• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1093-1099
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• 2016

Currently, there are 499 metropolitan subway stations in Korea, but there are not many studies on the influence zone of linkage between railway station and public transport. Existing studies have been studied almost in terms of accessibility.. In addition, the existing research on the influence zone of linkage using survey data and statistics, there is a limit to the theoretical basis and analysis techniques. In this paper, we propose a new method to select on the influence zone of linkage, It is a GIS analysis technique using the spatial data of the railway station user as the large data of the traffic card. We applied the GIS analysis technique for select the influence zone of linkage based on the travel time of the network for each public transportation system. As a result, it was confirmed that the influence of the link of 15 minutes on the local bus, 20 minutes on the city bus and 25 minutes on the intercity bus were clearly distinguished according to the difference in network access time.

• Journal of KIBIM
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• v.11 no.2
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• pp.43-53
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• 2021

The 'public agency oil joint purchase system' was introduced to lower public sector oil prices and contribute to the stability of the overall consumer oil market. The present study used spatial regression to analyze the factors affecting domestic gasoline price, focusing on the impact of potential implicit collusion among gas stations in determining domestic gasoline prices. Also, this study investigated the effect the location characteristics of the market convention gas stations and government offices on the pressure of price competition in the market and the gasoline price at general gas stations. To summarize the results of the spatial lag model (SLM), the individual characteristics of gas stations such as convenience stores (+), self-fuelling (-), commercial areas (+), subway stations (+), population density (-), and sales (-) are correlated to gasoline prices at gas stations, and the institutional location factors of gas stations (+) affected the average of 9 won per liter, 11 won per liter. In order to solve these problems, the establishment of a monitoring system reflecting the location characteristics of the region and the ongoing review of the system should be carried out. In addition, separate, expanded and promotional measures should be prepared for the convenience of general and public oil buyers.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.187-196
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• 2017

It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object-Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.44-63
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• 2007

The purpose of this study is to propose mining processes in the large trip-transaction database of the Metropolitan Seoul area and to analyze the spatial characteristics of travel behavior. For the purpose. this study introduces a mining algorithm developed for exploring trip patterns from the large trip-transaction database produced every day by transit users in the Metropolitan Seoul area. The algorithm computes trip chains of transit users by using the bus routes and a graph of the subway stops in the Seoul subway network. We explore the transfer frequency of the transit users in their trip chains in a day transaction database of three different years. We find the number of transit users who transfer to other bus or subway is increasing yearly. From the trip chains of the large trip-transaction database, trip patterns are mined to analyze how transit users travel in the public transportation system. The mining algorithm is a kind of level-wise approaches to find frequent trip patterns. The resulting frequent patterns are illustrated to show top-ranked subway stations and bus stops in their supports. From the outputs, we explore the travel patterns of three different time zones in a day. We obtain sufficient differences in the spatial structures in the travel patterns of origin and destination depending on time zones. In order to examine the changes in the travel patterns along time, we apply the algorithm to one day data per year since 2004. The results are visualized by utilizing GIS, and then the spatial characteristics of travel patterns are analyzed. The spatial distribution of trip origins and destinations shows the sharp distinction among time zones.

• Spatial Information Research
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• v.20 no.3
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• pp.83-93
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• 2012

Recent environmental concerns have made interest in environment-friendly transportation means such as walking, biking, and public transportation. However, since it is difficult to move long distance by walking or biking, their scope of application is rather limited. On the other hand, public transportation can solve traffic congestion, a recent social issue, though its usability may depend on its time schedule. Currently available information services on public transportation in the Web do not reflect well such traits of the public transportation; thus, in some cases, they may provide wrong information to end users. To solve such problems and provide information based on timetable of public transportations, this paper proposes a STP(Space Time Point) data model. Unlike existing space-time data models, this model recognizes the bottommost element of an object as a point and structures these points in hierarchical way to define an object. In particular, It can make it possible to implement a variety of dynamic spatial objects changing object information according to time. An objective of this study is to design a STP model for bus and subway based on timetables of public transportation in Daejeon area and builds a system to provide path navigation. With the designed navigation function, a path from the Daejeon National Cemetery to Hannam University was searched by time slot. The result showed that the system provided different paths by time, as the system guided different paths when bus operation was limited in midnight. As existing data model could not provide such results, it is confirmed that the system can provide path navigation based on real-time traffic information. It is expected that based on such functionality, it is possible to provide additional functionalities by applying diverse data models such as real-time transport information or traffic history information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.1-12
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• 2016

