A Demand Truncation and Migration Poisson Model for Real Demand Inference in Free-Floating Bike-Sharing System

Abstract

The free-floating bike-sharing system enables users to pick up bikes from everywhere. However, the spatial-temporal imbalance of bikes becomes severer in such systems. Consequently, bikes are sometimes not available at desired location and time, and the pick-up demand of users is truncated. On demand truncation, the bike user would either give up using the bike or migrate to the nearby to pick up the bike. Thus, the demand of bikes observed from smart locks does not equate with the real demand. However, capturing the real demand is crucial for system planning and operation. Therefore, a statistical model, namely the demand truncation and migration Poisson (DTMP) model, is proposed to analyze the real demand. It is able to jointly model the real demand of FFBS and the migration behavior of users. In particular, we analyzed the demand truncation and migration processes to establish the relationship between the expected value of observed demand and that of real demand. Then, the real demand of using bikes was assumed to be related to the influential factors and the demand function was formulated. Subsequently, the likelihood for each observation was established. The performance of the proposed model was evaluated through field-testing data. The results revealed that the proposed DTMP model is superior to the baseline Poisson model from both the fitness and accuracy perspectives. Finally, the spatial-temporal distribution of the real demand and unmet demand of bikes in typical hours are presented. The results can guide the efficient management of the bike-sharing system.

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