Multimodal shortest hyperpaths considering crowding in transit vehicles

Abstract

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.