  Discrete pedestrian simulation models are viable alternatives to particle
based approaches based on a continuous spatial representation. The effects of
discretisation, however, also imply some difficulties in modelling certain
phenomena that can be observed in reality. This paper focuses on the
possibility to manage heterogeneity in the walking speed of the simulated
population of pedestrians by modifying an existing multi-agent model extending
the floor field approach. Whereas some discrete models allow pedestrians (or
cars, when applied to traffic modelling) to move more than a single cell per
time step, the present work proposes a maximum speed of one cell per step, but
we model lower speeds by having pedestrians yielding their movement in some
turns. Different classes of pedestrians are associated to different desired
walking speeds and we define a stochastic mechanism ensuring that they maintain
an average speed close to this threshold. In the paper we formally describe the
model and we show the results of its application in benchmark scenarios.
Finally, we also show how this approach can also support the definition of
slopes and stairs as elements reducing the walking speed of pedestrians
climbing them in a simulated scenario.
