• Journal of Korea Spatial Information System Society
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• v.9 no.3
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• pp.25-33
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• 2007

The local governments of major cities in Korea are giving focus on public transportation to reduce congestion and improve accessibility in city areas. In this regards, the proper measurement of accessibility is now a key policy requirement for reorganizing the public transport network. Public transport routing problems, however, are considered to be highly complicated since a multi-mode travel generates different combinations of accessibility. While most of the previous research efforts on measuring transport accessibility are found at zone-levels, an alternative approach at a finer scale such as bus links and stops is presented in this study. We proposes a method to compute the optimal route choice of origin-destination pairs and measure the accessibility of the chosen modes combination based on topological configuration. The genetic algorithm is used for the computation of the journey paths, whereas the space syntax theory is used for the accessibility. This study used node-link data in GIS instead of axial lines which are manually drawn in space syntax. The resulting accessibilities of bus stops are calibrated by O-D survey data and the proposed process is tested on a CBD of Seoul.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3D
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• pp.355-361
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• 2011

In order to properly evaluate ITS services exposed in SMART Highway project, a confident dynamic origin-destination (OD) is inevitably needed. This paper used WAVE communication information as a part of call and response (C&R) communication which constitutes core part of the technology for constructing OD. This information includes node information and vehicle information (e.g., latitude and longitude) as well as trajectory data and sample path volume date calculated using node information and vehicle information. A procedure developed to construct a dynamic OD and to validate OD is consist of 1) making toy network and one-hour 00 (random distribution), 2) collecting link information and vehicle information, 3) constructing five-minute OD, and 4) validating estimated OD result using traffic volume and travel time simultaneously. The constructed OD is about 84.79% correct within less than 20% error range for 15min traffic volume, and about 85.42%, within less than 20% error rate of 15 min travel time. Some limitations and future research agenda have also been discussed.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1183-1188
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• 2009

Estimating project costs during the early stage of conceptual planning is very important when deciding whether to approve the project and allocate an appropriate budget. However, due to greater uncertainties involved in a project, it is challenging to estimate costs during this initial stage within a reasonable tolerance. This paper attempts to develop a cost-estimate model for public road projects under these circumstances and limitations. In the conceptual planning stage of a road project, there is only limited information for cost estimation, for example, such input data as total length of the route, origin and destination, number of lanes, general geographic characteristics of the route, and other basic attributes. This implies that the model should individuate suitable but restricted information without considering detailed features such as quantity of earthwork and a detailed route of a given condition. With these limited facts, this paper applies a case-based reasoning (CBR) method to solve a new problem by deriving similar past problems, which in turn is used to estimate the cost of a given project based on best-fitted previous cases. To develop a CBR cost-estimate model, the authors classified 8 representative variables, including project type, the number of lanes, total length, road design grades, etc. Then, we developed the CBR model, primarily by using 180 actual cases of public road projects, procured over the last decade. With the CBR model, it was found that the degree of error in estimation can be reasonably reduced, to below approximately 30% compared to the final costs estimated upon the completion of detailed design.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.