191 research outputs found
Parameter Estimation of Social Forces in Crowd Dynamics Models via a Probabilistic Method
Focusing on a specific crowd dynamics situation, including real life
experiments and measurements, our paper targets a twofold aim: (1) we present a
Bayesian probabilistic method to estimate the value and the uncertainty (in the
form of a probability density function) of parameters in crowd dynamic models
from the experimental data; and (2) we introduce a fitness measure for the
models to classify a couple of model structures (forces) according to their
fitness to the experimental data, preparing the stage for a more general
model-selection and validation strategy inspired by probabilistic data
analysis. Finally, we review the essential aspects of our experimental setup
and measurement technique.Comment: 20 pages, 9 figure
Continuous measurements of real-life bidirectional pedestrian flows on a wide walkway
Employing partially overlapping overhead \kinectTMS sensors and automatic
pedestrian tracking algorithms we recorded the crowd traffic in a rectilinear
section of the main walkway of Eindhoven train station on a 24/7 basis. Beside
giving access to the train platforms (it passes underneath the railways), the
walkway plays an important connection role in the city. Several crowding
scenarios occur during the day, including high- and low-density dynamics in
uni- and bi-directional regimes. In this paper we discuss our recording
technique and we illustrate preliminary data analyses. Via fundamental
diagrams-like representations we report pedestrian velocities and fluxes vs.
pedestrian density. Considering the density range - ped/m, we
find that at densities lower than ped/m pedestrians in
unidirectional flows walk faster than in bidirectional regimes. On the
opposite, velocities and fluxes for even bidirectional flows are higher above
ped/m.Comment: 9 pages, 7 figure
Modeling Routing Choices in Unidirectional Pedestrian Flows
In this work we present a simple routing model capable of capturing pedestrians path choices in the presence of a herding effect. The model is tested and validated against data from a large scale tracking campaign which we have conducted during the GLOW 2019 festival. The choice between alternative paths is modeled as an individual cost minimization procedure, with the cost function being associated to the (estimated) traveling time. In order to trigger herding effects the cost function is supplemented with a penalty term, modulated as a function of the fraction of pedestrians walking along each route. The model is shown to provide an accurate quantitative description of the decision process
Modeling Routing Choices in Unidirectional Pedestrian Flows
In this work we present a simple routing model capable of capturing pedestrians path choices in the presence of a herding effect. The model is tested and validated against data from a large scale tracking campaign which we have conducted during the GLOW 2019 festival. The choice between alternative paths is modeled as an individual cost minimization procedure, with the cost function being associated to the (estimated) traveling time. In order to trigger herding effects the cost function is supplemented with a penalty term, modulated as a function of the fraction of pedestrians walking along each route. The model is shown to provide an accurate quantitative description of the decision process
Path-integral representation of diluted pedestrian dynamics
We frame the issue of pedestrian dynamics modeling in terms of
path-integrals, a formalism originally introduced in quantum mechanics to
account for the behavior of quantum particles, later extended to quantum field
theories and to statistical physics. Path-integration enables a
trajectory-centric representation of the pedestrian motion, directly providing
the probability of observing a given trajectory. This appears as the most
natural language to describe the statistical properties of pedestrian dynamics
in generic settings. In a given venue, individual trajectories can belong to
many possible usage patterns and, within each of them, they can display wide
variability.
We provide first a primer on path-integration, and we introduce and discuss
the path-integral functional probability measure for pedestrian dynamics in the
diluted limit. As an illustrative example, we connect the path-integral
description to a Langevin model that we developed previously for a particular
crowd flow condition (the flow in a narrow corridor). Building on our previous
real-life measurements, we provide a quantitatively correct path-integral
representation for this condition. Finally, we show how the path-integral
formalism can be used to evaluate the probability of rare-events (in the case
of the corridor, U-turns)
Importance of d-p Coulomb interaction for high T cuprates and other oxides
Current theoretical studies of electronic correlations in transition metal
oxides typically only account for the local repulsion between d-electrons even
if oxygen ligand p-states are an explicit part of the effective Hamiltonian.
Interatomic interactions such as Upd between d- and (ligand) p-electrons, as
well as the local interaction between p-electrons, are neglected. Often, the
relative d-p orbital splitting has to be adjusted "ad hoc" on the basis of the
experimental evidence. By applying the merger of local density approximation
and dynamical mean field theory (LDA+DMFT) to the prototypical case of the
3-band Emery dp model for the cuprates, we demonstrate that, without any "ad
hoc" adjustment of the orbital splitting, the charge transfer insulating state
is stabilized by the interatomic interaction Upd. Our study hence shows how to
improve realistic material calculations that explicitly include the p-orbitals.Comment: 17 pages, 6 figures, our study shows that U_pd is the physics behind
previous ad-hoc shifts of the d-p level splittin
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