Analysis of the Use Characteristics and Influencing Factors of Shared Bikes

As mobile communications technology and the Internet advance rapidly, stake less shared bicycles have rapidly gained popularity worldwide, becoming an essential approach to alleviating urban traffic congestion and enhancing the efficiency of public transportation links However, with the widespread use of shared bikes, problems such as irrational scheduling, imbalance between supply and demand, and difficulties in parking management have been exposed. To solve these problems, this study analyzes the usage characteristics and influencing factors based on big data of shared bikes in New York City. This study employs data visualization, ordinary least squares regression (OLS) model and geographically weighted regression (GWR) model to provide an in-depth analysis of the usage patterns of shared bicycles. The results show that the use of shared bicycles has significant spatial and temporal characteristics, which are mainly influenced by factors such as population density, transportation infrastructure and surrounding dining facilities. Commuting demand is evident Especially during weekday morning and evening rush hours, between commercial districts and residential neighborhoods; while in areas with dense food and beverage facilities, the frequency of use increases significantly during lunch and dinner hours.