Modeling congestion effects arising from multiple travel modes, shared mobility modes in particular, is non-trivial because of the complex interactions among diverse agents and distinct traffic flow compositions. This research aims to provide a theoretical framework of generic traffic network equilibria to unify these services and hopefully become a step stone to modeling shared mobility services in congested road network. In the proposed framework, we mainly focus on three modes: driving solo, ridesharing, and e-hailing service. The four types of traffic flows are: personal vehicle drivers, e-hailing drivers, ridesharing riders, and e-hailing passengers. The first two flows contribute to traffic congestion while the latter two do not. To capture their interactions, a super extended network is created with four copied networks each of whom represents one type of traffic flow. The equilibrium of new mobility systems can then be reformulated as a quasi-variational inequality and solution existence is discussed. The numerical results are tested in both Braess network and Sioux Falls network to illustrate the impact of different parameters on equilibrium outcomes, including modal cost, system travel time and deadhead miles. The results of this model will help assist transportation planners in making policy and regulation decisions regarding shared mobility services.