of Forest Science
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• v.80 no.3
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• pp.317-325
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• 1991

Route projection of forest road involves several constraints ranging from construction cost to environmental impacts. This study is designed to assess the capability of computer-assisted map analysis techniques for deriving several alternatives of forest road planning. Three cartographic models are presented to address the limit of slope, soil erosion, and aesthetic value in designing forest roads over a relatively small size of mountainous forest. Primary spatial analysis techniques used are distance measurements and connectivity analysis. The fundamental approach used was to generate a set of friction maps in which each friction map represents a combined restriction for a forest road projection. Products of the spatial analysis are compared by both qualitative and quantitative methods. The results demonstrate that computer-assisted map analysis has a potential to solve rather complex problems of forest road planning by providing several alternatives effectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.609-618
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• 2021

The spread and damage of COVID-19 are putting significant pressure on the world, including Korea. Most countries place restrictions on movement and gathering to minimize contact between citizens and these policies have brought new changes to social patterns. This study generated traffic volume data on the scale of a road network using taxi movement data collected in the early stages of the COVID-19 third pandemic to analyze the impact of COVID-19 on movement patterns. After that, correlation analysis was performed with the data of confirmed cases in Daegu Metropolitan City and Local Moran's I was applied to analyze the effect of spatial characteristics. As a result, in terms of the overall road network, the number of confirmed cases showed a negative correlation with taxi driving and at least -0.615. It was confirmed that citizens' movement anxiety was reflected as the number of confirmed cases increased. The commercial and industrial areas in the center of the city confirmed the cold spot with a negative correlation and low-low local Mona's I. However, the road network around medical institutions such as hospitals and spaces with spatial characteristics such as residential complexes was high-high. In the future, this analysis could be used for preventive measures for policymakers due to COVID-19.

• Journal of Construction Engineering and Project Management
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• v.5 no.1
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• pp.26-31
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• 2015

Success of the construction companies is based on the successful completion of projects within the agreed cost and time limits. Artificial neural networks (ANN) have recently attracted much attention because of their ability to solve the qualitative and quantitative problems faced in the construction industry. For the estimation of cost and duration different ANN models were developed. The database consists of data collected from completed projects. The same data is normalised and used as inputs and targets for developing ANN models. The models are trained, tested and validated using MATLAB R2013a Software. The results obtained are the ANN predicted outputs which are compared with the actual data, from which deviation is calculated. For this purpose, two successfully completed highway road projects are considered. The Nftool (Neural network fitting tool) and Nntool (Neural network/ Data Manager) approaches are used in this study. Using Nftool with trainlm as training function and Nntool with trainbr as the training function, both the Projects A and B have been carried out. Statistical analysis is carried out for the developed models. The application of neural networks when forming a preliminary estimate, would reduce the time and cost of data processing. It helps the contractor to take the decision much easier.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.131-144
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• 1997

Traffic jam densified day by day is phenomenon to occur lack of the road capacity in comparison with traffic density, but lack of the road cannot be concluded by main cause of traffic ism. Because the central function of a city would be concentrated upon the downtown and traffic demand would not be evenly distributed by the classification of an hour. Therefore, this study based on the fact that each driver will select the route generating traffic delay very low when path choice from origin to destination in travel plan estimating the quality of passage could be maintained the speed he want will approach to a characteristic grasp of a road, traffic, driver changing every moment by traffic-demand of road increased as a geometrical series with analysis a classification of a street, a intersection along the path on traffic density and highway capacity analysis the path using GIS techniques about complex street network, also will get the path of actual optimum for traffic delay trend creating under various condition the classification per a hour, a day of week and an incident through network such as analysis for traffic generation zone adjacent about street, intersection, afterward will expect the result increasing efficiency of the road-use through a good distribution of traffic by optimum-path choice, accordingly will prepare the scientific, objective, appropriate basis to decide the reasonable time of a road-widen and expansion through section analysis along a rate of traffic volume vs. road capacity.

• 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 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.75-80
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• 2005

In this paper, a 3-dimensional analysis of magnetic road and a position sensing system for an autonomous vehicle system is described. Especially, a new position sensing system, end of the important component of an autonomous vehicle, is proposed. In a magnet based autonomous vehicle system, to sense the vehicle position, the sensor measures the field of magnetic road. The field depends on the sensor position of the vehicle on the magnetic road. As the rotation between the magnetic field and the sensor position is highly complex, it is difficult that the relation is stored in memory. Thus, a neural network is used to learn the mapping from th field to the position. The autonomous vehicle system with the proposed position sensing system is tested in experimental setup.

• Journal of Digital Convergence
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• v.10 no.3
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• pp.161-166
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• 2012

This paper study and analysis about road map and information assurance policy in center of information assurance issues, under the future combat environment, which is performing US military, and the background of modernization war of network centric.