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Exploring usage pattern variation of free-floating bike-sharing from a night travel perspective
16 references·0 citing·42 second hop
Exploring usage pattern variation of free-floating bike-sharing from a night travel perspective (2024)Exploring usage pattern variation of free…The scales of human mobility (2020)The scales of human mobilityDockless bike-sharing as a feeder mode of metro commute? The role of the feeder-related built environment: Analytical framework and empirical evidence (2020)Dockless bike-sharing as a fe…Bike sharing use in conjunction to public transport: Exploring spatiotemporal, age and gender dimensions in Oslo, Norway (2020)Bike sharing use in conjuncti…A review of bicycle-sharing service planning problems (2020)A review of bicycle-sharing s…A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system (2019)A model framework for discove…Understanding the usage of dockless bike sharing in Singapore (2018)Understanding the usage of do…The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets (2018)The station-free sharing bike…Electric fence planning for dockless bike-sharing services (2018)Electric fence planning for d…Bike sharing differences among Millennials, Gen Xers, and Baby Boomers: Lessons learnt from New York City’s bike share (2018)Bike sharing differences amon…Better Understanding the Characteristics and Influential Factors of Different Travel Patterns in Free-Floating Bike Sharing: Evidence from Nanjing, China (2018)Better Understanding the Char…Universal model of individual and population mobility on diverse spatial scales (2017)Universal model of individual…Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China (2016)Exploring the impact of built…New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas (2013)New evidence on walking dista…Power-Law Distributions in Empirical Data (2009)Power-Law Distributions in Em…Understanding individual human mobility patterns (2008)Understanding individual huma…Transit network design and scheduling: A global review (2008)Transit network design and sc…The origin of bursts and heavy tails in human dynamics (2005)The scaling laws of human travel (2006)A universal model for mobility and migration patterns (2012)How popular is your paper? 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References

  • 2009Power-Law Distributions in Empirical Data8,008 cited
  • 2008Understanding individual human mobility patterns6,071 cited
  • 2008Transit network design and scheduling: A global review671 cited
  • 2018Understanding the usage of dockless bike sharing in Singapore421 cited
  • 2013New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas390 cited
  • 2020The scales of human mobility361 cited
  • 2018The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets291 cited
  • 2016Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China258 cited
  • 2017Universal model of individual and population mobility on diverse spatial scales250 cited
  • 2019A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system195 cited
  • 2018Bike sharing differences among Millennials, Gen Xers, and Baby Boomers: Lessons learnt from New York City’s bike share185 cited
  • 2020Dockless bike-sharing as a feeder mode of metro commute? The role of the feeder-related built environment: Analytical framework and empirical evidence183 cited
  • 2018Electric fence planning for dockless bike-sharing services180 cited
  • 2020Bike sharing use in conjunction to public transport: Exploring spatiotemporal, age and gender dimensions in Oslo, Norway

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175 cited
  • 2020A review of bicycle-sharing service planning problems164 cited
  • 2018Better Understanding the Characteristics and Influential Factors of Different Travel Patterns in Free-Floating Bike Sharing: Evidence from Nanjing, China163 cited
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