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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2018  >  18(1): 150-158
TANG Lu-liang, CHEN Xi, YANG Xue, ZHANG Xia, LI Qing-quan. Public bicycle usage modeling based on urban land use[J]. Journal of Traffic and Transportation Engineering, 2018, 18(1): 150-158. doi: 10.19818/j.cnki.1671-1637.2018.01.014
Citation: TANG Lu-liang, CHEN Xi, YANG Xue, ZHANG Xia, LI Qing-quan. Public bicycle usage modeling based on urban land use[J]. Journal of Traffic and Transportation Engineering, 2018, 18(1): 150-158. doi: 10.19818/j.cnki.1671-1637.2018.01.014
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Public bicycle usage modeling based on urban land use

doi: 10.19818/j.cnki.1671-1637.2018.01.014
  • 1.

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, Hubei, China

  • 2.

    School of Urban Design, Wuhan University, Wuhan 430070, Hubei, China

  • 3.

    College of Civil Engineering, Shenzhen University, Shenzhen 518060, Guangdong, China

More Information
  • Author Bio:

    TANGLu-liang(1973-), male, professor, PhD, till@whu.edu.cn

  • Received Date: 2017-09-06
  • Publish Date: 2018-02-25
    Abstract
  • The public bicycle travel pattern was divided into three phases, namely going to a station, riding after renting, and leaving after returning.The influence of urban land use on public bicycle usage was investigated for each phase.For the first and third phases, the points of interst were used to measure the type of urban land use surrounding public bicycle station.By introducing time satisfaction function, a modeling method of the prediction of public bicycle demand and attraction was proposed based on multiple regression analysis.For the second phase, six influence factors of public bicycle usage related to urban land use were established, including the bicycle demand of origin station, the density of origin station, the remoteness of origin station, the attraction of destination station, the distance between origin and destination station, and the land use difference between origin and destination station.961 865 and 1 185 816 records of public bicycle usage respectively from New York and Shanghai were analyzed by using multipleregression analysis.Analysis result indicates that for the records of New York and Shanghai, the modeling method yields higher determination coefficients (0.738 and 0.607) than the traditional method (0.581 and 0.474) when the number of land use factors is invariable.All of six proposed factors have significant influence on the traffic volumes between the stations in bicycle traffic volume model, and the adjusted determination coefficient is 0.487.In conclusion, the modeling method can measure the influence of urban land use on the public bicycle usage more feasibly, and it provides a more accurate model of trip demand at stations, traffic volume between stations, and attraction of stations for public bicycle trips.

     

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