Stochastic transition model for pedestrian dynamics

Abstract

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.

preprint for Pedestrian and Evacuation Conference (PED2012) contribution

References in corpus (2)

• The walking behaviour of pedestrian social groups and its impact on crowd dynamics
• Solving the Direction Field for Discrete Agent Motion

Cited by in corpus (1)

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