Investigating Passengers’ Seating Behavior in Suburban Trains

Abstract

In pedestrian dynamics, individual-based models serve to simulate the behavior of crowds so that evacuation times and crowd densities can be estimated or the efficiency of public transportation optimized. Often train systems are investigated where seat choice may have a great impact on capacity utilization. Thus it is necessary to reproduce passengers’ behavior inside trains. Yet there is surprisingly little research on the subject. In this contribution, we collect data on seating behavior in Munich’s suburban trains, analyze it, and subsequently introduce a model that matches what we observe. For example, within a compartment, passengers tend to choose the seat group with the smallest number of other passengers. Within a seat group, passengers prefer window seats and forward-facing seats. When there is already another person, passengers tend to choose the seat diagonally across from that person. These and other aspects are incorporated in our model. We demonstrate the applicability of our model and present a qualitative validation with a simulation example. The model’s implementation is part of the free and open-source VADERE simulation framework for pedestrian dynamics and thus available for cross-validation. The model can be used as one component in larger systems for the simulation of public transport.