• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.739-751
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• 2020

Seoul public bike program facilitates access to bicycles and offers potential for greater mobility and health for users. Furthermore, it would have positive impacts on transport congestion, energy use, and the environment. Hence, it is important to find future rental locations by taking to account both bike-demand and regional imbalance. This paper first finds eligible candidates of rental locations with the required spatial conditions such as a sufficient sidewalk width and accessibility of bike pick-up vehicles. And then, estimates public bike daily usage for each selected location via random forest based on Seoul public bike historical usage, Seoul geographical features, regional characteristics, and populations. This study contributes to a better comprehension of the Seoul public bike program, and would be useful in determining new public bike rental locations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.475-486
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• 2021

The purpose of this study was to propose a policy direction to improve the service of public bicycles in Seoul by identifying the physical characteristics that affect the satisfaction level in the Seoul Metropolitan Government's public bicycle use environment. To this end, a survey was conducted on users regarding their experiences using public bicycles in Seoul, and the responses of 567 people were analyzed. IPA analysis and ordinal logistic analysis were used. An analysis of the Seoul Metropolitan Government's public bicycle IPA showed that the satisfaction level was lower than that of importance in all categories. Among them, the most urgent need for improvement was the installation of bicycle roads, improved connectivity of bicycle roads, improved road management, classification of roads and bicycle roads, improved safety during night driving, and low satisfaction levels. Second, an analysis of the factors affecting the satisfaction in the public bicycle use environment showed that the model's explanatory power increased significantly from 0.062 to 0.437 after incorporating perceived variables, confirming that the perceived neighborhood environment characteristics are an important variable for determining the satisfaction level in the public bicycle use environment, among the perceived neighborhood environmental characteristics, accessibility, convenience, manageability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.33-42
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• 2020

This study analyzed the bicycle traffic patterns and identified the influence factors for each traffic purpose using the household traffic conditions survey for Seoul. The results are summarized as follows. First, as a result of surveying the bicycle traffic ratios according to the administrative dongs, there was a difference of 14.2% by region. Second, various personal characteristic variables, such as age, gender, income, occupation, and housing type, affect the bicycle mode choice, and bicycle passage increases when using facilities in residential areas. Third, among the neighborhood environments, the bicycle traffic for commuting purposes appeared to increase more in the areas of higher land use mix and lower crime rates. In addition, the bicycle road density and the inclination of the area commonly affect bicycle travel for commuting, shopping, exercising, and leisure.

• Review of Korean Society for Internet Information
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• v.19 no.2
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• pp.37-44
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• 2018

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.607-610
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• 2016

최근 자전거 이용인구가 급격하게 증가함에 따라 자전거 교통사고 역시 증가하고 있다. 이에 DB를 통해 이용자에게 알맞은 자전거 도로에 대한 정보를 제공하여 자전거 도로를 활성화하고자 다음과 같은 프로젝트를 진행하게 되었다. 서울시를 중심으로 사용자의 지역, 선호하는 길이, 난이도에 따른 DB를 제공하여 알맞은 자전거 도로를 선택하도록 하였으며, 기업에게는 자전거 이용자의 DB를 제공하여 마케팅에 활용할 수 있도록 하였다.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.405-411
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• 2016

Seoul city is publishing new plans to increase modal share rate of bicycle every year, such as, maintaining bicycle related facilities. But bicycle's modal share rate in Seoul stayed same for the last decade and people are still facing difficulties using bicycle related facilities. These problems are causing bicycle usage as connecting transportation of public transit to decrease. This study looked at the high bicycle modal countries, such as, Netherlands, Germany and Japan to find applicable solutions by analyzing cases and comparing them with cases of highly populated subway station of Sindorim in Seoul. For example, in Germany and Netherlands there is bicycle-parking system to help bikers to access subway easier, in Japan there is underground bicycle parking tower to safely keep high volume of bicycles with in small space. For Seoul city to increase its modal share rate, they should look at problems from users' prospective and solve it by fixing it and improving the services, not by making more facilities.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.97-106
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• 2010

Environmental issues resulting from climate change and energy crises have become global issues, and cycling has gained greater popularity for sustainable transportation. Though many cities are trying to build bicycle roads, it is not easy to implement bicycle roads because there is little available space for bicycle facilities. Therefore, road diets have become more popular in Korea. However, there has been no intensive research to date of their impacts. The purpose of this research is to evaluate the effects of road diets and construction of bike lanes. Every benefit, including energy benefit, environmental benefit, and health benefit is considered, while only time savings benefit has been considered in previous studies. The benefit analysis for the Seoul metropolitan area as a case study shows that road diets have a (1) time saving benefit for only five percent of the mode share and (2) enough total benefit even if bicycle mode share is less than two percent.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.107-120
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• 2023

The public bicycle of Seoul, Ttareungyi, was launched at October 2015 to reduce traffic and carbon emissions in downtown Seoul and now, 2023 Oct, the cumulative number of user is upto 4 million and the number of bike is about 43,000 with about 2700 stations. However, super growth of Ttareungyi has caused the several problems, especially demand/supply mismatch, and thus the Seoul citizen has been complained about out of stock. In this point, this study conducted a real time demand forecasting model to prevent stock out bike at stations. To develop the model, the research team gathered the rental·return transaction data of 20,000 bikes in whole 1600 stations for 2019 year and then analyzed bike usage, user behavior, bike stations, and so on. The forecasting model using machine learning is developed to predict the amount of rental/return on each bike station every hour through daily learning with the recent 90 days data with the weather information. The model is validated with MAE and RMSE of bike stations, and tested as a prototype service on the Seoul Bike Management System(Mobile App) for the relocation team of Seoul City.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.10-21
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• 2021

This study analyzed how external variables, such as the supply policy of shared bicycles and the spread of infectious diseases, affect the demand for shared bicycle use in the COVID-19 era. In addition, this paper presents a methodology for more accurate predictions. The Seasonal Auto-Regulatory Integrated Moving Average with Exogenous stressors methodology was applied to capture the effects of exogenous variables on existing time series models. The exogenous variables that affected the future demand for shared bicycles, such as COVID-19 and the supply of public bicycles, were statistically significant. As a result, from the supply volume and COVID-19 outbreak according to the scenario, it was estimated that approximately 46,000 shared bicycles would be supplied by 2022, and the COVID-19 cases would continue to be at the current level. In addition, approximately 32 million and 45 million units per year will be needed in 2021 and 2024, respectively.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.169-178
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• 2021

Recently, a bike-sharing system (BSS) has become popular as a convenient "last mile" transportation. Rebalancing of bikes is a critical issue to manage BSS because the rents and returns of bikes are not balanced by stations and periods. For efficient and effective rebalancing, accurate traffic prediction is important. Recently, cluster-based traffic prediction has been utilized to enhance the accuracy of prediction at the station-level and the clustering step is very important in this approach. In this paper, we propose a k-means based clustering algorithm that overcomes the drawbacks of the existing clustering methods for BSS; indeterministic and hardly converged. By employing the centroid initialization and using the temporal proportion of the rents and returns of stations as an input for clustering, the proposed algorithm can be deterministic and fast.