Social Force Model for Pedestrian Dynamics
Dirk Helbing,Péter Molnár +1 more
Reads0
Chats0
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
More filters
Journal ArticleDOI
Goal-based trajectory analysis for unusual behaviour detection in intelligent surveillance
TL;DR: The proposed method extends the original goal-based approach in three ways: first, the spatial scene structure is learned in a training phase; second, a region transition model is learned to describe normal movement patterns between spatial regions; and third, classification of trajectories in progress is performed in a probabilistic framework using particle filtering.
Posted Content
Multiple Object Tracking: A Review.
TL;DR: A comprehensive and systematic review of the recent advances in various aspects about multiple object tracking and provides some potential directions with insights for MOT, which are still open issues and need more research efforts.
Journal ArticleDOI
A Bayesian Model for Crowd Escape Behavior Detection
Si Wu,Hau-San Wong,Zhiwen Yu +2 more
TL;DR: A Bayesian framework for escape detection is proposed by directly modeling crowd motion in both the presence and absence of escape events by introducing the concepts of potential destinations and divergent centers to characterize crowd motion respectively, and constructing the corresponding class-conditional probability density functions of optical flow.
Journal ArticleDOI
Kinects and human kinetics: a new approach for studying pedestrian behavior
TL;DR: This work presents a data collection approach for studying pedestrian behavior which uses the increasingly popular low-cost sensor Microsoft Kinect and calibrates three variations of the Social Force model, indicating their particular ability to reproduce the observed pedestrian behavior in microscopic simulations.
Journal ArticleDOI
A hierarchy of heuristic-based models of crowd dynamics
Pierre Degond,Cécile Appert-Rolland,Cécile Appert-Rolland,Mehdi Moussaïd,Julien Pettré,Guy Theraulaz,Guy Theraulaz +6 more
TL;DR: In this article, a hierarchy of kinetic and macroscopic models from a noisy variant of the heuristic behavioral individual-based model of Moussaid et al, PNAS 2011, where the pedestrians are supposed to have constant speeds was derived.
References
More filters
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.