In rush hours, the onboard crowd level within transit vehicles is a problem of any large city.
At the expense of time savings, some users will avoid riding crowded lines if they consider
that transit vehicles do not have enough personal space. This paper presents a hypergraph
model and an algorithm to find multimodal shortest hyperpaths considering the user
constraints on the sequence of boarded modes and their preferences of onboard crowding
levels. It is assumed that transit inter-arrivals are random. A penalty for riding transit
vehicles is defined to model how the users perceive the onboard crowd levels. This penalty
depends on the onboard crowd levels and the seating capacity of the vehicles. A stateautomaton
is used to model the user constraints on the sequence of boarded modes. To find
the shortest hyperpaths, the user selects their origin, destination, the maximum number of
modal transfers, and the onboard crowd level threshold. A use case on a sample multimodal
network is presented.
