Determinants of passengers' metro car choice revealed through automated data sources
A Stockholm metro case study
Soumela Peftitsi (KTH Royal Institute of Technology)
Erik Jenelius (KTH Royal Institute of Technology)
O. Cats (TU Delft - Transport and Planning)
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Abstract
The paper proposes a methodology based on multiple automated
data sources for evaluating the eects of station layout, arriving traveller flows,
and platform and on-board crowding on the distribution of boarding passengers
in individual cars of a metro train. The methodology is applied to a case
study for a sequence of stations in the Stockholm metro network. While train
car loads are generally skewed towards the leading cars, results indicate that
a crowded arriving train is associated with increasing boarding shares in the
middle and rear cars. Moreover, higher platform crowding is found to have a
positive signicant eect on the boarding share in the middle car. We nd that
the boarding car distribution is also aected by the locations of entrances and
the distribution of entering traveller ows. The insights may be used by transit
planners and operators to increase the understanding of how passengers behave
under crowding conditions and identify the factors that aect travelers'
metro car choice.