Urban transportation systems are currently undergoing substantial transformations with the introduction of Shared Mobility Services (SMSs). These services provide convenient alternatives to traditional modes of transport and can help reduce the reliance on private cars. However, their impact on the overall transportation system and on users’ choices remains not fully explored, particularly when integrated with public transport (PT). To target this research gap, our study introduces a comprehensive dynamic modeling approach for intermodal transportation systems, integrating SMSs with PT. We propose a user equilibrium flow-based time-independent model to simultaneously handle path and mode choice, passenger-driver matching, and intermodality. Additionally, we use a rolling horizon approach with a trip-based macroscopic simulator to consider the system’s dynamics. The proposed framework provides a baseline for analyzing commuters’ behavior within multi-modal transportation networks. We apply the proposed framework to an analytical multi-modal network and the results validate the ability of the model to represent all interactions between the modes, formulate users’ choices at equilibrium, and capture the dynamics of traffic conditions and demand.