• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.1-25
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• 2022

After the first Covid-19 confirmed case occurred in Korea in January 2020, interest in personal transportation such as public bicycles not public transportation such as buses and subways, increased. The demand for 'Ddareungi', a public bicycle operated by the Seoul Metropolitan Government, has also increased. In this study, a demand prediction model of a GRU(Gated Recurrent Unit) was presented based on the rental history of public bicycles by time zone(2019~2021) in Seoul. The usefulness of the GRU method presented in this study was verified based on the rental history of Around Exit 1 of Yeouido, Yeongdengpo-gu, Seoul. In particular, it was compared and analyzed with multiple linear regression models and recurrent neural network models under the same conditions. In addition, when developing the model, in addition to weather factors, the Seoul living population was used as a variable and verified. MAE and RMSE were used as performance indicators for the model, and through this, the usefulness of the GRU model proposed in this study was presented. As a result of this study, the proposed GRU model showed higher prediction accuracy than the traditional multi-linear regression model and the LSTM model and Conv-LSTM model, which have recently been in the spotlight. Also the GRU model was faster than the LSTM model and the Conv-LSTM model. Through this study, it will be possible to help solve the problem of relocation in the future by predicting the demand for public bicycles in Seoul more quickly and accurately.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1799-1810
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• 2011

Origin-Destination(OD) trip survey being used in travel demand forecasting has been obtained through totalizing process with direct sample survey techniques such as plate license survey, roadside interview, household travel survey, and cordon line counts. However, the OD survey has many discrepancies in sampling, totalizing process, and such discrepancies contains problems of difference between forecasted traffic volume and observed data. On the other hand, transit smart card data recently collected has credible resource of obtaining travel information for bus and metro. This paper presents parameter estimation of gravity model by using transit smart card data. Through the parameter estimation method, we estimated =0.57, ${\beta}$=0.14 of gravity model for bus, and ${\alpha}$=-0.21, ${\beta}$=0.05 for metro. The statistical test such as T-test, coefficient of correlation, Theil`s inequality coefficient showed no difference between observed volume and estimated volume. Elasticities of bus and metro derived in this paper are also reasonable.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4795-4802
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• 2010

In order to solve the traffic problem in jeju, we must reduce demand for car travel. In addition, demand for passenger travel by public transport policy is needed for conversion. And to improve the quality of public transport services are desperately needed. The purpose of this study, personal characteristics of the trip traveler and the relationship between transportation choice, and personal effectiveness as a factor in travel costs and travel time on the impact of transportation choices will investigate. Restructure its public transportation routes, when to switch to buses to car traffic on the data as a basis for the factors that may be. In addition to improving the quality of public transport services is expected to be able to contribute. To study the performance of the May 2010 survey was conducted. And multinominal logit model were conducted. According to the analysis, People who own homes and families with more than 5 people are likely to use cars. If a prolonged travel time is likely to use buses. However, increasing the cost of travel increases the likelihood that the car is available.

• Journal of the Korean Society for Railway
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• v.16 no.2
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• pp.129-137
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• 2013

This study This study aims to identify sound developmental directions for transit-oriented development (TOD), which is a topic of interest in the field of urban development, and conducts an empirical analysis of station influence areas within Seoul according to the characteristics of transit types. The results suggest that there are differences among variables that influence demand for public transportation according to transit types. This means that it is necessary to identify improvement plans in developing public transport strategies for the capital region based on such differentiated influence factors and to build foundations to continue to increase demand for public transportation. Also, station influence areas should be developed into hubs by establishing appropriate bus-only lane networks as a supplementary means, rather than directly connecting subway stations with each other.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.219-232
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• 2023

Mobility services need to change according to the regional characteristics of the target service area. Accordingly, analysis of mobility patterns and characteristics based on Origin-Destination (OD) data that reflect travel behaviors in the target service area is required. However, since conventional methods construct the OD data obtained from the administrative district-based zone system, it is hard to ensure spatial homogeneity. Hence, there are limitations in analyzing the inherent travel patterns of each mobility service, particularly for new mobility service like Demand Responsive Transit (DRT). Unlike the conventional approach, this study applies a data-driven clustering technique to conduct spatial analyses on OD travel patterns of regional mobility services based on reconstructed OD data derived from re-aggregation for original OD distributions. Based on the reconstructed OD data that contains information on the inherent feature vectors of the original OD data, the proposed method enables analysis of the spatial characteristics of regional mobility services, including public transit bus, taxi and DRT.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.93-105
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• 2014

This study evaluated the relative efficiency of mobile emission reduction countermeasures through a Data Envelopment Analysis (DEA) approach and determined the priority of countermeasures based on the efficiency. Ten countermeasures currently applied for reducing greenhouse gases and air pollution materials were selected to make a scenario for evaluation. The reduction volumes of four air pollution materials(CO, HC, NOX, PM) and three greenhouse gases($CO_2$, $CH_4$, $N_2O$) for the year 2027, which is the last target year, were calculated by utilizing both a travel demand forecasting model and variable composite emission factors with respect to future travel patterns. To estimate the relative effectiveness of reduction countermeasures, this study performed a super-efficiency analysis among the Data Envelopment Analysis models. It was found that expanding the participation in self car-free day program was the most superior reduction measurement with 1.879 efficiency points, followed by expansion of exclusive bus lanes and promotion of CNG hybrid bus diffusion. The results of this study do not represent the absolute data for prioritizing reduction countermeasures for mobile greenhouse gases and air pollution materials. However, in terms of presenting the direction for establishing reduction countermeasures, this study may contribute to policy selection for mobile emission reduction measures and the establishment of systematic mid- and long-term reduction measures.

