Social Force Model for Pedestrian Dynamics
Dirk Helbing,Péter Molnár +1 more
TLDR
Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.Abstract:
It is suggested that the motion of pedestrians can be described as if they would be subject to ``social forces.'' These ``forces'' are not directly exerted by the pedestrians' personal environment, but they are a measure for the internal motivations of the individuals to perform certain actions (movements). The corresponding force concept is discussed in more detail and can also be applied to the description of other behaviors. In the presented model of pedestrian behavior several force terms are essential: first, a term describing the acceleration towards the desired velocity of motion; second, terms reflecting that a pedestrian keeps a certain distance from other pedestrians and borders; and third, a term modeling attractive effects. The resulting equations of motion of nonlinearly coupled Langevin equations. Computer simulations of crowds of interacting pedestrians show that the social force model is capable of describing the self-organization of several observed collective effects of pedestrian behavior very realistically.read more
Citations
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Robust abandoned object detection integrating wide area visual surveillance and social context
James Ferryman,David C. Hogg,Jan Sochman,Ardhendu Behera,Jose A. Rodriguez-Serrano,Simon F. Worgan,Longzhen Li,Valerie Leung,M. P. Evans,Philippe Cornic,Stéphane Herbin,Stefan Schlenger,Michael Dose +12 more
TL;DR: A video surveillance framework that robustly and efficiently detects abandoned objects in surveillance scenes is presented, based on a novel threat assessment algorithm which combines the concept of ownership with automatic understanding of social relations in order to infer abandonment of objects.
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Enhancing a tsunami evacuation simulation for a multi-scenario analysis using parallel computing
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References
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