• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.257-257
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• 2001

• Transportation Technology and Policy
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• v.7 no.4
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• pp.57-65
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• 2010

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.645-657
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• 2021

Along with the rapid development of the economy, the urban scale has extended rapidly, leading to the formation of different types of urban function districts (UFDs), such as central business, residential and industrial districts. Recognizing the spatial distributions of these districts is of great significance to manage the evolving role of urban planning and further help in developing reliable urban planning programs. In this paper, we propose an automatic UFD division method based on big data analysis of point of interest (POI) data. Considering that the distribution of POI data is unbalanced in a geographic space, a dichotomy-based data retrieval method was used to improve the efficiency of the data crawling process. Further, a POI spatial feature analysis method based on the mean shift algorithm is proposed, where data points with similar attributive characteristics are clustered to form the function districts. The proposed method was thoroughly tested in an actual urban case scenario and the results show its superior performance. Further, the suitability of fit to practical situations reaches 88.4%, demonstrating a reasonable UFD division result.

• Journal of Korean Society of Transportation
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• v.1 no.1
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• pp.28-42
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• 1983

In recent years, significant advances have been made enabling travel demand analysis and network design methods to be used as increasingly realistic evaluation tools. What has been lacking is the integration of travel demand analysis with network design models. This paper reviews some of advanced (integrated) modeling approaches and presents future research directions of integrated modeling system. To design urban transportation networks, it is argued that the travelers' free choice of mode, destination and route should be introduced into transportation network design procedure instead of assuming that trips from a zone to a workplace are fixed or deriving them in a normative procedure to achieve hypothetical system optima.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1739-1742
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• 2011

Public transportation network in our country is concentrated and advanced focusing on urban area in order to secure economic feasibility. As a result, as dependence on private vehicles is relatively getting higher in public transportation vulnerable area, traffic problem occurs since the average running speed in urban area is 22.5km/h. This paper has an objective to suggest an improvement plan by selecting public transportation vulnerable area, and defining according to urban structure, formation and function, and understand traffic characteristics and draw problems. As a method selecting public transportation vulnerable area, an area with high division rate of vehicle was selected as a primary proposed site by calculating division rate of means of public transportation according to area. Final proposed site was selected by using GIS Buffering technique aiming at selected proposed site, and selecting non-benefit area 500m outside, which is the road limit distance from each subway and bus station. Lastly, the degree of improvement effect was studied by constructing imaginary public transportation network aiming at final proposed site and comparing to the amount of change in division rate of means of transportation.

• Transactions of Materials Processing
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• v.22 no.1
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• pp.42-47
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• 2013

The bicycle is one of the most important eco-friendly transport methods which can mitigate global warming. The portability of a bike on public transportation systems is essential for the wide spread use of bicycles by people in urban environments. In this study, a lightweight urban folding bike was developed with careful consideration of the association with public transport. A folding frame using a moving slide link mechanism made from AL6061 is proposed. Numerical analysis was conducted to evaluate structural safety of the bike in both vertical and pedal loading tests. The proposed urban folding bicycle weights only 10kg and summation of its width, length, and height in the folded configuration is under 158cm.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.228-230
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• 2003

In this study, uses of remote sensed imagery in urban environment analysis are represented with the actual processed results with newly implemented programs running under ESRI ArcView-GIS to extract secondary information about mainly urban transportation environment. Implemented programs are about Accessibility index and Connectivity index. Accessibility index and Connectivity index are composed of four types of different algorithms and three types of algorithms such as alpha, gamma, and shimmel index. As show applied examples, tried to find out how remotely sensed imageries can be effectively utilized at actual processing in the direct or indirect ways in these algorithms.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.775-779
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• 2002

Currently, high-resolution satellite imagery such as KOMPSAT and IKONOS has been tentatively utilized to various types of urban engineering problems such as transportation planning, site planning, and utility management. This approach aims at software development and followed applications of remotely sensed imagery to transportation geographic analysis. At first, GDPA (Gradient Direction Profile Algorithm) and main modules in it are overviewed, and newly implemented results under MS visual programming environment are presented with main user interface, input imagery processing, and internal processing steps. Using this software, road network are automatically generated. Furthermore, this road network is used to transportation geographic analysis such as gamma index and road pattern estimation. While, this result, being produced to do-facto format of ESRI-shapefile, is used to several types of road layers to urban/transportation planning problems. In this study, road network using KOMPSAT EOC imagery and IKONOS imagery are directly compared to multiple road layers with NGI digital map with geo-coordinates, as ground truth; furthermore, accuracy evaluation is also carried out through method of computation of commission and omission error at some target area. Conclusively, the results processed in this study is thought to be one of useful cases for further researches and local government application regarding transportation geographic analysis using remotely sensed data sets.

• International Journal of High-Rise Buildings
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• v.10 no.1
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• pp.1-8
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• 2021

Currently, big data and open data, together with traditional measured data, have come to constitute a new data environment, expanding new technical paths for quantitative analysis of the street environment. Streets provide precious linear public space in high-density residential areas. Pedestrian activities are the main body of street vitality. In this paper, 441 street segments were selected from 21 residential districts in high-density downtown area of Shanghai as cases, to quantitatively evaluate the influencing factors of pedestrian activities. Bivariate analysis was performed, and the results showed that street vitality was not only correlated with a highly populated environment, but also with other factors. In particular, the density of entrances and exits of residential properties, the proportion of walkable areas, and the density of retail and service facilities, were correlated with the vitality of street segments. The magnitudes of correlation between the street environmental factors and the pedestrian traffic differed across various trip purposes. Segment connectivity factors were more correlated with walking for leisure than for transportation. While public transportation factors were mainly correlated with walking for transportation, vehicular traffic factors were negatively correlated with walking for leisure.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.