other players, which may be overly restrictive and infeasible in a practical competitive market. In this paper, we propose a Bayesian game framework that does not require the complete information of other players.

The main contributions of our work are: (1) A multi-stage charging station placement strategy with incremental EV penetration rates is first formulated, which takes into account the interactions among EVs, road network, and the electric power grid; (2) The nested logit model is then employed to characterize the overall consumer satisfaction and predict the aggregated charging demand, which provides insights into the preferences and decision-making processes of EV owners; (3) An oligopolistic market model of EV charging service providers is studied and a Bayesian game framework is applied to analyze the strategic interactions among service providers. (4) A simulation software has been developed to analyze the interplay among EV owners, road network, power grid, urban infrastructure and charging stations [^3].

The paper is organized as follows: Section [slowromancap2@]{} presents the problem formulation. Section [slowromancap3@]{} discusses the nested logit model and how charging demand is calculated. In Section [slowromancap4@]{}, we describe the impact of EV charging on the power grid. In Section [slowromancap5@]{}, a Bayesian game is used 