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Social Force Model for Pedestrian Dynamics

Dirk Helbing, +1 more
- 01 May 1995 - 
- Vol. 51, Iss: 5, pp 4282-4286
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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.

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From Goals, Waypoints & Paths To Long Term Human Trajectory Forecasting

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Modeling crowd dynamics by the mean-field limit approach

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Recognition of crowd behavior from mobile sensors with pattern analysis and graph clustering methods

TL;DR: In this article, the authors presented a methodological framework for the recognition of crowd behavior from on-body sensors, such as those in mobile phones, for the analysis and understanding of crowd dynamics.
References
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Book

Field theory in social science

Kurt Lewin
Book

Kinetic theory of vehicular traffic

TL;DR: A theory of multi-LANE traffic flow and the space-time evolution of thevelocity distribution of cars are examined to help understand the role of driver behaviour and strategy in this network.
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Improved fluid-dynamic model for vehicular traffic.

TL;DR: The fluid-dynamic traffic model of Kerner and Konh\"auser is extended by an equation for the vehicles' velocity variance, able to describe the observed increase of velocity variance immediately before a traffic jam develops.
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