A large-scale empirical study on impacting factors of taxi charging station utilization

Charging station planning is critical in the implementation of public transport electrification. However, in cities, there is insufficient experience and knowledge of the factors that influence the utilization of charging stations, particularly charging stations aimed at serving a fleet of electric taxis. Shenzhen is one of the pioneers in promoting electric taxis. In this paper, we collect large-scale datasets from Shenzhen and provide a data-driven space–time analysis of the relationship between charging station utilization and urban form and demand for taxi services. We use a Random Forest Regression model to explore these relationships and apply a Shapley value method to interpret the results. We find that demand for taxi services, measured as hourly pick-up and drop-off densities, have a non-linear relationship with utilization. Metro station density positively correlates with utilization, whereas the relationships between population density, land-use entropy, road density, and bus station density are more complicated.