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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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Book ChapterDOI

Pedestrian Simulation Using Geometric Reasoning in Velocity Space

TL;DR: A novel pedestrian representation based on a new model of pedestrian motion coupled with a geometric optimization method that exhibits the same types of self-organizing behaviors shown by previous models is presented.
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Statistical characteristics of evacuation without visibility in random walk model

TL;DR: In this paper, the authors investigated the evacuation process from a dark room with an exit by the use of the biased random walk model and clarified the statistical properties of the walker escaping from the room through the exit.
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A cellular automata evacuation model considering friction and repulsion

TL;DR: In this article, a new cellular automata model based on traditional models is introduced in which repulsion and friction are modeled quantitatively, and it is indicated that the model can simulate some basic behaviors, e.g., arching and the "faster-is-slower" phenomenon, in evacuation as multi-particle self-driven models, but with high efficiency as the normal cellular automaton model and the lattice gas model.
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Biologically-informed neural networks guide mechanistic modeling from sparse experimental data

TL;DR: In this article, BINNs are trained in a supervised learning framework to approximate in vitro cell biology assay experiments while respecting a generalized form of the governing reaction-diffusion partial differential equation (PDE).
Proceedings ArticleDOI

Predicting Behaviors of Basketball Players from First Person Videos

TL;DR: This paper presents a method to predict the future movements (location and gaze direction) of basketball players as a whole from their first person videos using the 3D reconstruction of multiple first person cameras to automatically annotate each others visual semantics of social configurations.
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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