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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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Citations
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Perceived cost potential field cellular automata model with an aggregated force field for pedestrian dynamics

TL;DR: In this article, the authors proposed a perceived potential field and an aggregated force field for navigation of pedestrians in a walking domain with poor visibility or complex geometries, and compared with a formulation that does not include the latter field, the proposed model displays an advantage in simulating overcrowded pedestrian flows, e.g., at the front of a bottleneck or at a left/right turn in a corridor.
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A review on technological advancements in crowd management

TL;DR: The crowd modeling aspects during the planning of crowded scenario, and the technological advancements in crowd data acquisition techniques [based on Vision, Wireless/Radio-Frequency and Web/Social-media data mining technologies] during execution of crowded event are discussed.
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A framework for model integration and holistic modelling of socio-technical systems

TL;DR: The framework enables the modeller to identify non-trivial interface points such as between the spatial interactions of an ABM and the causal reasoning of a HQBN, and between the process activity representation of a BPMN and simulated behavioural performance in aHQBN.
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A particle model of crowd behavior: Exploring the relationship between alcohol, crowd dynamics and violence

TL;DR: In this paper, it is argued that intoxication disrupts social interactions between individuals, and that the emergence of affiliative behavior is a product of individual level interactions and that intoxication increases individuals levels of stress and therefore aggression.
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Tracking in dense crowds using prominence and neighborhood motion concurrence

TL;DR: A novel tracking method tailored to dense crowds is proposed which provides an alternative and complementary approach to methods that require modeling of crowd flow and is less likely to fail in the case of dynamic crowd flows and anomalies by minimally relying on previous frames.
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.
Journal ArticleDOI

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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