• Title/Summary/Keyword: Dockless

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Derivation of Factors Affecting Demand for Use of Dockless Shared Bicycles Based on Big Data (빅데이터 기반의 Dockless형 공유자전거 이용수요 영향요인 도출)

  • Kim, Suk Hee;Kim, Hyung Jun;Shin, Hye Young;Lee, Hyun Kyoung
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.3
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    • pp.353-362
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    • 2023
  • In this research, the usage status and characteristics of user big data of Mobike, a dockless bike sharing service introduced in Suwon city, were analyzed, and multiple regression analysis was performed to identify factors influencing the demand for dockless bike sharing service. For analysis, usage data of bike sharing system in Suwon city in 2019 were obtained, and they were organized by areas. As a result of analyzing the characteristics of the influencing factors selected for each area, it was found that the extension of bicycle roads shows high in areas with high demand for bicycles or adjacent areas. Also, the population of 10-30's shows high in areas with high demand for bicycles or adjacent areas. In addition, it was analyzed that the use of bike sharing system is high in areas with high maintenance rate of bicycle roads and large-scale residential and commercial facilities near residential districts and adjacent areas. As a result of the multiple regression analysis, it is analyzed that length of bicycle·pedestrian roads (non-separated), population of 10-30's, number of railway stations, number of schools, number of commercial facilities, number of industrial facilities factors were significant. It is expected that it may be possible to create an environment in which citizens want to use dockless bike sharing service by identifying factors affecting the number of stationless shared bicycles. Also, the results of data analysis are considered to be contributing to policy data to promote the use of dockless bike sharing.

Study on Shared E-scooter Usage Characteristics and Influencing Factors (공유 전동킥보드 이용 특성 및 영향요인에 관한 연구)

  • Kim, Su jae;Lee, Gyeong jae;Choo, Sangho;Kim, Sang hun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.1
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    • pp.40-53
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    • 2021
  • Recently, shared dockless e-scooter usage has rapidly increased, rather than the station-based shared mobility service, because of convenience. This transition leads to new social problems in urban areas such as increased traffic accidents and hindrance of pedestrian environments. In this study, we analyze the usage characteristics of shared e-scooters in Seoul, and identify factors influencing demand for shared e-scooters by developing a negative binomial regression model. As a result, the usage characteristics show that the average trip distance, the average trip duration, and the average trip speed were 1.5km, 9.4min, and 10.3km/h, respectively. Demographic factor, transport facility factors, land use factors, and weather factors have statistically significant impacts on demand for shared e-scooters. The results of this study will be used as basic data for suggesting effective operation strategies for areas with higher shared e-scooter demand and for establishing transport policies for facilitating shared e-scooter usage.

A Study on the Satisfaction Differences in Dockless Bike in Suwon City (스테이션 없는 공유자전거 이용 만족도 차이 분석연구(수원시 사례를 중심으로))

  • Kim, Sukhee;Lee, Nam il
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.2
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    • pp.157-166
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    • 2020
  • The city of Suwon has introduced a dockless bike for the first time in Korea. In this study, a questionnaire was conducted for citizens to suggest improvement through satisfaction analysis. As a result of the survey, 88 % of respondents awarded the presence of a bike, and 90 % answered positively in terms of bike policy; whereas mature civic ethics showed an low satisfaction. For the purpose of usage, approximately 75 % of users mainly used for commuting, business, shopping, and the connection with mass transit. In the result of the primary means of a trip, a private car was most preferred before operation; However, it was found that mode transition has been actively carried out. This suggests significant implications for implementing sustainable urbanism. Meanwhile, The level of satisfaction significantly differed in the field of payment method, charge, usage guidance and publicity by an occupation and age groups commonly. Satisfaction in bike maintenance was statistically differed by an occupation. Satisfaction in Rental-return and registration procedures showed differences by an age groups. The results of this study will contribute to establishment related policies and to more activate dockless shared bike.

Optimizing Locations for Micro-mobility Parking Area based on User Big-data Analysis (빅데이터 기반 공유형 마이크로 모빌리티의 주차시설 입지 최적화 연구)

  • Choi, Nakhyeon;Kim, Junghwa
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.2
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    • pp.195-206
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    • 2023
  • Most of the Micro-mobility parking in Korea use Dockless system. However, Dockless can result in cluttering, infrastructure deficiencies, and safety challenges as has been observed in cities. It is necessary to introduce a Station Parking system in order to solve the drawbacks of the dockless, but the introduction without engineering has low accessibility and induces side effects. In this study, to decide optimal location about number of the Micro-mobility Station, we has been applied the MCLP model about the coverage range, usage demand, usage time in order to classify the type of Micro-mobility Station. For the MCLP, User Date input to reflect realistic demand in Bundang new town, Korea. The result show that the optimal number of facilities in 400 m was 146, and the coverage ratio was 99.83 %, which was most suitable coverage for solving the parking problem. We also classified the demand into 4 levels and the usage time into 3 levels, and by crossing them, we were able to classify the Parking lot types into 12 types. It is possible to propose strategic policies in the installation and operation of Micro-mobility Parking System.

Unlocking Shared Bike System by Exploiting an Application Log (애플리케이션 로그를 이용한 공유 자전거 시스템의 잠금장치 해제 방법)

  • Cho, Junwan;Lee, Jeeun;Kim, Kwangjo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.4
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    • pp.719-728
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    • 2019
  • Recently, there has been a growing market for shared mobility businesses that share 'transport' such as cars and bikes, and many operators offer a variety of services. However, if the fare can not be charged normally because of security vulnerability, the operator can not continue the business. So there should be no security loopholes. However, there is a lack of awareness and research on shared mobility security. In this paper, we analyzed security vulnerabilities exposed in application log of shared bike service in Korea. We could easily obtain the password of the bike lock and the encryption key of the AES-128 algorithm through the log, and confirmed the data generation process for unlocking using software reverse engineering. It is shown that the service can be used without charge with a success rate of 100%. This implies that the importance of security in shared mobility business and new security measures are needed.

Analysing Spatial Usage Characteristics of Shared E-scooter: Focused on Spatial Autocorrelation Modeling (공유 전동킥보드의 공간적 이용특성 분석: 공간자기상관모형을 중심으로)

  • Kim, Sujae;Koack, Minjung;Choo, Sangho;Kim, Sanghun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.1
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    • pp.54-69
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    • 2021
  • Policy improvement such as the revision of the Road Traffic Act are proposed for personal mobility(especially e-scooter) usage. However, there is not enough discussion to solve the problem of using shared e-scooter. In this study, we analyze the influencing factors that amount of pick-up and drop-off of shared e-scooter by dividing the Seoul into a 200m grid. we develop spatial auotcorrelation model such as spatial lag model, spatial error model, spatial durbin model, and spatial durbin error model in order to consider the characteristics of the aggregated data based on a specific space, and the spatial durbin error model is selected as the final model. As a result, demographic factor, land use factor, and transport facility factors have statistically significant impacts on usage of shared e-scooter. The result of this study will be used as basic data for suggesting efficient operation strategies considering the characteristics of weekday and weekend.