The recent explosive adoption of electric vehicles (EVs) and plug-in hybrid EVs (PHEVs) has sparked considerable interest in academia in developing efficient charging schemes. Supported by the advanced vehicle-to-grid network, vehicles and charging stations can, respectively, make better charging and pricing decisions via real-time information sharing. In this paper, we study the charging problem in an intelligent transportation system, which consists of smart-grid enabled charging stations and networked EVs. Each vehicle aims to select a station with the lowest charging cost by considering the charging prices and its location, while the objective of a charging station is to maximize its revenue, given the charging strategy of the vehicles. We employ a multi-leader multi-follower Stackelberg game to model the interplay between the vehicles and charging stations, in which the location factor plays an important role. We show that the equilibrium of the followers' subgame played by the vehicles exits, while the stations are able to reach an equilibrium of their subgame with respect to the charging prices. Therefore, the Nash equilibrium of the Stackelberg game is achievable using the proposed charging scheme. Finally, the performance of the proposed approach is demonstrated via extensive trace-driven simulations.