We present a transit equilibrium model in which boarding decisions are stochastic. The
model incorporates congestion, reflected in higher waiting times at bus stops and increasing
in-vehicle travel time. The stochastic behavior of passengers is introduced through a
probability for passengers to choose boarding a specific bus of a certain service. The modeling
approach generates a stochastic common-lines problem, in which every line has a
chance to be chosen by each passenger. The formulation is a generalization of deterministic
transit assignment models where passengers are assumed to travel according to shortest
hyperpaths. We prove existence of equilibrium in the simplified case of parallel lines (stochastic
common-lines problem) and provide a formulation for a more general network
problem (stochastic transit equilibrium). The resulting waiting time and network load
expressions are validated through simulation. An algorithm to solve the general stochastic
transit equilibrium is proposed and applied to a sample network; the algorithm works well
and generates consistent results when considering the stochastic nature of the decisions,
which motivates the implementation of the methodology on a real-size network case as
the next step of this research.