Estimating optimal substitution scale of urban gasoline taxis by electric taxis in the era of green energy: a case study of Zhengzhou City

Electric Taxis (ETs) are the most favored alternatives to Gasoline Taxis (GTs) in cities that aim to reduce environmental pollution. How to develop a reasonable scale on which GTs are substituted by ETs remains a challenge to governments due to the dynamics and complexity of the taxi system. To address this challenge, this paper develops a discrete-event-based simulation framework to simulate participants in the system and estimate the results under different substitution scales, which are helpful to understanding the status changing law of entities under different substitution scales, such as the operating indices of ETs, the unsatisfied travel requirements of passengers, and the usage state of charging facilities. The framework abstracts the behavioral process of ETs into three elements, namely, entity, behavior, and event. The entities are constructed from the information derived from the trajectory data. The behaviors are defined by rules following behavioral logic under anxiety psychology, which is caused by the limited range of ETs. The events are triggered based on rules from reality. With the help of this framework, a multi-objective optimization model is developed to obtain the optimal substitution scale of GTs in the case study area of Zhengzhou City. Overall, the approach could provide a practical tool to address this challenge, which could support further studies of the effect of ETs on urban taxis.

Automated summary

This paper develops a discrete-event-based simulation framework to simulate the optimal substitution scale of electric taxis (ETs) for gasoline taxis (GTs) in order to understand the status changing law of entities under different scales. It provides a practical tool to support further studies of the effect of ETs on urban taxis.