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Open AccessJournal ArticleDOI

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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Proceedings ArticleDOI

Development of pedestrian behavior model taking account of intention

TL;DR: A pedestrian behavior model that produces humanlike behavior was developed that takes into account the pedestrian's intention and moves toward the subgoal according to virtual forces affected by other pedestrian and environment.
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Book ChapterDOI

Abnormal crowd behavior detection by social force optimization

TL;DR: Results show the consistent higher performances of the proposed method as compared to other state-of-the-art algorithms, proving the goodness ofThe proposed approach.
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Reciprocal Learning Networks for Human Trajectory Prediction

TL;DR: A new method for network prediction, called reciprocal attack for matched prediction, is developed, which improves the prediction accuracy and outperforms the state-of-the-art methods for human trajectory prediction.
Journal ArticleDOI

On the modelling of crowd dynamics by generalized kinetic models

TL;DR: In this article, a new approach for modeling the behavior of pedestrians is introduced, which borrows techniques from the kinetic theory of rarefied gazes, and is based on concepts from the KG for active particles.
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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