• Journal of Trauma and Injury
• /
• v.22 no.2
• /
• pp.128-133
• /
• 2009

Purpose: Bicycle riding is a healthy and cheap form of transportation and a popular form of recreation. This study aims to evaluate the epidemiology and the factors affecting the severity of bicycle-related injuries and to find effective methods for preventing injuries. Methods: This is a retrospective study of the patients'characteristics, the injury severity, the injury location, the effect of safety equipment on the bicycle injury based on information collected through the NEDIS (National Emergency Department Information System) from 1,284,429 patients who visited 55 emergency rooms nationwide. Results: During the research period throughout 55 emergency rooms 5,671 patients were seen because of bicycle injuries. The male-to-female ratio was 3.1:1, the median age 28 years old, and 42.6% of the patients were younger than 20 years old. Injury sites were mostly in the extremities(46.7%), the head(32.4%), and the face(14%), and 70.3% of severely injured patients had accompanying head trauma. Males aged 65 and older was possibly associated with severe head trauma. Of the patients who provided helmet information 4.8%(71patients) used helmets, and 95.2%(1392 patients) did not. In this group of patients providing helmet information, none of those wearing helmets died, but 0.4% of those not wearing helmets died. Conclusion: In this study, most bicycle injuries occurred in young adult men. From now, there seems to be a need for more effort on publicity activities on bicycle injuries and on the education of children and teenagers, who show a high incidence rate, and of senior citizens (over 65 years old) who show a high severity rate, about using a safety helmet to reduce the severity of injury.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.6
• /
• pp.3037-3054
• /
• 2019

Public bicycle system (PBS) is a new emerging and popular mode of public transportation. PBS data can be adopted to analyze human movement patterns. Previous work usually focused on specific scales, and the relationships between different levels of hierarchies are ignored. In this paper, we introduce a multi-scale and interactive visual analytics system to investigate human cycling movement and PBS usage condition. The system supports level-of-detail explorative analysis of spatio-temporal characteristics in PBS. Visual views are designed from global, regional and microcosmic scales. For the regional scale, a bicycle network is constructed to model PBS data, and an flow-based community detection algorithm is applied on the bicycle network to determine station clusters. In contrast to the previous used Louvain algorithm, our method avoids producing super-communities and generates better results. We provide two cases to demonstrate how our system can help analysts explore the overall cycling condition in the city and spatio-temporal aggregation of stations.

• Korean Journal of Artificial Intelligence
• /
• v.10 no.1
• /
• pp.9-14
• /
• 2022

The demand for public bicycles operated by the Seoul Metropolitan Government is increasing every year. The size of the Seoul public bicycle project, which first started with about 5,600 units, increased to 3,7500 units as of September 2021, and the number of members is also increasing every year. However, as the size of the project grows, excessive budget spending and deficit problems are emerging for public bicycle projects, and new bicycles, rental office costs, and bicycle maintenance costs are blamed for the deficit. In this paper, the Azure Machine Learning Studio program and the Boosted Decision Tree Regression technique are used to predict the number of public bicycle rental over environmental factors and time. Predicted results it was confirmed that the demand for public bicycles was high in the season except for winter, and the demand for public bicycles was the highest at 6 p.m. In addition, in this paper compare four additional regression algorithms in addition to the Boosted Decision Tree Regression algorithm to measure algorithm performance. The results showed high accuracy in the order of the First Boosted Decision Tree Regression Algorithm (0.878802), second Decision Forest Regression (0.838232), third Poison Regression (0.62699), and fourth Linear Regression (0.618773). Based on these predictions, it is expected that more public bicycles will be placed at rental stations near public transportation to meet the growing demand for commuting hours and that more bicycles will be placed in rental stations in summer than winter and the life of bicycles can be extended in winter.

• Journal of Korean Society of Transportation
• /
• v.33 no.2
• /
• pp.125-135
• /
• 2015

In this study our main focus is to verify the relationship between social value of transportation system and its perceived features. To achieve this objective, we investigated the value of public bike system (PBS) through willingness to pay (WTP) analysis using contingent valuation method (CVM) and the survey was conducted for 1726 respondents who live in Suwon, Korea. Moreover the determinants related to features related to bicycle use were also gathered. The estimated binary logistic regression and censored regression reveal that the value of PBS is influenced by perceived features towards bicycle use incorporating non-congestion, transportation mode like auto and bus, and high mobility system as well as other variables such as income, bicycle ownership etc. Furthermore the results show that the perceiving of positive features to bicycle use leads to higher social value of PBS. Based on the findings, we discuss the importance of pre-review for transport policy implementation, and also explore the possibilities for application to PBS.

