A Spatiotemporal Charging Load Forecast of Electric Taxis Based on Travel Probability Matrix

Inhalt:
With the large-scale popularization of electric taxis, their random charging load has gradually formed the characteristics of two-dimensional distribution in time and space. In order to analyze the specific distribution situation of the charging load, it is necessary to accurately describe the travel characteristics of taxis. Therefore, this paper proposes a spatiotemporal charging load forecast method of electric taxis based on travel probability matrix. Firstly, a single electric taxi model and a traffic network model are established respectively, in which the impact of urban road flow on the traffic speed is reflected by a speed-flow model. Secondly, a travel probability matrix is constructed to realize the travel simulation of a single electric taxi. Thirdly, based on above models, the spatiotemporal distribution results of electric taxis charging load in urban areas can be obtained through Monte Carlo simulation. Finally, the effectiveness of the proposed method is verified by taking the actual traffic network in a certain area as an example. The simulation results show that the electric taxis charging load has different distribution characteristics in different functional areas.