• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.91-99
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• 2019

Existing node-to-node based optimal path searching is built on the assumption that all destination nodes can be arrived at from an origin node. However, the recent appearance of the adaptive path search algorithm has meant that the optimal path solution cannot be derived in node-to-node path search. In order to reflect transportation data at the links in real-time, the necessity of the node-to-link (or link-to-node; NL) problem is being recognized. This research assumes existence of a network with link-label and non-additive path costs as a solution to the node-to-link optimal path problem. At the intersections in which the link-label has a turn penalty, the network retains its shape. Non-additive path cost requires that M-similar paths be enumerated so that the ideal path can be ascertained. In this, the research proposes direction deletion and turn restriction so that regulation of the loop in the link-label entry-link-based network transformation method will ensure that an optimal solution is derived up until the final link. Using this method on a case study shows that the proposed method derives the optimal solution through learning. The research concludes by bringing to light the necessity of verification in large-scale networks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.5
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• pp.605-612
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• 2019

Traditionally, travel demand forecasts have been conducted based on the data collected by a survey of individual travel behavior, and their limitations such as the accuracy of travel demand forecasts have been also raised. In recent, advancements in information and communication technologies are enabling new datasets in travel demand forecasting research. Such datasets include data from global positioning system (GPS) devices, data from mobile phone signalling, and data from call detail record (CDR), and they are used for reducing the errors in travel demand forecasts. Based on these background, the objective of this study is to assess the feasibility of CDR as a base data for travel demand forecasts. To perform this objective, CDR data collected for Daegu Metropolitan area for four days in April including weekdays and weekend days, 2017, were used. Based on these data, we analyzed the correlation between CDR and travel demand by travel survey data. The result showed that there exists the correlation and the correlation tends to be higher in discretionary trips such as non-home based business, non-home based shopping, and non-home based other trips.

• The Journal of Bigdata
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• v.7 no.2
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• pp.235-244
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• 2022

The rental history data of public bicycles in Seoul were analyzed to examine how pandemic phenomena such as COVID-19 caused changes in people's micro mobility. Data for 2019 and 2021 were compared and analyzed by dividing them before and after COVID-19. Data were collected from public data portal sites, and data marts were created for in-depth analysis. In order to compare the changes in the two periods, the riding direction type dimension and the rental station type dimension were added, and the derived variables (rotation rate per unit, riding speed) were newly created. There is no significant difference in the average rental time before and after COVID-19, but the average rental distance and average usage speed decreased. Even in the mobility of Ttareungi, you can see the slow rhythm of daily life. On weekdays, the usage rate was the highest during commuting hours even before COVID-19, but it increased rapidly after COVID-19. It can be interpreted that people who are concerned about infection prefer Ttareungi to village buses as a means of micro-mobility. The results of data mart-based visualization and analysis proposed in this study will be able to provide insight into public bicycle operation and policy development. In future studies, it is necessary to combine SNS data such as Twitter and Instagram with public bicycle rental history data. It is expected that the value of related research can be improved by examining the behavior of bike users in various places.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.17-29
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• 2008

A volume-delay function(VDF) has been used to describe the relation between traffic volumes and delay experienced by travelers on the roads traveling from origin to destination, which has been usually adopted in traffic assignment. For the purpose of more precise description of traffic pattern, we have to estimate the parameters of VDF in advance. This paper presents a methodology for estimating the parameters, which combined with golden section method. By using the method we have estimated the parameters with real data based on KTDB(2006), and validated them. Compared to the existing values of the parameters, newly estimated values are found to be closer to real world.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.19-30
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• 2005

The objective of this research is to keep track of path travel time using methods of collecting traffic data. Users of traffic information are looking for extensive information on path travel time, which is referred to as the time taken for traveling from the origin to the destination. However, all the information available is the average path travel times, which is a simple sum of the average link travel times. The average path travel time services are not up to the expectation of traffic information consumers. To improve provide more accurate path travel time services, this research makes a number of different estimates of various path travel times on one path, assuming it will be under the same condition, and provides a range of estimates with their probabilities to the consumers, who are looking for detailed information. To estimate the distribution of the path travel times as a combination of link travel times. this research analyzes the relation between the link travel time and path travel time. Based on the result of the estimation. this research develops the algorithm that combines the distribution of link travel time and estimates the path travel time based on the link travel times. This algorithm was tested and proven to be highly reliable for estimating the path traffic time.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.63-74
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• 2005