• Journal of Korean Society of Transportation
• /
• v.12 no.1
• /
• pp.85-95
• /
• 1994

While bicycles are an exhaust-free and low energy consuming mode of transport, the use of them is getting decreased. The aim of this research is to find out current levels of bicycle ownership and to estimate the ownerships of the bicycles by spatial structure and social factors in the metropolitan area. The parameters which affect on the characteristics of the bicycle ownership are classified into aggregate and disaggregate categories. The ownerships of the bicycles are estimated by the multiple regression analysis using urban characteristics data and the binary logit analysis using household characteristics data. The results of this study to population, car ownership, and number of male in the household, and negatively by the population density.

• Transactions of Materials Processing
• /
• v.22 no.1
• /
• pp.42-47
• /
• 2013

The bicycle is one of the most important eco-friendly transport methods which can mitigate global warming. The portability of a bike on public transportation systems is essential for the wide spread use of bicycles by people in urban environments. In this study, a lightweight urban folding bike was developed with careful consideration of the association with public transport. A folding frame using a moving slide link mechanism made from AL6061 is proposed. Numerical analysis was conducted to evaluate structural safety of the bike in both vertical and pedal loading tests. The proposed urban folding bicycle weights only 10kg and summation of its width, length, and height in the folded configuration is under 158cm.

• Journal of Auto-vehicle Safety Association
• /
• v.12 no.1
• /
• pp.6-14
• /
• 2020

Personal mobility, which was used exclusively for leisure activities, has recently been used as a means of transportation, and it is expected to increase its role as the next generation transportation. Sales of personal mobility are increasing rapidly, but the problem is that traffic accidents are also increasing. In this study, human body injury caused by various collisions between electric wheel users and road users that occur on bicycle or pedestrian roads mainly used by personal mobility is analyzed through collision analysis and collision risk analysis. In the case of the collision accident for electric wheel, it is analyzed that the road users are more likely to be injured on the pedestrian road than the bicycle road. In addition, the head hit each other or fall and hit the floor caused severe head injury.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.433-434
• /
• 2019

이 논문은 공공 빅 데이터를 활용하여 '서울자전거 따릉이'를 기반으로 자전거 교통 데이터베이스 시스템을 제작하고, 제작한 데이터베이스 시스템을 활용하는 예시를 보여주고 있습니다. 데이터베이스 시스템의 제작 과정을 통하여 데이터베이스 설계, 데이터 수집, 제작 및 가공 과정, 데이터베이스 시스템의 유용한 활용 예시를 확인할 수 있습니다. 버스, 택시와 같이 따릉이와 연계할 수 있는 다양한 대중교통 데이터를 추가로 활용한다면 더욱 정확하게 따릉이의 발전방향과 혼잡한 교통 환경 개선을 제시할 수 있는 유용한 정보를 도출할 수 있을 것이다.

• Journal of Korean Society of Transportation
• /
• v.27 no.4
• /
• pp.17-30
• /
• 2009

Recently, Interest in the riding of bicycles increased, but existing researches on the effect of bicycle facilities and the supply analysis and evaluation bike analysis of the importance of the item is most fulfilling. Those do not reflect characteristics of the region and the current satisfaction on the riding of bicycles. Therefore, this research will classify Gu Dong of Busan into good region, possible region and difficult region on the riding of bicycles to reflect characteristics of bicycles with the non-power and characteristics of riders with the main purpose of the exercise. Maintenance of bicycles classified according to the region will be decided to the Line-to-Line maintenance as to connect the main point of regions and to the Point-to-Point as to link the main point within region. Then, step-by-step bicycles activation of Busan differentiated by region offers. Also, Survey on Gangseo-Gu, Sasang-Gu, Gijang-Gun with good bicycle conditions and Busan-Jin-Gu with the best maintenance effect will be about the bicycle. The structure model of consciousness-based on the use of bicycles will be made by using Survey results and considering the region characteristics. This structure model will show a correlation of the current satisfaction, the bicycle-related facilities maintenance policy needs, region characteristics and the next intends to riding the bicycle.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.2D
• /
• pp.217-225
• /
• 2011

Currently our country has very serious problems of traffic congestion and urban environment due to increasing automobile ownership. Recently, our concern about environmentally sustainable transportation and green transportation is increasing, so the government is pushing ahead the policy of bicycle using activation. So it is needed to develop a model to analyze the service level of bicycle roads more realistically. In this study, a neuro-fuzzy inference model to analyze the service level of bicycle roads was built selecting the width of bicycle roads, the number of conflicts during cycling and pedestrian volume, which have fuzzy characteristics, as input variables. The predictability of the model was evaluated comparing the surveyed and the estimated. The values of the statistics, $R^2$, MAE and MSE were 0.987, 0.142, 0.032. Therefore, It may be judged that the explainability of the model is very high. The service levels of bicyle roads estimated by the model are 1~3 steps lower than KHCM assessments. The reason may be explained that the model estimates the service level considering the width of bicycle roads and the number of conflicts simultaneously besides pedestrian volume.