3,505 research outputs found
Invisible control of self-organizing agents leaving unknown environments
In this paper we are concerned with multiscale modeling, control, and
simulation of self-organizing agents leaving an unknown area under limited
visibility, with special emphasis on crowds. We first introduce a new
microscopic model characterized by an exploration phase and an evacuation
phase. The main ingredients of the model are an alignment term, accounting for
the herding effect typical of uncertain behavior, and a random walk, accounting
for the need to explore the environment under limited visibility. We consider
both metrical and topological interactions. Moreover, a few special agents, the
leaders, not recognized as such by the crowd, are "hidden" in the crowd with a
special controlled dynamics. Next, relying on a Boltzmann approach, we derive a
mesoscopic model for a continuum density of followers, coupled with a
microscopic description for the leaders' dynamics. Finally, optimal control of
the crowd is studied. It is assumed that leaders exploit the herding effect in
order to steer the crowd towards the exits and reduce clogging. Locally-optimal
behavior of leaders is computed. Numerical simulations show the efficiency of
the optimization methods in both microscopic and mesoscopic settings. We also
perform a real experiment with people to study the feasibility of the proposed
bottom-up crowd control technique.Comment: in SIAM J. Appl. Math, 201
Rationality: a social-epistemology perspective
Both in philosophy and in psychology, human rationality has traditionally been studied from an "individualistic" perspective. Recently, social epistemologists have drawn attention to the fact that epistemic interactions among agents also give rise to important questions concerning rationality. In previous work, we have used a formal model to assess the risk that a particular type of social-epistemic interactions lead agents with initially consistent belief states into inconsistent belief states. Here, we continue this work by investigating the dynamics to which these interactions may give rise in the population as a whole
Ped-Air: A Simulator for Loading, Unloading, and Evacuating Aircraft
AbstractWe present Ped-Air, a pedestrian simulation system to model the loading, unloading, and evacuation of commercial aircraft. We address the challenge of simulating passenger movement in constrained spaces (e.g., aisles and rows), along with complex, coordinating behaviors between the passengers. Ped-Air models different categories of passengers and flight crew, capturing their unique behaviors and complex interactions. We exhibit Ped-Airs capabilities by simulating passenger movements on two representative aircraft: a single-aisle Boeing 737, and a double-aisle Boeing 777. We are able to simulate the following behaviors: stress, luggage placement, flight staff assisting passengers, obstructed exits for evacuation
Disentangling intrinsic motion from neighbourhood effects in heterogeneous collective motion
Most real world collectives, including active particles, living cells, and
grains, are heterogeneous, where individuals with differing properties
interact. The differences among individuals in their intrinsic properties have
emergent effects at the group level. It is often of interest to infer how the
intrinsic properties differ among the individuals, based on their observed
movement patterns. However, the true individual properties may be masked by
emergent effects in the collective. We investigate the inference problem in the
context of a bidisperse collective with two types of agents, where the goal is
to observe the motion of the collective and classify the agents according to
their types. Since collective effects such as jamming and clustering affect
individual motion, an agent's own movement does not have sufficient information
to perform the classification well: a simple observer algorithm, based only on
individual velocities cannot accurately estimate the level of heterogeneity of
the system, and often misclassifies agents. We propose a novel approach to the
classification problem, where collective effects on an agent's motion is
explicitly accounted for. We use insights about the physics of collective
motion to quantify the effect of the neighbourhood on an agent using a
neighbourhood parameter. Such an approach can distinguish between agents of two
types, even when their observed motion is identical. This approach estimates
the level of heterogeneity much more accurately, and achieves significant
improvements in classification. Our results demonstrate that explicitly
accounting for neighbourhood effects is often necessary to correctly infer
intrinsic properties of individuals.Comment: Supplementary movies can be found in:
https://www.dannyraj.com/obsinf-supp-inf
Adaptive network models of collective decision making in swarming systems
We consider a class of adaptive network models where links can only be
created or deleted between nodes in different states. These models provide an
approximate description of a set of systems where nodes represent agents moving
in physical or abstract space, the state of each node represents the agent's
heading direction, and links indicate mutual awareness. We show analytically
that the adaptive network description captures the phase transition to
collective motion in swarming systems and that the properties of this
transition are determined by the number of states (discrete heading directions)
that can be accessed by each agent.Comment: 8 pages, 5 figure
Optimal Self-Organization
We present computational and analytical results indicating that systems of
driven entities with repulsive interactions tend to reach an optimal state
associated with minimal interaction and minimal dissipation. Using concepts
from non-equilibrium thermodynamics and game theoretical ideas, we generalize
this finding to an even wider class of self-organizing systems which have the
ability to reach a state of maximal overall ``success''. This principle is
expected to be relevant for driven systems in physics like sheared granular
media, but it is also applicable to biological, social, and economic systems,
for which only a limited number of quantitative principles are available yet.Comment: This is the detailled revised version of a preprint on
``Self-Organised Optimality'' (cond-mat/9903319). For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.html and
http://angel.elte.hu/~vicsek
Two dimensional outflows for cellular automata with shuffle updates
In this paper, we explore the two-dimensional behavior of cellular automata
with shuffle updates. As a test case, we consider the evacuation of a square
room by pedestrians modeled by a cellular automaton model with a static floor
field. Shuffle updates are characterized by a variable associated to each
particle and called phase, that can be interpreted as the phase in the step
cycle in the frame of pedestrian flows. Here we also introduce a dynamics for
these phases, in order to modify the properties of the model. We investigate in
particular the crossover between low- and high-density regimes that occurs when
the density of pedestrians increases, the dependency of the outflow in the
strength of the floor field, and the shape of the queue in front of the exit.
Eventually we discuss the relevance of these results for pedestrians.Comment: 20 pages, 5 figures. v2: 16 pages, 5 figures; changed the title,
abstract and structure of the paper. v3: minor change
Influence of the number of predecessors in interaction within acceleration-based flow models
In this paper, the stability of the uniform solutions is analysed for
microscopic flow models in interaction with predecessors. We calculate
general conditions for the linear stability on the ring geometry and explore
the results with particular pedestrian and car-following models based on
relaxation processes. The uniform solutions are stable if the relaxation times
are sufficiently small. The analysis is focused on the relevance of the number
of predecessors in the dynamics. Unexpected non-monotonic relations between
and the stability are presented.Comment: 18 pages, 14 figure
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