Understanding the usage of dockless bike sharing in Singapore

被引:356
|
作者
Shen, Yu [1 ,2 ]
Zhang, Xiaohu [2 ]
Zhao, Jinhua [3 ]
机构
[1] Tongji Univ, Minist Educ, Key Lab Rd & Traff Engn, Shanghai, Peoples R China
[2] Singapore MIT Alliance Res & Technol Ctr, Singapore, Singapore
[3] MIT, Dept Urban Studies & Planning, Cambridge, MA 02139 USA
基金
新加坡国家研究基金会;
关键词
Built environment; data mining; dockless; stationless bike sharing; GPS data; spatiotemporal analysis; TRAVEL; WEATHER; IMPACT;
D O I
10.1080/15568318.2018.1429696
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A new generation of bike-sharing services without docking stations is currently revolutionizing the traditional bike-sharing market as it dramatically expands around the world. This study aims at understanding the usage of new dockless bike-sharing services through the lens of Singapore's prevalent service. We collected the GPS data of all dockless bikes from one of the largest bike sharing operators in Singapore for nine consecutive days, for a total of over 14million records. We adopted spatial autoregressive models to analyze the spatiotemporal patterns of bike usage during the study period. The models explored the impact of bike fleet size, surrounding built environment, access to public transportation, bicycle infrastructure, and weather conditions on the usage of dockless bikes. Larger bike fleet is associated with higher usage but with diminishing marginal impact. In addition, high land use mixtures, easy access to public transportation, more supportive cycling facilities, and free-ride promotions positively impact the usage of dockless bikes. The negative influence of rainfall and high temperatures on bike utilization is also exhibited. The study also offered some guidance to urban planners, policy makers, and transportation practitioners who wish to promote bike-sharing service while ensuring its sustainability.
引用
收藏
页码:686 / 700
页数:15
相关论文
共 50 条
  • [41] Exploiting Interpretable Patterns for Flow Prediction in Dockless Bike Sharing Systems
    Gu, Jingjing
    Zhou, Qiang
    Yang, Jingyuan
    Liu, Yanchi
    Zhuang, Fuzhen
    Zhao, Yanchao
    Xiong, Hui
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 34 (02) : 640 - 652
  • [42] Time Series Forecasting of Dockless Bike-Sharing OD with the Weather
    Shao, Xin
    Yang, Yang
    Yao, En-Jian
    Liu, Dong-Mei
    CICTP 2023: INNOVATION-EMPOWERED TECHNOLOGY FOR SUSTAINABLE, INTELLIGENT, DECARBONIZED, AND CONNECTED TRANSPORTATION, 2023, : 806 - 816
  • [43] Nonlinear and Threshold Effects of the Built Environment on Dockless Bike-Sharing
    Chen, Ming
    Wang, Ting
    Liu, Zongshi
    Li, Ye
    Tu, Meiting
    SUSTAINABILITY, 2024, 16 (17)
  • [44] i-CHANGE: A Platform for Managing Dockless Bike Sharing Systems
    Apostolidis, Lazaros
    Papadopoulos, Symeon
    Liatsikou, Maria
    Fyrogenis, Ioannis
    Papadopoulos, Efthymis
    Keikoglou, George
    Alexiou, Konstantinos
    Chondros, Nasos
    Kompatsiaris, Ioannis
    Politis, Ioannis
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2020, PT II, 2020, 12250 : 851 - 867
  • [45] Built environment effects on the integration of dockless bike-sharing and the metro
    Guo, Yuanyuan
    He, Sylvia Y.
    TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2020, 83
  • [46] Dynamic incentive schemes for managing dockless bike-sharing systems
    Jin, Huan
    Liu, Shaoxuan
    So, Kut C.
    Wang, Kun
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2022, 136
  • [47] Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems
    Pan, Ling
    Cai, Qingpeng
    Fang, Zhixuan
    Tang, Pingzhong
    Huang, Longbo
    THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2019, : 1393 - 1400
  • [48] Citywide Bike Usage Prediction in a Bike-Sharing System
    Li, Yexin
    Zheng, Yu
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2020, 32 (06) : 1079 - 1091
  • [49] Comparison of usage regularity and its determinants between docked and dockless bike-sharing systems: A case study in Nanjing, China
    Ji, Yanjie
    Ma, Xinwei
    He, Mingjia
    Jin, Yuchuan
    Yuan, Yufei
    JOURNAL OF CLEANER PRODUCTION, 2020, 255 (255)
  • [50] Effects of dockless bike-sharing system on public bike system: case study in Nanjing, China
    Li, Weiyu
    Tian, Lixin
    Gao, Xingyu
    Batool, Humera
    INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS, 2019, 158 : 3754 - 3759