• Journal of the Korean Regional Science Association
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• v.38 no.4
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• pp.75-91
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• 2022

With the recent increase in interest in climate change issues, the use of bicycles is complementing public transportation and attracting attention as one of the eco-friendly means of transportation. Daejeon Metropolitan City has been operating Tashu, a public bicycle, since 2008. This study empirically analyzed the spatial characteristics that affect the use of public bicycles by grasping the current status and characteristics of public bicycles and applying spatial econometrics analysis, an analysis model that considers the spatial dependence of spatial data. In addition, a comparative analysis was performed by deriving the results of analyzing six models in terms of rental, return, peak time, non-peak time, weekday, and weekend based on the spatial error model identified as the optimal spatial econometrics model. The analysis model results showed that significant spatial characteristics differed according to the type of public bicycle use. In general, the use of public bicycles was high in areas with a high proportion of young people, a high number of public transportation users, good access to universities and rivers, and relatively low land use mix, and high proportion of apartments. These results indicated that public bicycles are used for commuting purposes on weekdays and leisure purposes on weekends, and if the convenience of using bicycles is improved, the use of public bicycles can be further increased.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.62-74
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• 2020

Although the government and local governments devote efforts to activate bicycles, they only access to the supply infrastructure such as bike lanes and the public bicycle rental service centers without considering the measures to overcome the geographical constraints of slope. Therefore, this study constructs bicyclist's energy consumption estimation model through experimental methods of slope gradient and heart rate measurement and suggest the bicycle route choice model which could minimize the energy by the slope gradient. After calculating the RMSE of the estimated energy consumption by applying this model to the simulation section, it is confirmed to be 41% better than the model which does not reflect slope gradient. The results of this study are expected to be applied to the bicycle infrastructure planning that considers both longitude and transverse of bike lanes and the algorithm of bicycle route guidance system in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.182-190
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• 2009

To solve the problems of traffic congestion, air pollution and energy derived from increased car consumption, people are in recognition of the importance of green mode, bicycle. Bicycle use rate in Busan is lower due to the terrain and limited public transportation accessibility. Therefore, geographical conditions and use activation should be initially considered in the bicycle route planning. We calculated a weight using AHP(Analytic Hierarchy Process), make a database using GIS tool and deduced the routes applying calculated weight in this study. The result of this study, We could get reliable data as inspecting consistency of the research. Routes are deducted in the place where using demand is higher than arbitrarily chosen routes. Therefore, the route planning through AHP is expected to be utilized in area-specialty-reflected route planning or bicycle road alternatives testing.

• Journal of Fashion Business
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• v.26 no.6
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• pp.47-63
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• 2022

This study aimed to examine the changes in women's fashion, focusing on the repercussions that bicycles had on women's life and fashion, centered on France in the 19th century, and then it examines the significance of the period to women's cycling clothing and its contribution to fashion. The research is based on literature and visual materials extracted from 19th century French newspapers, magazines, and posters. As a result of this study, the appearance of bicycles in the 19th century contributed to fashion as follows. First, the need for clothing suitable for outdoor activities promoted development of new designs with practical and functional features. Second, the clothing worn by female cyclists contributed to the introduction and propagation of new clothing, and pioneering wearing trousers. Third, the boom of bicycles in the 1890s led to the expansion of ready-to-wear items in department. The significance of the period to women's cycling clothing in the 19th century France is as follows. First, the era challenged customs and attitudes towards women's bicycle clothing and led to modernization. Second, a new and reasonable clothing design was presented that required a compromise to be accepted by the public. Third, although the clothing reform movement was not active in France, bloomer-style bicycle clothing was popular among fashionable women in Paris, revealing only its visual status as the capital of fashion in the 19th century.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.861-866
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• 2022

Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1123-1132
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• 2018

In this paper, we design and implement a public bicycle sharing system based on smart phone application capable of distributing access codes via internet connection. When smartphone user uses the application to request a bicycle unlock code, server receives the request and sends an encrypted code, which is used to unlock the bicycle at the station and the same code is used to return the bicycle. The station's hardware prototypes were built on top of Internet devices such as raspberry pi, arduino, keypad, and motor driver, and smartphone application basically includes shared bike rental and return functionality. It also includes an additional feature of reservation for a certain time period. We tested the implemented system, and found that it is efficient because it shows the average of 3-4 seconds delay. The system can be implemented to manage multiple bikes with a single control box, and as the user can use a smartphone application, this makes the system more cost effective.