• Journal of the Korean Regional Science Association
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• v.32 no.4
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• pp.39-49
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• 2016

The main objective of this paper is to analyze university students' modal shift for commuting trip due to the introduction of new urban rail transit in a satellite city of metropolitan area. The paper uses SP(2011)/RP(2013) data collected from Yeungnam University in Gyeongsan City, which is a satellite city of Deagu Metropolitan City. So far few researches, especially using before-and-after individual SP/RP travel survey, have been conducted on analyzing university students' modal shift due to the introduction of new urban rail transit. For this research, some descriptive statistical analyses were conducted. Furthermore, some empirical logit models were estimated for analyzing factors affecting the modal shift. Finally, some important findings and policy implications are discussed. The significant findings from this research are summarized as follows. From the descriptive statistical analyses of SP and RP data, it is found that the rate of modal shift to rail transit is relatively high especially for bus travellers. Furthermore, from the empirical SP model estimation, it is found that time saving is the most important factor affecting the modal shift to urban rail transit. On the other hand, from the empirical RP model estimation, it is found that residential location is the most important factor affecting the modal shift to urban rail transit.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.17-23
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• 2009

Due to the rapid increase of vehicles on the street, Korean society is facing worsening traffic congestions and air pollutions. Also, the oil price pickup has led to increasing need for the use of public transportation. In particular, transfering among public transportation may be a main factor for riders who are commuting for a long distance journey. In order to ensure such connectivity, transfer stations have been actively built in Korea. However, it would be necessary to shift those vehicles, from cars to public transportations by enhancing the users' satisfaction with public transportation through strategies for minimizing the users' waiting cost by building an efficient connective system between transportation modes as well as the preparation of aforementioned transfer stations. Therefore, this study aimed to develop an algorithm for minimizing transferring passengers' waiting costs based on service intervals of linked buses within the transfer facilities. In order to adjust the service interval, we calculated the total costs, involving the wait cost of transfer passengers and bus operation costs, and produced an allocation interval, that would minimize the costs. We selected a KTX departing from Seoul station, and a No. 6014 bus route in Gwangmyeong city where it starts from the Gwangmyeong station in order to for verifying the model. Then, the transfer passengers' total waitting cost was reduced equivalent to the maximum of 212 minutes, and it revealed that the model performed very effectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1517-1524
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• 2014

In recent years, the interest of environmental-friendly transportation modes has been growing. This is because of social and environmental problems such as increasing gas price and climate change. In Europe, bike-sharing service, one of the environmental-friendly transportation modes, has been already operated. Bike-sharing service named "Tashu" has been operated in Daejeon city since 2009. This study is a fundamental research to increase utilization efficiency of bike-sharing service and to decide optimal locations of bike stations. In addition this study examines characteristics of bike usage and analyzes factors affecting to demands using multiple regression model. Based on the result of examining of characteristics of bike usage, the rate of bike usage is higher compared with installation rate of public bike stations near parks in Daejeon. In addition demands of bike usage in weekend is higher than in weekday. It reveals that the main purpose of bike usage could be recreational activities. The return rate at the same location with rental station is comparatively high. Moreover, bike usage pattern is biased in specific areas (Dunsan and Yuseong) because bike-sharing stations are not equally located. As a result of multiple regression model, the factors affecting to demands are number of passengers in buses, length of bike lanes, parks, distance to waterfront, and rate of young people. A statistical significance of factors (r-square) is 0.748, which has strong relationship.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.599-608
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• 2022

There has been criticism that the government-led makerspace did not reflect the actual demand of makers, so there was a limit to performance creation. In this regard, the study aims to diagnose the current status and problems of makerspace and to suggest the implication to respond to policy demand. To this end, we analyzed the current status of makerspace by utilizing the government documents. Then, we conducted a survey of SMEs related to ICT devices that experienced makerspace, and analyzed their opinions on D·N·A technology demand, management difficulties, and governments' support policies. As results, the study proposed several improvement measures to upgrade makerspace as a digital conversion platform as follows. First, due to the nature of the existing industry for introducing D·N·A technology, there is a limit for companies to enter the market on their own, so comprehensive support from the government is needed. Second, it is necessary to establish and expand an empirical test bed for the development of new products and services so that various types of metaverse contents can be discovered and digital transformation convergence models of existing businesses can be derived. Third, by modifying the support method to operate the makerspace as a platform that implements the government-led start-up support policy, boldly transfer what the private sector can do well to the private sector. The participants of Industry·University·Institute Collaboration should freely share ideas and help the common problem be solved. Based on the problems and the findings for improvement, it is expected that the current makerspace would be upgraded to a digital conversion platform suitable for the demand of the field.