1,559 research outputs found
Multiscale modeling of granular flows with application to crowd dynamics
In this paper a new multiscale modeling technique is proposed. It relies on a
recently introduced measure-theoretic approach, which allows to manage the
microscopic and the macroscopic scale under a unique framework. In the
resulting coupled model the two scales coexist and share information. This
allows to perform numerical simulations in which the trajectories and the
density of the particles affect each other. Crowd dynamics is the motivating
application throughout the paper.Comment: 30 pages, 9 figure
Multiscale modeling of granular flows with application to crowd dynamics
In this paper a new multiscale modeling technique is proposed. It relies on a
recently introduced measure-theoretic approach, which allows to manage the
microscopic and the macroscopic scale under a unique framework. In the
resulting coupled model the two scales coexist and share information. This
allows to perform numerical simulations in which the trajectories and the
density of the particles affect each other. Crowd dynamics is the motivating
application throughout the paper.Comment: 30 pages, 9 figure
From individual behaviour to an evaluation of the collective evolution of crowds along footbridges
This paper proposes a crowd dynamic macroscopic model grounded on microscopic
phenomenological observations which are upscaled by means of a formal
mathematical procedure. The actual applicability of the model to real world
problems is tested by considering the pedestrian traffic along footbridges, of
interest for Structural and Transportation Engineering. The genuinely
macroscopic quantitative description of the crowd flow directly matches the
engineering need of bulk results. However, three issues beyond the sole
modelling are of primary importance: the pedestrian inflow conditions, the
numerical approximation of the equations for non trivial footbridge geometries,
and the calibration of the free parameters of the model on the basis of in situ
measurements currently available. These issues are discussed and a solution
strategy is proposed.Comment: 23 pages, 10 figures in J. Engrg. Math., 201
Macroscopic modeling and simulations of room evacuation
We analyze numerically two macroscopic models of crowd dynamics: the
classical Hughes model and the second order model being an extension to
pedestrian motion of the Payne-Whitham vehicular traffic model. The desired
direction of motion is determined by solving an eikonal equation with density
dependent running cost, which results in minimization of the travel time and
avoidance of congested areas. We apply a mixed finite volume-finite element
method to solve the problems and present error analysis for the eikonal solver,
gradient computation and the second order model yielding a first order
convergence. We show that Hughes' model is incapable of reproducing complex
crowd dynamics such as stop-and-go waves and clogging at bottlenecks. Finally,
using the second order model, we study numerically the evacuation of
pedestrians from a room through a narrow exit.Comment: 22 page
Pedestrian flows in bounded domains with obstacles
In this paper we systematically apply the mathematical structures by
time-evolving measures developed in a previous work to the macroscopic modeling
of pedestrian flows. We propose a discrete-time Eulerian model, in which the
space occupancy by pedestrians is described via a sequence of Radon positive
measures generated by a push-forward recursive relation. We assume that two
fundamental aspects of pedestrian behavior rule the dynamics of the system: On
the one hand, the will to reach specific targets, which determines the main
direction of motion of the walkers; on the other hand, the tendency to avoid
crowding, which introduces interactions among the individuals. The resulting
model is able to reproduce several experimental evidences of pedestrian flows
pointed out in the specialized literature, being at the same time much easier
to handle, from both the analytical and the numerical point of view, than other
models relying on nonlinear hyperbolic conservation laws. This makes it
suitable to address two-dimensional applications of practical interest, chiefly
the motion of pedestrians in complex domains scattered with obstacles.Comment: 25 pages, 9 figure
Non-local first-order modelling of crowd dynamics: a multidimensional framework with applications
In this work a physical modelling framework is presented, describing the
intelligent, non-local, and anisotropic behaviour of pedestrians. Its
phenomenological basics and constitutive elements are detailed, and a
qualitative analysis is provided. Within this common framework, two first-order
mathematical models, along with related numerical solution techniques, are
derived. The models are oriented to specific real world applications: a
one-dimensional model of crowd-structure interaction in footbridges and a
two-dimensional model of pedestrian flow in an underground station with several
obstacles and exits. The noticeable heterogeneity of the applications
demonstrates the significance of the physical framework and its versatility in
addressing different engineering problems. The results of the simulations point
out the key role played by the physiological and psychological features of
human perception on the overall crowd dynamics.Comment: 26 pages, 17 figure
Handling congestion in crowd motion modeling
We address here the issue of congestion in the modeling of crowd motion, in
the non-smooth framework: contacts between people are not anticipated and
avoided, they actually occur, and they are explicitly taken into account in the
model. We limit our approach to very basic principles in terms of behavior, to
focus on the particular problems raised by the non-smooth character of the
models. We consider that individuals tend to move according to a desired, or
spontanous, velocity. We account for congestion by assuming that the evolution
realizes at each time an instantaneous balance between individual tendencies
and global constraints (overlapping is forbidden): the actual velocity is
defined as the closest to the desired velocity among all admissible ones, in a
least square sense. We develop those principles in the microscopic and
macroscopic settings, and we present how the framework of Wasserstein distance
between measures allows to recover the sweeping process nature of the problem
on the macroscopic level, which makes it possible to obtain existence results
in spite of the non-smooth character of the evolution process. Micro and macro
approaches are compared, and we investigate the similarities together with deep
differences of those two levels of description
Modeling rationality to control self-organization of crowds: An environmental approach
In this paper we propose a classification of crowd models in built
environments based on the assumed pedestrian ability to foresee the movements
of other walkers. At the same time, we introduce a new family of macroscopic
models, which make it possible to tune the degree of predictiveness (i.e.,
rationality) of the individuals. By means of these models we describe both the
natural behavior of pedestrians, i.e., their expected behavior according to
their real limited predictive ability, and a target behavior, i.e., a
particularly efficient behavior one would like them to assume (for, e.g.,
logistic or safety reasons). Then we tackle a challenging shape optimization
problem, which consists in controlling the environment in such a way that the
natural behavior is as close as possible to the target one, thereby inducing
pedestrians to behave more rationally than what they would naturally do. We
present numerical tests which elucidate the role of rational/predictive
abilities and show some promising results about the shape optimization problem
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