Origin-Destination Distribution Prediction Model for Public Bicycles Based on Rental Characteristics

Abstract

Accurate prediction of the rental demand origin-destination distribution of public bicycles provides a foundation according to which layout planning, operational management and dispatching of bicycle sharing system stations may be achieved. Based on the conventional double-constrained gravity model, the rental duration distribution function was employed as a distribution impedance function in order to establish a prediction model for the origin-destination distribution of public bicycles in a bicycle sharing system. The expense incurred by the weighted average travel time of the bicycle sharing system located in the old town of Zhenhai District, Ningbo, was applied to test the origin-destination distribution prediction model for public bicycles based on characteristics of rental duration distribution. Results indicate that the established model demonstrates high precision and can be used to effectively predict the origin-destination distribution of bicycle sharing systems, thus avoiding the dense distribution over short distances which results from the conventional double-constrained gravity model.