Results 1 - 10
of
504
Simulating dynamical features of escape panic
- Nature
"... One of the most disastrous forms of collective human behaviour is the kind of crowd stampede induced by panic, often leading to fatalities as people are crushed or trampled. Sometimes this behaviour is triggered in life-threatening situations such as fires in crowded buildings; 1,2 at other times, s ..."
Abstract
-
Cited by 254 (4 self)
- Add to MetaCart
One of the most disastrous forms of collective human behaviour is the kind of crowd stampede induced by panic, often leading to fatalities as people are crushed or trampled. Sometimes this behaviour is triggered in life-threatening situations such as fires in crowded buildings; 1,2 at other times, stampedes can arise from the rush for seats3,4 or seemingly without causes. Tragic examples within recent months include the panics in Harare, Zimbabwe, and at the Roskilde rock concert in Denmark. Although engineers are finding ways to alleviate the scale of such disasters, their frequency seems to be increasing with the number and size of mass events. 2,5 Yet, systematic studies of panic behaviour, 6−9 and quantitative theories capable of predicting such crowd dynamics, 5,10−12 are rare. Here we show that simulations based on a model of pedestrian behaviour can provide valuable insights into the mechanisms of and preconditions for panic and jamming by incoordination. Our results suggest practical ways of minimising the harmful consequences of such events 1 Helbing/Farkas/Vicsek: Simulating Dynamical Features of Escape Panic 2 and the existence of an optimal escape strategy, corresponding to a suitable mixture of individualistic and collective behaviour. Up to now, panics as a particular form of collective behaviour occuring in situations of scarce or dwindling resources1,6 has been mainly studied from the perspective of social psychology. 7−9 Panicking individuals tend to show maladaptive and relentless mass behaviour like jamming and life-threatening overcrowding, 1−4,8 which has often been attributed to social contagion1,4,8 (see Brown9 for an overview of theories). According to Mintz, 6 the observed jamming is a result of incoordination and depends on the reward structure. After having carefully studied the related socio-psychological literature, 6−9 reports in the media and available video materials (see
Abnormal Crowd Behavior Detection using Social Force Model
"... In this paper we introduce a novel method to detect and localize abnormal behaviors in crowd videos using Social Force model. For this purpose, a grid of particles is placed over the image and it is advected with the space-time average of optical flow. By treating the moving particles as individuals ..."
Abstract
-
Cited by 122 (3 self)
- Add to MetaCart
(Show Context)
In this paper we introduce a novel method to detect and localize abnormal behaviors in crowd videos using Social Force model. For this purpose, a grid of particles is placed over the image and it is advected with the space-time average of optical flow. By treating the moving particles as individuals, their interaction forces are estimated using social force model. The interaction force is then mapped into the image plane to obtain Force Flow for every pixel in every frame. Randomly selected spatio-temporal volumes of Force Flow are used to model the normal behavior of the crowd. We classify frames as normal and abnormal by using a bag of words approach. The regions of anomalies in the abnormal frames are localized using interaction forces. The experiments are conducted on a publicly available dataset from University of Minnesota for escape panic scenarios and a challenging dataset of crowd videos taken from the web. The experiments show that the proposed method captures the dynamics of the crowd behavior successfully. In addition, we have shown that the social force approach outperforms similar approaches based on pure optical flow.
You’ll never walk alone: modeling social behavior for multi-target tracking
- IN INT. CONF. ON COMPUTER VISION (ICCV
, 2009
"... Object tracking typically relies on a dynamic model to predict the object’s location from its past trajectory. In crowded scenarios a strong dynamic model is particularly important, because more accurate predictions allow for smaller search regions, which greatly simplifies data asso-ciation. Tradit ..."
Abstract
-
Cited by 120 (3 self)
- Add to MetaCart
Object tracking typically relies on a dynamic model to predict the object’s location from its past trajectory. In crowded scenarios a strong dynamic model is particularly important, because more accurate predictions allow for smaller search regions, which greatly simplifies data asso-ciation. Traditional dynamic models predict the location for each target solely based on its own history, without tak-ing into account the remaining scene objects. Collisions are resolved only when they happen. Such an approach ignores important aspects of human behavior: people are driven by their future destination, take into account their environment, anticipate collisions, and adjust their trajec-tories at an early stage in order to avoid them. In this work, we introduce a model of dynamic social behavior, inspired by models developed for crowd simulation. The model is trained with videos recorded from birds-eye view at busy locations, and applied as a motion model for multi-people tracking from a vehicle-mounted camera. Experiments on real sequences show that accounting for social interactions and scene knowledge improves tracking performance, espe-cially during occlusions.
Scalable Behaviors for Crowd Simulation
- EUROGRAPHICS
, 2004
"... Crowd simulation for virtual environments offers many challenges centered on the trade-offs between rich behavior, control and computational cost. In this paper we present a new approach to controlling the behavior of agents in a crowd. Our method is scalable in the sense that increasingly complex ..."
