Social Force Model for Pedestrian Dynamics
Dirk Helbing,Péter Molnár +1 more
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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Modeling pedestrian flow accounting for collision avoidance during evacuation
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Dynamic calibration of agent-based models using data assimilation
TL;DR: This paper describes how ABMs can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation, and builds a hierarchy of exemplar models that are used to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.
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Pedestrian Behavior Modeling From Stationary Crowds With Applications to Intelligent Surveillance
TL;DR: A novel model is proposed to model pedestrian behaviors by incorporating stationary crowd groups as a key component and is demonstrated through multiple applications, including walking path prediction, destination prediction, personality attribute classification, and abnormal event detection.
Proceedings ArticleDOI
Social-aware robot navigation in urban environments
TL;DR: A robot navigation algorithm, called social-aware navigation, which is mainly driven by the social-forces centered at the robot, is proposed, which uses a MCMC Metropolis-Hastings algorithm in order to learn the parameters values of the method.
Proceedings ArticleDOI
How do people walk side-by-side?: using a computational model of human behavior for a social robot
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