Estimating model for urban carrying capacity on bike-sharing

Abstract

As the demand for bike-sharing has been increasing, the oversupply problem of bike-sharing has occurred, which leads to the waste of resources and disturbance of the urban environment. In order to regulate the supply volume of bike-sharing reasonably, an estimating model was proposed to quantify the urban carrying capacity (UCC) for bike-sharing through the demand data. In this way, the maximum supply volume of bike-sharing that a city can accommodate can be obtained. The UCC on bike-sharing is reflected in the road network carrying capacity (RNCC) and parking facilities’ carrying capacity (PFCC). The space-time consumption method and density-based spatial clustering of application with noise (DBSCAN) algorithm were used to explore the RNCC and PFCC for bike-sharing. Combined with the users’ demand, the urban load ratio on bike-sharing can be evaluated to judge whether the UCC can meet users’ demand, so that the supply volume of bike-sharing and distribution of the related facilities can be adjusted accordingly. The application of the model was carried out by estimating the UCC and load ratio of each traffic analysis zone in Nanjing, China. Compared with the field survey data, the effect of the proposed algorithm was verified.