• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4D
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• pp.467-472
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• 2009

Even if Seoul City administration improved its public transportation service, transportation model share in seoul has not been increased. Subway user is also decreasing. Therefore, policy transition into TOD(Transit Oriented Development) should be applied in oder to enhance subway modal share. This paper develops a influencing model by using variables of transportation demand and supply. In addition, it provides major influencing factors for users in subway station area and level of transportation supply based on the analysis results. The results show that: first, cluster analysis presents that traffic pattern is proved to be different according to land use characteristics(residence, non-residence); second, main transportation variables such as transferring distance, the number of bus stop, the number of short distant bus lines, and the number of bicycle are more supplied in residential area compared to non-residential areas; third, the number of lines, bus dispatching interval, operating time, and distance between subway stations are more supplied in non-residential areas than residential areas. All in all, the results will be useful for providing priority of considerations in case of decision-making on public transportation policy in subway station area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1317-1325
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• 2014

The study focused on analyzing spatial sampling by minimizing autocorrelation of spatial based on spatial and geographical data. The study concluded two different ways of minimizing autocorrelation. First, it was important to use suitable spatial sampling method to alienate spatial autocorrelation from spatial or geographical data. The shear distribution rate of public transportation in Seoul resulted in high rate of autocorrelation. However, the study showed samples eliminated autocorrelation when samples were extracted with reasonable distance(above 400m) apart. Without spatial sampling the distortion of spatial data leads to false results; therefore, spatial sampling is indispensable. Second, factors which fluctuates shear distribution of public transportation spatial sampling changed before and after spatial sampling. This was caused by incapable of controling inherent spatial autocorrelation of the data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.667-675
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• 2021

The purpose of this study is as follows: First, to analyze the spatial structure of Jeju by analyzing the rate of parking demand and supply; Second, to determine the parking service imbalance between regions; and third, to elucidate the causes of this spatial structural parking service imbalance and provide effective measures. Due to the rapid population and tourism growth, Jeju is suffering from traffic congestion and serious parking problems. For this, the ways to efficiently utilize the existing parking spaces were identified through spatial structure analysis based on the parking demand and supply in the Jeju area. As short-term policy, the following changes were proposed: switching to small-scale eup or myeon blocks of parking space, use of shared parking system, and repairing side streets in residential areas. As mid-to-long-term policy, it is linked to other means of transportation as follows: parking demand management policy through modal share by reorganizing public transportation routes or expanding traffic facilities; securing park-and-ride lots; and different parking pricing for different time periods. To implement these policies, each area of the public sector, private sector, and private-public partnership should develop the bond of sympathy by areas and participants.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.44-57
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• 2019

It is crucial to understand how people make decisions on mode choice and to accurately predict their behaviors in transportation planning. One of avenues for advancing modeling is, in particular, taking into account for taste heterogeneity in modeling that can incorporate different decision-making processes across group. In this study, we hypothesize that how people make decisions on mode choice would differ by destination in that land use characteristics are heterogeneous by zone even if zones are all in the same area. To this end, we apply Latent Class Modeling (LCM) to commute trips in Seoul by using 2010 household travel diary survey, investigate types of latent classes with the aid of characteristics of destination, and analyze how those classes differently response to factors. The LCM identifies two classes: in the first one, modal split of auto and public transit (bus and metro) is almost half-and-half and the trip destinations are characterized by relatively more residence facilities and less business/commercial facilities; in the second one, public transit has a notably high share and trip destinations are characterized by relatively more business/commercial facilities. In addition, it turns out that demographic and socio-economic variables affect mode choice differently by class.