  The proposed stochastic model for pedestrian dynamics is based on existing
approaches using cellular automata, combined with substantial extensions, to
compensate the deficiencies resulting of the discrete grid structure. This
agent motion model is extended by both a grid-based path planning and mid-range
agent interaction component. The stochastic model proves its capabilities for a
quantitative reproduction of the characteristic shape of the common fundamental
diagram of pedestrian dynamics. Moreover, effects of self-organizing behavior
are successfully reproduced. The stochastic cellular automata approach is found
to be adequate with respect to uncertainties in human motion patterns, a
feature previously held by artificial noise terms alone.