When we introduce the BRT systems, it is very important to decide the operating factors, such as bus-stop locations or headway. If the factors are inappropriate, unessential expenses for the operator and users of the bus line may be caused, and it leads increase of social total cost. So, it is necessary that we consider users' origin and destination of each bus line when we set location of bus-stops and the optimal headway. Meanwhile, Smart Card System was introduced of fare collection for the Public Transportation Reform in Seoul last year. This new card system makes it possible to store up the information about bus operating and passenger's trip link. With these substantial information. we can estimate bus-stop-based O-D table. So, in this thesis, it was studied a systematic methodology to find the optimal location and headway for skip-stop bus system (as a type of first step for BRT). The proposed methodology in this thesis is expected to be useful to effect analysis or setting operating factors for skip-stop bus system in each bus line.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2166-2178
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• 2010

The Korea Transportation Database (KTDB) is used to obtain data on the origin and destination (OD) of inter-city travel, which are currently used in railroad planning when estimating traffic demand. The KTDB employs the trip assignment method, whereby the total traffic volume researched for inter-city travel in Korea is divided into road, rail and air traffic, etc. However, as regards rail travel, the railroad stations are not identical to the existing zones or the connector has not been established because there are several stations in one zone as such, certain problems with the applicable methods have been identified. Therefore, estimates of the volume of railroad traffic using the KTDB display low reliability compared to other modes of transportation. In this study, these problems are reviewed and analyzed, and use of the aggregate model method to estimate the direct demand for rail travel is proposed in order to improve the reliability of estimation. In addition, a method of minimizing error in traffic demand estimation for the railroad field is proposed via an analysis of the relationship between the aggregate model and various social-economic indicators including population, distances, numbers of industrial employees, numbers of automobiles, and the extension of roads between cities.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.533-538
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• 2005

Due to rapidly inc Due to rapidly Increase the number of vehicles, the number of vehicle passed over the traffic capacity which is allowable on each road. In order to disperse the traffic in the congestion area, ITS related techniques have been studied advancing. However, the cost of setting up and managing In is considerable to recently improve the problem or In, various traffic analysis technique are problem using low cost RFID. In this paper, the method of RFID-Reader location selection, which is a core technique to analyze traffic amount and traffic context is proposal. In order to systematically utilize traffic related road information, GIS is used for the proposal method. In addition, a rule-based model using O/D data that is the important information for selection the location of traffic observation.

• Journal of Korean Society of Forest Science
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• v.95 no.4
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• pp.381-387
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• 2006

This study tried to develop a model which can predict a long-term of forest recreation quantity corresponded with econometrics. Simultaneously this study was conducted with the aim of development of practical matrix which is able to apply forest recreation management with policy-control variables about forest supplement with some problem of former study using only a cross-section analysis. As the results of analyses, forest recreation quantity is affected (-) relation by distance, (+) relation by population of the origin area, the size of forest, and a destination's annual social expenditure. In addition, the distance variable is elastic, however, the other variables are inelastic. This results might correspond to a general gravity model theory about forest recreation quantity.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.27-32
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• 2007

3D based information is demanded increasingly as cities grow three dimensionally and buildings become large and complex. The use of 3D GIS is also getting attention as fundamental data for ubiquitous computing applications such as location-based guidance, path finding and emergency escaping. However, most 3D modeling techniques are focused on the visualization of buildings or terrains and do not have topological structures required in spatial analyses. In this paper, we introduce a method to incorporate topological relationship into 3D models by combining 2D GIS layers and 3D model. We divide indoor spaces of a 3D model into discrete objects and then define the relationship with corresponding features in 2D GIS layers through database records. We also show how to construct hallways network in the 2D-3D integrated building model. Finally, we test different cases of route finding situations inside a building such as normal origin-destination path finding and emergency evacuation.