6,756 research outputs found
A simple Monte Carlo model for crowd dynamics
In this paper we introduce a simple Monte Carlo method for simulating the
dynamics of a crowd. Within our model a collection of hard-disk agents is
subjected to a series of two-stage steps, implying (i) the displacement of one
specific agent followed by (ii) a rearrangement of the rest of the group
through a Monte Carlo dynamics. The rules for the combined steps are determined
by the specific setting of the granular flow, so that our scheme should be
easily adapted to describe crowd dynamics issues of many sorts, from stampedes
in panic scenarios to organized flow around obstacles or through bottlenecks.
We validate our scheme by computing the serving times statistics of a group of
agents crowding to be served around a desk. In the case of a size homogeneous
crowd, we recover intuitive results prompted by physical sense. However, as a
further illustration of our theoretical framework, we show that heterogeneous
systems display a less obvious behavior, as smaller agents feature shorter
serving times. Finally, we analyze our results in the light of known properties
of non-equilibrium hard-disk fluids and discuss general implications of our
model.Comment: to be published in Physical Review
COORDINATION OF LEADER-FOLLOWER MULTI-AGENT SYSTEM WITH TIME-VARYING OBJECTIVE FUNCTION
This thesis aims to introduce a new framework for the distributed control of multi-agent systems with adjustable swarm control objectives. Our goal is twofold: 1) to provide an overview to how time-varying objectives in the control of autonomous systems may be applied to the distributed control of multi-agent systems with variable autonomy level, and 2) to introduce a framework to incorporate the proposed concept to fundamental swarm behaviors such as aggregation and leader tracking. Leader-follower multi-agent systems are considered in this study, and a general form of time-dependent artificial potential function is proposed to describe the varying objectives of the system in the case of complete information exchange. Using Lyapunov methods, the stability and boundedness of the agents\u27 trajectories under single order and higher order dynamics are analyzed. Illustrative numerical simulations are presented to demonstrate the validity of our results. Then, we extend these results for multi-agent systems with limited information exchange and switching communication topology. The first steps of the realization of an experimental framework have been made with the ultimate goal of verifying the simulation results in practice
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