This article takes three bicycle sharing systems as the research object, the Citi Bike of New York City, the Capital Bike share of Washington and the Divvy of Chicago. Adopting the method of Data mining, the corresponding long-term historic credit card data, bicycle sharing system location data and the land-use properties coming from three bicycle sharing systems are compared and analyzed to get bicycle sharing system in seasonal, spatial and temporal distribution, site symmetry aspects of trip characteristics, which provides support for bicycle sharing system Operational decisions.
IC Card-Based Data Mining Characteristics of Urban Public Bicycles
Fifth International Conference on Transportation Engineering ; 2015 ; Dailan, China
ICTE 2015 ; 2124-2132
25.09.2015
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Traffic accident characteristics and association analysis of electric bicycles based on data mining
British Library Conference Proceedings | 2022
|Transportation Research Record | 2014
|Origin-Destination Distribution Prediction Model for Public Bicycles Based on Rental Characteristics
British Library Conference Proceedings | 2018
|