• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.703-709
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• 2009

This article analyzes the obtained data on consciousness survey of disabled and non-disabled pedestrians, and proposes fundamental data for public strategy in order to enhance facilities in subway stations in advance. This paper conduct literature review, new listing survey related to 'The Code for Improvement of Convenience for Moving Vulnerable Pedestrians', and Modified-Importance-Performance Analysis (M-IPA). The results show that disabled pedestrians want enhancement in information facilities as a whole. In addition, the results show that several improvements needs to be applied to accessible sidewalk, to informative notification, to alarm and evacuation system and to toilet for disabled pedestrians. This indicates that disabled pedestrians heavily concentrate on accessibility to subway station and provided information compared with disabled pedestrians.

• Journal of Korea Planning Association
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• v.53 no.6
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• pp.39-59
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• 2018

This study examines the relationship between the usage of public bike and physical environment factors around the public bike stations using the public bike rental history data from 2016 to 2017 in Seoul, Korea. Focusing on the different influences of determinant factors by distance to public bike station, this study identifies influential factors that affect the usage of public bike. The results of the analysis are as follows. First, both the land use and physical environmental variables of bike station areas show strong associations with the usage of public bike. Second, the usage of public bike is also associated with neighborhood living facilities, business facilities, land use mix, the distance to subway station, public facilities and universities. This finding indicates that public bike has played a role as a transportation mode for the short-distance travel and commuting purposes in everyday life. Third, this study shows that the usage of public bike is strongly associated with the average slope, traffic volume around public bike stations, distance to streams or rivers, and the types of bike lane. This finding also indicates that surrounding environmental factors play an important role in the usage of public bike. Finally, this study identifies the different influences of determinant factors on the usage of public bike by distance to public bike station. This study suggests policy implications for the potential locations of public bike stations in the future.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.83-95
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• 2021

In this study, various usage patterns were analyzed after establishing a data mart for micro mobility analysis based on the rental history of public bicycles in Seoul. Rental history data is origin-destination data that includes the rental location and time, and the return location and time. About 1500 rental locations were classified according to the characteristics of the location to create a 'station type' dimension. We also created a 'path type' dimension that displays whether the rental location and return location are the same. In addition, a derived variable called speed, which is obtained by dividing the distance used by the time used, is added, and through this, the characteristics of the riding area and the reason for the rental can be estimated. Meanwhile, administrative district link, administrative neighborhood link, and station type link were created to apply network analysis. Through this analysis, the roles and proportions of administrative districts, public facilities, and private facilities engaged in micro-mobility services were visualized. 49.9% of rentals occur at rental offices near transportation facilities, and half of them occur at rental offices near subway stations. The number of rentals during the evening rush hour is more than double that of the morning rush hour. When the path type is unidirectional, there is a fixed destination, so the distance and time used are short, and the movement speed tends to be high. In the case of round-trip, the purpose of use is exercise or leisure, so the distance and time used are long, and the movement speed is slow. It is expected that the results of the analysis can be used as reference materials for selecting new rental locations, providing convenient services for users, and developing user-specialized products.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.101-116
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• 2017

This Study estimates the actual night traffic using the smart card data used by most of the public transportation users, and compares it with the current night bus routes by KT Telecom based on the night time call volume. In order to compare the current night bus and night trips evaluated by smart card data, we presented indicators related to the degree of matching, and estimated the volume of service currently provided. The unique approach of the study is that we chose subway station instead of bus stop for the unit of the study. Bus stops has their complexity in a way that stops with same name could belong to different administrative area depending on its direction. For this reason, we decided to use subway station and defined its adjacent administrative district as the scope of influence. Since night bus is the primary means of transportation during the late night, it is anticipated that they will be able to provide better service by calculating the actual traffic and selecting the routes.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.6
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• pp.692-702
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• 2011