• The Journal of Bigdata
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• v.6 no.2
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• pp.139-149
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• 2021

Ddareungi, a public bicycle service in Seoul, establishes itself as a means of daily transportation for citizens in Seoul. We speculated that the pattern of using Ddareungi may have changed since COVID-19. This study explores changes in using Ddareungi after COVID-19 with descriptive statistical analysis and network analysis. The analysis results are summarized as follows. The average traveling distance and average traveling speed have decreased over the entire time in a day since COVID-19. The round trip rate has increased at dawn and morning and has decreased in the evening and night. The average weighted degree and average clustering coefficient have decreased, and the modularity has increased. The clusters, located north of the Han River in Seoul, had a similar geographic distribution before and after COVID-19. However, the clusters, located south of the Han River, had different geographic distributions after COVID-19. Traveling routes added to the top 5 traffic rankings after COVID-19 had an average traveling distance of fewer than 1,000 meters. We expect that the results of this study will help improve the public bicycle service in Seoul.

• Journal of Digital Convergence
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• v.16 no.4
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• pp.299-306
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• 2018

This study is to measure traveling experience of bike riders whom going long distance trip. Bike paths and bike riding are crucial element for modern people's life style. At the same time, a bicycle trail is being developed by the National Bicycled-Oriented Chair Plan, which was established in 2009 by the National Bike Policy Master Plan. 13 million bike riders in Korea is keep on trying the long distance bike trip and its number is increasing every year. Accordingly, the Ministry of Public Administration and Security decides to promote the convenience of riders by developing bicycle app for long distance rider. The study attempted to assess usability of this app with 39 bike applications whom currently using the bike application. Afterwards, the researchers tests 11 hypotheses through in-depth interviews of six activated members. In sum, Bicycle travelers should be provided with bike trail guidance based on theme section skill, provided in-time speed distance related information, communicated with other bike riders, given tips for bike supplies and maintenance, and provided English language service. The study hopes to help find a customized service for bike travelers.

• The Journal of Bigdata
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• v.7 no.2
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• pp.235-244
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• 2022

The rental history data of public bicycles in Seoul were analyzed to examine how pandemic phenomena such as COVID-19 caused changes in people's micro mobility. Data for 2019 and 2021 were compared and analyzed by dividing them before and after COVID-19. Data were collected from public data portal sites, and data marts were created for in-depth analysis. In order to compare the changes in the two periods, the riding direction type dimension and the rental station type dimension were added, and the derived variables (rotation rate per unit, riding speed) were newly created. There is no significant difference in the average rental time before and after COVID-19, but the average rental distance and average usage speed decreased. Even in the mobility of Ttareungi, you can see the slow rhythm of daily life. On weekdays, the usage rate was the highest during commuting hours even before COVID-19, but it increased rapidly after COVID-19. It can be interpreted that people who are concerned about infection prefer Ttareungi to village buses as a means of micro-mobility. The results of data mart-based visualization and analysis proposed in this study will be able to provide insight into public bicycle operation and policy development. In future studies, it is necessary to combine SNS data such as Twitter and Instagram with public bicycle rental history data. It is expected that the value of related research can be improved by examining the behavior of bike users in various places.

• Information Systems Review
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• v.22 no.1
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• pp.147-165
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• 2020

The sharing economy service is now spreading in various fields such as accommodation, cars and bicycles. In particular, bicycle-sharing service have become very popular around the world, and since September 2015, Seoul has been providing a bicycle-sharing service called 'Ttareungi'. However, the number of bicycles is unbalanced among rental stations continuously according to the user's bicycle use. In order to solve these problems, we employed social network analysis using Ttareungi data in Seoul, Korea. We analyzed degree centrality, closeness centrality, betweenness centrality and k-core. As a result, the degree centrality was found to be closely linked with bus or subway transfer center. Closeness centrality was found to be in an unbalanced departure and arrival frequency or poor public transport proximity. Betweenness centrality means where the frequency of departure and arrival occurs frequently. Finally, the k-core analysis showed that Mapo-gu was the most important group by time zone. Therefore, the results of this study may contribute to the planning of relocation and additional installation of bike rental station in Seoul.