Volume 40 Issue 3
Jun.  2022
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Article Navigation >  Journal of Transport Information and Safety  > 2022  >  40(3): 146-153
LI Fu, XU Liangjie, CHEN Guojun, ZHU Ranbo. An Analysis of Spatial-temporal Characteristics of Origin and Destination of Shared-bike Users[J]. Journal of Transport Information and Safety, 2022, 40(3): 146-153. doi: 10.3963/j.jssn.1674-4861.2022.03.015
Citation: LI Fu, XU Liangjie, CHEN Guojun, ZHU Ranbo. An Analysis of Spatial-temporal Characteristics of Origin and Destination of Shared-bike Users[J]. Journal of Transport Information and Safety, 2022, 40(3): 146-153. doi: 10.3963/j.jssn.1674-4861.2022.03.015
shu

An Analysis of Spatial-temporal Characteristics of Origin and Destination of Shared-bike Users

doi: 10.3963/j.jssn.1674-4861.2022.03.015
  • 1.

    School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China

  • 2.

    School of Automotive and Traffic Engineering, Hubei University of Arts and Science, Xiangyang 441053, Hubei, China

  • Received Date: 2020-12-23
    Available Online: 2022-07-25
    Abstract
  • In a view of the frequent imbalance between supply and demand and uneven distribution of shared bikes over space, this paper studies the origin-destination distribution of shared-bike users and the temporal characteristics of riding demand in different areas, so as to provide theoretical support for dispatch operations of shared-bike systems. Based on riding data of users, the mean-shift algorithm is used to cluster the origin and destination points of riding, and the distribution of areas with a high riding record is obtained. Then, Spearman correlation coefficient is used to measure the similarity of temporal characteristics of riding demand. Six typical temporal characteristics of riding demand are extracted by clustering the temporal cumulative differences between the volumes of rented and returned bikes in different areas. The relationship between temporal characteristics of riding demand and land use (represented by point of interest, POI)is studied by factor analysis. The results show that the spatial distribution of aggregation areas of shared bikes is basically correlated to the spatial pattern of the urban road network in the area. There is little variation for the distribution of aggregation areas in different time periods, and the only difference is the volume of bike riding in different areas. Besides, it shows that temporal characteristics of riding demand and land use are related. Commercial land use is the dominating factor for the areas where the number of rented bicycles is less than that of returned bicycles in one day, which accounts for 40% of the total. For the areas where the number of rented bicycles is larger than that of returned bicycles in one day, residential land use is the dominating factor, accounting for 57% of the total. In areas with mixed land use, the difference between bicycle renting and returning is small and prone to fluctuate. In addition, the proportion of dominant factors of a temporal characteristics of riding demand may change between weekday and weekend, and the temporal characteristics of riding demand in a region are different between weekday and weekend.

     

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