This paper is to analyze characteristics of transfer trips and to identify impacts of land use on them. Using the smart transport card data of Seoul on a weekday in April 2013, we explored general characteristics of the transfer trips such as spatial and temporal distributions, transfer types, and geographical patterns of transfer trips. Then, the multiple regression model for the transfer trips was developed, considering land use as well as socio-economic variables as explanatory ones. For the characteristics of the transfer trips, their ratio to the total trips accounts for 26.7%. Nearly 87% of the trips are one-time transferred, and 64.7% are bus-subway transfer trips. In addition, the transfer trips are more likely to appear nearby subway stations and business facilities. The regression model indicates that land use variables such as the floor areas of business facilities and department stores and mixed land use index significantly positively affect the transfer trips. Our results can be used as basic data for choosing feasible locations of multi-modal transfer centers in urban areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.859-867
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• 2019

Severe weather conditions, such as heavy snowfall, rain, heatwave, etc., may affect travel behaviors of people and finally change traffic patterns in transportation networks. To deal with those changes and prevent any negative impacts on the transportation system, understanding those impacts of severe weather conditions on the travel patterns is one of the critical issues in the transportation fields. Hence, this study has focused on the impacts of a weather condition on travel patterns of public transportations, especially when a heavy snowfall which is one of the most critical weather conditions. First, this study has figured out the most significant weather condition affecting changes of public transport ridership using weather information, card data for public transportation, mobile phone data; and then, developed a decision-tree model to determine complex inter-relations between various factors such as socio-economic indicators, transportation-related information, etc. As a result, the trip generation of public transportations in Seoul during a heavy snowfall is mostly related to average access times to subway stations by walk and the number of available parking lots and spaces. Meanwhile, the trip attraction is more related to business and employment densities in that destination.

• Journal of Korean Public Health Nursing
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• v.20 no.1
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• pp.28-38
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• 2006

Purpose: To explore the level of health status and health promotion lifestyle, and the group differences in health promotion lifestyle among Seoul citizens who participated in free hypertension screening. Methods: This study was a cross sectional descriptive design. The administered questionnaire included the Health-Promoting Lifestyle Profile II (HPLP II), perceived health status scale, and demographic questions. Blood pressure was measured by researcher teams. Data were collected from July 2 to 6, 2004 in the waiting area of subway stations 7 in Seoul. The study subjects were 168 adults. Results: The average age of the respondents was 55.45 years and 38.7% of them perceived themselves as healthy, while 44% did not know their own blood pressure. Among the participants, 44.6% were classified as 'prehypertensive', and 36.9% as having high blood pressure. The mean score of health promotion lifestyle was 2.62 and the order of subcategories of health promotion lifestyle was interpersonal relationship, spiritual growth, nutrition, stress management, physical activities, and health responsibilities. The subcategories of health promotion lifestyle differed significantly by age, sex, job, and smoking. Conclusions: It is important to encourage adults to participate actively in health promotion. In addition, health promotion programs should be developed and implemented based on group differences.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.165-174
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• 2019

They are frequently used today in public places such as street, subway, school or library. Since users can sometimes print documents that contain confidential data using Printer Kiosks, the devices should store and manage the documents securely. In this paper, we identify potential security threats in Printer Kiosks and suggest practical attack scenarios that can take place. To show the feasibility of suggested attack, we analyzed network traffic that were generated by the real Printer Kiosk device. As a result of our analysis, we have found that attackers can access other users' scanned files and access other users' documents from Printer Kiosk's home page. We confirmed that using our attack, we could retrieve other users' personal data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.1-19
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• 2023

Bikes have recently emerged as an alternative to carbon neutrality. To understand the demand for public bikes, we endeavored to estimate travel frequency of public bike by considering the intermediate stops. Using the GPS trajectory data of 'Ttareungyi', a public bike service in Seoul, we identified a stay point and estimated travel frequency reflecting population, land use, and physical characteristics. Application of map matching and a stay point detection algorithm revealed that stay point appeared in about 12.1% of the total trips. Compared to a trip without stay point, the trip with stay point has a longer average travel distance and travel time and a higher occurrence rate during off-peak hours. According to visualization analysis, the stay points are mainly found in parks, leisure facilities, and business facilities. To consider the stay point, the unit of analysis was set as a hexagonal grid rather than the existing rental station base. Travel frequency considering the stay point were analyzed using the Zero-Inflated Negative Binomial (ZINB) model. Results of our analysis revealed that the travel frequency were higher in bike infrastructure where the safety of bike users was secured, such as 'Bikepath' and 'Bike and pedestrian path'. Also, public bikes play a role as first & last mile means of access to public transportation. The measure of travel frequency was also observed to increase in life and employment centers. Considering the results of this analysis, securing safety facilities and space for users should be given priority when planning any additional expansion of bike infrastructure. Moreover, there is a necessity to establish a plan to supply bike infrastructure facilities linked to public transportation, especially the subway.