Understanding Bike Sharing Stations Usage with Chi-Square Statistics

Bike sharing systems have both great potential and great challenge for the development of smart and green urban environment. Many problems, arising from design and operation of bike sharing systems, have no easy solutions and call for complex mathematical models. Nowadays, there are a lot of sophisticated methods for understanding and administration of bike sharing systems, based on Data mining techniques, graph computations, temporal networks models, etc. At the same time, as the digitalization is accelerating, easy and affordable old-school methods are often overlooked. This paper presents a simple but efficient Chi-square test for analyzing bike sharing stations usage in mornings and evenings. The proposed method determines stations that keep the same usage patterns over time. Experiments conducted on CitiBike trip data for New York City's bike sharing service, have shown promising performance of the proposed method.