Traffic Equilibrium Considering Heterogeneity Across Electric Vehicles

Rapid growth in the number of electric vehicles (EVs) calls for research on traffic equilibrium in urban transportation networks (UTNs). As a result of the interaction of EVs and fast charging stations (FCSs), traffic flow is influenced by EV drivers’ charging preferences. However, little research investigates the impact of heterogeneous charging preferences across EV drivers on the traffic flow at traffic equilibrium. This paper establishes a traffic model where the heterogeneity across EV drivers is reflected in the monetary value of time and sensitivity to electricity prices. Based on the traffic model, we propose a Stackelberg game to model the interaction of EVs and FCSs while ensuring the user equilibrium of UTN. The game features a hierarchical structure. At the higher level, FCSs play a non-cooperative game by strategically setting electricity prices with imperfect information of other FCSs. At the lower level, EVs play an evolutionary game to charge at FCSs with the lowest cost. An adaptive step control method is designed to prevent potential oscillations near the Nash equilibrium. Numerical results show that the difference in EV flow on the road can reach 18.42% without considering heterogeneity and considering heterogeneity. The proposed framework can illustrate how the heterogeneity across EVs influences the formation of traffic flow in traffic equilibrium calculation.