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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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Proceedings ArticleDOI

Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker

TL;DR: This paper presents an approach which includes the interaction between pedestrians in two ways: first, considering social and grouping behavior, and second, using a global optimization scheme to solve the data association problem.
Proceedings ArticleDOI

Feature-Based Prediction of Trajectories for Socially Compliant Navigation

TL;DR: This paper presents a novel approach to predict the movements of pedestrians that applies a maximum entropy learning method based on features that capture relevant aspects of the trajectories to determine the probability distribution that underlies human navigation behavior.
Book

Crowd Simulation

TL;DR: The second edition of Crowd Simulation includes in-depth discussions on the techniques of path planning, including a new hybrid approach between navigation graphs and potential-based methods and a free-of-collision method for crowds.
Journal ArticleDOI

A dynamic cellular automaton model for evacuation process with obstacles

TL;DR: A dynamic cellular automaton (CA) model is proposed to simulate the evacuation process in the rooms with obstacles, and effects of pedestrians distribution, doors position and doors width on the evacuation time are discussed.
Journal ArticleDOI

A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions

TL;DR: The Social Force Model presents some limitations when describing the experimental data of pedestrian flows in normal conditions — in particular the specific flow rates for different door widths and the fundamental diagram.
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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