Abstract
-
Cited by 73 (2 self)
- Add to MetaCart
Crowd simulation for virtual environments offers many challenges centered on the trade-offs between rich behavior, control and computational cost. In this paper we present a new approach to controlling the behavior of agents in a crowd. Our method is scalable in the sense that increasingly complex crowd behaviors can be created without a corresponding increase in the complexity of the agents. Our approach is also more authorable; users can dynamically specify which crowd behaviors happen in various parts of an environment. Finally, the character motion produced by our system is visually convincing. We achieve our aims with a situation-based control structure. Basic agents have
Anomaly detection in crowded scenes,”
- in IEEE Conference on Computer Vision and Pattern Recognition,
, 2010
"... ..."
(Show Context)
Time-evolving measures and macroscopic modeling of pedestrian flow
, 2008
"... This paper deals with the early results of a new model of pedestrian flow, conceived within a measure-theoretical framework. The modeling approach consists in a discrete-time Eulerian macroscopic representation of the system via a family of measures which, pushed forward by some motion mappings, pr ..."
Abstract
-
Cited by 49 (11 self)
- Add to MetaCart
(Show Context)
This paper deals with the early results of a new model of pedestrian flow, conceived within a measure-theoretical framework. The modeling approach consists in a discrete-time Eulerian macroscopic representation of the system via a family of measures which, pushed forward by some motion mappings, provide an estimate of the space occupancy by pedestrians at successive time steps. From the modeling point of view, this setting is particularly suitable to treat nonlocal interactions among pedestrians, obstacles, and wall boundary conditions. In addition, analysis and numerical approximation of the resulting mathematical structures, which is the main target of this work, follow more easily and straightforwardly than in case of standard hyperbolic conservation laws, also used in the specialized literature by some Authors to address analogous problems.
Finding Paths for Coherent Groups using Clearance
- EUROGRAPHICS/ACM SIGGRAPH SYMPOSIUM ON COMPUTER ANIMATION (2004)
, 2004
"... Virtual environment are often populated with moving units and the paths for these units should be planned. When multiple units need to exhibit coherent behavior in a cluttered environment, current techniques often fail, i.e. the resulting paths for the units in the group lack the coherence require ..."
Abstract
-
Cited by 48 (7 self)
- Add to MetaCart
Virtual environment are often populated with moving units and the paths for these units should be planned. When multiple units need to exhibit coherent behavior in a cluttered environment, current techniques often fail, i.e. the resulting paths for the units in the group lack the coherence required. In this paper, we propose a novel approach to motion planning for coherent groups of units. The method
Aggregate Dynamics for Dense Crowd Simulation
"... Figure 1: Some examples of large, dense crowds simulated with our technique. (a) 100,000 pilgrims moving through a campsite. (b) 80,000 people on a trade show floor. (c) 25,000 pilgrims with heterogeneous goals in a mosque. Large dense crowds show aggregate behavior with reduced individual freedom o ..."
Abstract
-
Cited by 47 (7 self)
- Add to MetaCart
Figure 1: Some examples of large, dense crowds simulated with our technique. (a) 100,000 pilgrims moving through a campsite. (b) 80,000 people on a trade show floor. (c) 25,000 pilgrims with heterogeneous goals in a mosque. Large dense crowds show aggregate behavior with reduced individual freedom of movement. We present a novel, scalable approach for simulating such crowds, using a dual representation both as discrete agents and as a single continuous system. In the continuous setting, we introduce a novel variational constraint called unilateral incompressibility, to model the large-scale behavior of the crowd, and accelerate inter-agent collision avoidance in dense scenarios. This approach makes it possible to simulate very large, dense crowds composed of up to a hundred thousand agents at nearinteractive rates on desktop computers.
Modeling the Evolution of Human Trail Systems
- Nature
, 1997
"... Many human social phenomena, suchh as cooperation [1–3], the growth of settlements [4], traffic dynamics [5–7] and pedestrian movement [7–10], appear to be accessible to mathematical descriptions that invoke self-organization [11,12]. Here we develop a model of pedestrian motion to explore the evolu ..."
Abstract
-
Cited by 43 (4 self)
- Add to MetaCart
(Show Context)
Many human social phenomena, suchh as cooperation [1–3], the growth of settlements [4], traffic dynamics [5–7] and pedestrian movement [7–10], appear to be accessible to mathematical descriptions that invoke self-organization [11,12]. Here we develop a model of pedestrian motion to explore the evolution of trails in urban green spaces such as parks. Our aim is to address such questions as what the topological structures of these trail systems are [13], and whether optimal path systems can be predicted for urban planning. We use an ‘active walker ’ model [14–19] that takes into account pedestrian motion and orientation and the concomitant feedbacks with the surrounding environment. Such models have previously been applied to the study of complex structure formation in physical [14–16], chemical [17] and biological [18,19] systems. We find that our model is able to reporduce many of the observed large-scale spatial features of trail systems. 1 Helbing/Keltsch/Molnár: Modelling the Evolution of Human Trail Systems 2 Previous studies have shown that various observed self-organization phenomena in pedestrian crowds can be simulated very realistically. This includes the emergence of lanes of uniform walking direction and oscillatory changes of the passing direction at bottlenecks
