Social Force Model for Pedestrian Dynamics
Dirk Helbing,Péter Molnár +1 more
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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.read more
Citations
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Proceedings ArticleDOI
Recursive Social Behavior Graph for Trajectory Prediction
TL;DR: Wang et al. as mentioned in this paper used graph convolutional neural network (CNN) to propagate social interaction information in a social behavior graph and achieved state-of-the-art performance on the ETH and UCY datasets.
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Effect of authority figures for pedestrian evacuation at metro stations
TL;DR: Social force based modeling and simulation results show that factors that may influence the evacuation effect of crowd, such as the number and locations of AFs, their spread of direction, calming effect and distribution strategies etc, play important roles in evacuation efficiency.
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CROSS: Modelling Crowd Behaviour with Social-Cognitive Agents
TL;DR: This paper presents CROSS, a generic framework to model crowd simulations as a social scientific tool for understanding crowd behaviour, and specifies the CROSS framework for a festival context to demonstrate how CROSS meets the need for a theory that reflects the dynamic interplay between individuals and their environment.
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Efficient and Trustworthy Social Navigation via Explicit and Implicit Robot–Human Communication
TL;DR: A planning framework that uses a combination of implicit (robot motion) and explicit (visual/audio/haptic feedback) communication during mobile robot navigation during social navigation and results show that the planner generated plans that are easier to understand, reduce users‘ effort, and increase users’ trust of the robot.
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Cellular automaton simulation of pedestrian flow considering vision and multi-velocity
TL;DR: A cellular automaton model with an asynchronous update has been used to identify the pedestrians walking at the different speeds and the relationships between velocity–density and pedestrian types are analyzed.
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