Determinants of passengers' metro car choice revealed through automated data sources: a Stockholm case study

We propose a methodology based on multiple automated data sources for evaluating the effects of station layout, arriving traveler flows, and platform and on-board crowding on the distribution of boarding passengers among individual cars of metro trains. The methodology is applied to a case study for a sequence of stations in the Stockholm metro network. The findings suggest that passengers opt for less crowded train cars in crowded situations, trading-off walking and in-vehicle crowding while waiting and riding. We find that the boarding car distribution is also affected by the locations of platform access points and the distribution of entering traveler flows. These insights may be used by transit planners and operators to increase the understanding of how passengers behave under varying crowding conditions, identify the factors that affect travelers' choice of metro car and eventually reduce experienced on-board crowding and increase the capacity utilization of the trains through investments in infrastructure or operational interventions.Transport and Plannin