Abstract:

Aiming at the problem of tidal supply-demand imbalance of shared bicycles， a built environment indicator system was constructed from the three dimensions of socio-demographic， transportation design， and land use. Based on the Agglomerative Hierarchical Clustering model， typical time-aggregation patterns of shared bicycles were obtained from clustering. The nonlinear relationship and the threshold effect between them were revealed by using the Random Forest and SHapley Additive exPlanations models. Ultimately， Kunming was an example to prove that. The results show that the temporal aggregation modes of shared bicycles mainly show the first-in-last-out mode and the first-out-last-in mode， accounting for 91.4% of the sum of all modes. There is a significant nonlinear relationship between the built environment and the temporal aggregation modes of shared bicycles. The temporal aggregation modes of shared bicycles are primarily influenced by the density of the bus line network， proximity of parks and attractions， proximity of metro stations， and POI density of companies. When the proximity of metro stations is less than 0.5 km， there is an elevating effect on the probability of showing the first-in-last-out mode. When the POI density of companies is less than 25 per cell， there is a depressing effect on the probability of showing the first-in-last-out mode.

Key words: engineering of communication and transportation system, shared bicycle, temporal aggregation modes, random forest classifier, nonlinear influence, built environment