  Collectively coordinated cell migration plays a role in tissue embryogenesis,
cancer, homeostasis and healing. To study these processes, different cell-based
modelling approaches have been developed, ranging from lattice-based cellular
automata to lattice-free models that treat cells as point-like particles or
extended detailed cell shape contours. In the spirit of what Osborne et al.
[PLOS Computational Biology, (2017) 13, 1-34] did for cellular tissue structure
simulation models, we here compare five simulation models of collective cell
migration, chosen to be representative in increasing order of included detail.
They are Vicsek-Gr\'egoire particles, Szab\'o-like particles, self-propelled
Voronoi model, cellular Potts model, and multiparticle cells, where each model
includes cell motility. We examine how these models compare when applied to the
same biological problem, and what differences in behaviour are due to different
model assumptions and abstractions. For that purpose, we use a benchmark that
discriminates between complex material flow models, and that can be
experimentally approached using cell cultures: the flow within a channel around
a circular obstacle, that is, the geometry Stokes used in his historical 1851
experiment. For each model we explain how to best implement it; vary cell
density, attraction force and alignment interaction; draw the resulting maps of
velocity, density and deformation fields; and eventually discuss its respective
advantages and limitations. We thus provide a recommendation on how to select a
model to answer a given question, and we examine whether models of motile
particles and motile cells display similar collective effects.
