Spatio-temporal Analysis of Precipitation Effects on Bicycle-Sharing Systems with Tensor Approach

Bicycle-sharing systems (BSS) have become an increasingly popular form of sustainable transportation in urban areas. This study investigates the effect of precipitation on BSS demand using data from the Divvy system in Chicago during May 2020, which experienced the wettest May in the last 150 years. It has been found that the number of BSS trips did not necessarily decrease on rainy days, with the intensity and hours of rainfall being crucial factors affecting changes in demand. High rainfall intensity throughout the day or during BSS peak demand hours significantly reduces trips. Moreover, warnings of river overflow and road flooding, even with insignificant amounts of precipitation, lead to a considerable reduction in trips. However, scattered showers of low intensity during non-peak hours can contribute to increased travel. Study's horizontal slices correlation (HSC) research results indicate that the number of trips for different days follows a highly similar pattern of change.