Dynamic wireless charging technology has emerged, enabling electric vehicles to charge while in motion. Considering the substantial cost associated with dynamic wireless charging, it is evident that plug-in charging and dynamic wireless charging will coexist for an extended period. To address the current research gap concerning the selection of charging infrastructure locations for multiple types of vehicles, including gasoline-powered ones, a bi-level optimization model is proposed. The upper-level model aims to determine the optimal charging facility locations within a given budget, minimizing the total travel cost of the system. In contrast, the lower-level model incorporates a multi-class user equilibrium framework to capture route preferences for both gasoline and electric vehicles. Genetic algorithms were employed to solve and assess the impact of critical parameters such as electric vehicle adoption rates and investment levels on the outcomes.