18,505 research outputs found
Dynamics of pedestrians in regions with no visibility - a lattice model without exclusion
We investigate the motion of pedestrians through obscure corridors where the
lack of visibility (due to smoke, fog, darkness, etc.) hides the precise
position of the exits. We focus our attention on a set of basic mechanisms,
which we assume to be governing the dynamics at the individual level. Using a
lattice model, we explore the effects of non-exclusion on the overall exit flux
(evacuation rate). More precisely, we study the effect of the buddying
threshold (of no-exclusion per site) on the dynamics of the crowd and
investigate to which extent our model confirms the following pattern revealed
by investigations on real emergencies: If the evacuees tend to cooperate and
act altruistically, then their collective action tends to favor the occurrence
of disasters.Comment: 20 page
How simple rules determine pedestrian behavior and crowd disasters
With the increasing size and frequency of mass events, the study of crowd
disasters and the simulation of pedestrian flows have become important research
areas. Yet, even successful modeling approaches such as those inspired by
Newtonian force models are still not fully consistent with empirical
observations and are sometimes hard to calibrate. Here, a novel cognitive
science approach is proposed, which is based on behavioral heuristics. We
suggest that, guided by visual information, namely the distance of obstructions
in candidate lines of sight, pedestrians apply two simple cognitive procedures
to adapt their walking speeds and directions. While simpler than previous
approaches, this model predicts individual trajectories and collective patterns
of motion in good quantitative agreement with a large variety of empirical and
experimental data. This includes the emergence of self-organization phenomena,
such as the spontaneous formation of unidirectional lanes or stop-and-go waves.
Moreover, the combination of pedestrian heuristics with body collisions
generates crowd turbulence at extreme densities-a phenomenon that has been
observed during recent crowd disasters. By proposing an integrated treatment of
simultaneous interactions between multiple individuals, our approach overcomes
limitations of current physics-inspired pair interaction models. Understanding
crowd dynamics through cognitive heuristics is therefore not only crucial for a
better preparation of safe mass events. It also clears the way for a more
realistic modeling of collective social behaviors, in particular of human
crowds and biological swarms. Furthermore, our behavioral heuristics may serve
to improve the navigation of autonomous robots.Comment: Article accepted for publication in PNA
Pedestrians moving in dark: Balancing measures and playing games on lattices
We present two conceptually new modeling approaches aimed at describing the
motion of pedestrians in obscured corridors:
* a Becker-D\"{o}ring-type dynamics
* a probabilistic cellular automaton model.
In both models the group formation is affected by a threshold. The
pedestrians are supposed to have very limited knowledge about their current
position and their neighborhood; they can form groups up to a certain size and
they can leave them. Their main goal is to find the exit of the corridor.
Although being of mathematically different character, the discussion of both
models shows that it seems to be a disadvantage for the individual to adhere to
larger groups. We illustrate this effect numerically by solving both model
systems. Finally we list some of our main open questions and conjectures
Toward a Mathematical Theory of Behavioral-Social Dynamics for Pedestrian Crowds
This paper presents a new approach to behavioral-social dynamics of
pedestrian crowds by suitable development of methods of the kinetic theory. It
is shown how heterogeneous individual behaviors can modify the collective
dynamics, as well as how local unusual behaviors can propagate in the crowd.
The main feature of this approach is a detailed analysis of the interactions
between dynamics and social behaviors.Comment: 22 pages, 5 figure
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