Abstract
As a green travel mode, bike-sharing system is becoming more and more important in urban traffic. Due to the uneven distribution of users’ demand in time and space, researchers focus on the rebalancing problems, but few of them study the dynamic time series characteristics of demand changes which is helpful to understand the user’s behavior mechanism and optimize the management strategy. Firstly, the demand fluctuation “mode” is defined by using statistical physics method, and the directed-weighted networks of the demand variation of Station Based and Free Floating Bike-sharing systems in different periods are established, the cumulative time rule of the new nodes is also given. Evolutionary differences in node strength and its distribution, average path length and Betweenness of two networks are compared, the characteristics of key modes and the transformation relationship between modes are revealed. Finally, a network similarity measure function is constructed to quantify the dependence of demand fluctuation between two systems. This paper not only describes the demand fluctuation of different bike-sharing systems in more details than other method, but also lays a foundation for green travel demand prediction. This can help operators or governments rebalance the uneven demand in time, which can make the supply more effectively match the demand.
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