Analysis of the spatiotemporal riding modes of dockless shared bicycles based on tensor decomposition

ABSTRACT

Studies on the riding modes of shared bicycles have aimed to heighten the understanding of cycling characteristics. This paper analyzes the spatiotemporal riding modes of shared bicycles based on tensor decomposition in Beijing, China. Two third-order tensors are constructed for the origin and destination points of shared bicycles in the day, hour, and space dimensions. Three factor matrices explicitly reveal two modes, three modes, and six modes in the day dimension, hour dimension, and space dimension, respectively. The relationships among the different modes in the three dimensions are demonstrated in an interaction table. Further, the density for different types of points of interest (POIs) are calculated to further analyze the potential riding purpose for different riding modes. Notably, the main POI types for the areas of O2 and D2 modes are consistent with the areas of D3 and O3 modes, which reflects the tidal characteristics of the commuting activities of shared bicycles. The main functional areas are inferred according to the riding modes and POIs, which enables verification of the correctness of the obtained riding modes to some extent. By method comparison, tensor decomposition shows the advantage of being able to reveal the spatiotemporal modes among multiple dimensions.