For more effective indoor radon reduction policy and technique, we researched radon data analysis for some buildings in Seoul. Those buildings were categorized as dwelling, underground and office space and the variations of radon concentration and its sources were evaluated. The variations of radon concentrations of indoor space of buildings for a day were patterned specifically by dwelling habits and different environment. As for the new built apartments which were not yet moved in, their indoor radon concentrations were showed more than 3 times after applying interior assembly, and were 5 times higher than ones of rather old residences. As for the subway stations, the radon concentrations during off-run times were about 15% higher than run-times. 10% of radon seemed to be reduced by installation of platform screen doors. As for office space, radon concentrations during working hours were about 2.5 times higher than non-working hours. Plaster board are expected as a main source of radon for them. By radon measurement method for long-term, its data can be over estimated because it covers non-active time in office or public space. Therefore combination of short and long-term measurement method is required for effective and economic reduction. Furthermore importance of ventilation is requested as public information service for all dwelling space. And also standardization for radium content or radiation of radon is necessary.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2447-2453
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• 2013

In this study, the effects of weather conditions such as rainfall, discomfort index, snowfall, and sensible temperature on public transport demand in Seoul were analyzed using statistical data. The reasons were also derived from the survey. The data for the analysis were collected over the weekdays and weekends, and seasonal data of summer and winter were also gathered separately. Rainfall amount, discomfort index, and sensible temperature except snowfall amount, whose samples were insufficient, decreased the public transport demand by 2-7%. Rainfall amount and sensible temperature were statistically significant. Correlation analysis also showed that rainfall amount and sensible temperature are highly correlated with the demand. To find the reasons, the survey was conducted on citizens living in the Seoul Metropolitan Area. About 30% of the respondents wished to give up using bus when rainfall was heavy or temperature was low. On the contrary, auto and subway users increased by 10%. The results of this study could be used as the basic data when the public transportation planning or operation related policies according to the weather condition are concerned.

• Journal of the Korean housing association
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• v.18 no.6
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• pp.35-44
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• 2007

The purpose of this paper is to find out the factors affecting the apartment price given three sets of variables such as characteristics of apartment building, apartment site, and location. Data of 1,579 housing units in 224 apartment complex sites in Ilsan city were selected from the housing information of four public and private housing sources in 2006. The first set of variables for physical features include housing size (pyoung), preferring-floor, building orientation, heating system and structure of entrance. The second set of variables for building were number of housing units, built year and rank of construction company. The third set of variables for location were distance from number of school, the subway station, distance of department store and park. For the analysis, the hedonic price model, which was one of the methods to estimate social convenience, was used along with the SPSS statistical program and regression analysis. The results are as follows, Firstly, in the structural characteristic variables, it was analyzed that all of the variables except facing affected the apartment price. Secondly, In the site characteristic variables, unusually all of the variables were not affected the apartment price in Ilsan city. Finally, the locational characteristic variables number of school, the subway station, distance of department store and park affected the apartment price. In case of Ilsan city, educational facilities was likely to positively contribute to the price of apartment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.28-37
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• 2020

This study developed a deep learning model that predicts rental demand for public bicycles. For this, public bicycle rental data, weather data, and subway usage data were collected. After building an exponential smoothing model, ARIMA model and LSTM-based deep learning model, forecasting errors were compared and evaluated using MSE and MAE evaluation indicators. Based on the analysis results, MSE 348.74 and MAE 14.15 were calculated using the exponential smoothing model. The ARIMA model produced MSE 170.10 and MAE 9.30 values. In addition, MSE 120.22 and MAE 6.76 values were calculated using the deep learning model. Compared to the value of the exponential smoothing model, the MSE of the ARIMA model decreased by 51% and the MAE by 34%. In addition, the MSE of the deep learning model decreased by 66% and the MAE by 52%, which was found to have the least error in the deep learning model. These results show that the prediction error in public bicycle rental demand forecasting can be greatly reduced by applying the deep learning model.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.101-111
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• 2005

Various urban transport policies have an effect on urban transit riderships and accessibility. This study reports variations of metropolitan subway travel patterns affected by an enormous change in bus routes and transfer discount fare policy between subway and bus mode conducted by Seoul city in July 1st of 2004. In an effort to see the difference between the before and the after policies, two data sets are prepared. Firstly, on a daily bassis. an origin-destination trip table of May of 2004 is used. Secondly, on a daily bassis, an origin-destination trip table of August-September of 2004 is used as a counter measure. Even if seasonal variation was not considered, Seoul metropolitan area have experienced increasing riderships and accessibility. Finally, the effects of accessibility in spatial interaction model by rall service changes such as random shocks were scrutinized and interpreted in detail.

• 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.