  Stochastic particle--based models are useful tools for describing the
collective movement of large crowds of pedestrians in crowded confined
environments. Using descriptions based on the simple exclusion process, two
populations of particles, mimicking pedestrians walking in a built environment,
enter a room from two opposite sides. One population is passive -- being
unaware of the local environment; particles belonging to this group perform a
symmetric random walk. The other population has information on the local
geometry in the sense that as soon as particles enter a visibility zone, a
drift activates them. Their self-propulsion leads them towards the exit. This
second type of species is referred here as active. The assumed crowdedness
corresponds to a near--jammed scenario. The main question we ask in this paper
is: Can we induce modifications of the dynamics of the active particles to
improve the outgoing current of the passive particles? To address this
question, we compute occupation number profiles and currents for both
populations in selected parameter ranges. Besides observing the more classical
faster--is--slower effect, new features appear as prominent like the
non--monotonicity of currents, self--induced phase separation within the active
population, as well as acceleration of passive particles for large--drift
regimes of active particles.
