No Arabic abstract
Despite the vast amount of studies on pedestrian flow, the data concerning high densities are still very inadequate. We organize one large-scale pedestrian flow experiment on a ring corridor. With 278 participants, the density as high as 9 m^(-2) is reached. In the uni-directional flow, four different states are observed, including the free flow, congested state, over-congested state and hyper-congested state. The features of the hyper-congested state are similar to the crowd turbulence reported in the empirical data of Helbing et al., and the transition between the stopped state and the moving state can be found. The flow rates in the over-congested state are nearly constant, due to the downstream propagation of pedestrian clusters. In the bi-directional flow, three different types of lane formations are observed in the experiment: (1) three lanes are directly formed ; (2) two lanes are directly formed; (3) firstly three lanes are formed, and then they transit into two lanes. After the lane formation, some interesting phenomena have been observed, including the inhomogeneous distribution of pedestrians across the lanes, and the formation and dissipation of localized crowd. Our study is expected to help for better understanding and modeling the dynamics of high density pedestrian flow.
Swarm intelligence is widely recognized as a powerful paradigm of self-organized optimization, with numerous examples of successful applications in distributed artificial intelligence. However, the role of physical interactions in the organization of traffic flows in ants under crowded conditions has only been studied very recently. The related results suggest new ways of congestion control and simple algorithms for optimal resource usage based on local interactions and, therefore, decentralized control concepts. Here, we present a mathematical analysis of such a concept for an experiment with two alternative ways with limited capacities between a food source and the nest of an ant colony. Moreover, we carry out microscopic computer simulations for generalized setups, in which ants have more alternatives or the alternative ways are of different lengths. In this way and by variation of interaction parameters, we can get a better idea, how powerful congestion control based on local repulsive interactions may be. Finally, we will discuss potential applications of this design principle to routing in traffic or data networks and machine usage in supply systems.
We study how large functional networks can grow stably under possible cascading overload failures and evaluated the maximum stable network size above which even a small-scale failure would cause a fatal breakdown of the network. Employing a model of cascading failures induced by temporally fluctuating loads, the maximum stable size $n_{text{max}}$ has been calculated as a function of the load reduction parameter $r$ that characterizes how quickly the total load is reduced during the cascade. If we reduce the total load sufficiently fast ($rge r_{text{c}}$), the network can grow infinitely. Otherwise, $n_{text{max}}$ is finite and increases with $r$. For a fixed $r,(<r_{text{c}})$, $n_{text{max}}$ for a scale-free network is larger than that for an exponential network with the same average degree. We also discuss how one detects and avoids the crisis of a fatal breakdown of the network from the relation between the sizes of the initial network and the largest component after an ordinarily occurring cascading failure.
Production in an economy is a set of firms activities as suppliers and customers; a firm buys goods from other firms, puts value added and sells products to others in a giant network of production. Empirical study is lacking despite the fact that the structure of the production network is important to understand and make models for many aspects of dynamics in economy. We study a nation-wide production network comprising a million firms and millions of supplier-customer links by using recent statistical methods developed in physics. We show in the empirical analysis scale-free degree distribution, disassortativity, correlation of degree to firm-size, and community structure having sectoral and regional modules. Since suppliers usually provide credit to their customers, who supply it to theirs in turn, each link is actually a creditor-debtor relationship. We also study chains of failures or bankruptcies that take place along those links in the network, and corresponding avalanche-size distribution.
Lane formation in bidirectional pedestrian streams is based on a stimulus-response mechanism and strategies of navigation in a fast-changing environment. Although microscopic models that only guarantee volume exclusion can qualitatively reproduce this phenomenon, they are not sufficient for a quantitative description. To quantitatively describe this phenomenon, a minimal anticipatory collision-free velocity model is introduced. Compared to the original velocity model, the new model reduces the occurrence of gridlocks and reproduces the movement of pedestrians more realistically. For a quantitative description of the phenomenon, the definition of an order parameter is used to describe the formation of lanes at transient states and to show that the proposed model compares relatively well with experimental data. Furthermore, the model is validated by the experimental fundamental diagrams of bidirectional flows.
Recent empirical studies suggest that heavy-tailed distributions of human activities are universal in real social dynamics [Muchnik, emph{et al.}, Sci. Rep. textbf{3}, 1783 (2013)]. On the other hand, community structure is ubiquitous in biological and social networks [M.~E.~J. Newman, Nat. Phys. textbf{8}, 25 (2012)]. Motivated by these facts, we here consider the evolutionary Prisoners dilemma game taking place on top of a real social network to investigate how the community structure and the heterogeneity in activity of individuals affect the evolution of cooperation. In particular, we account for a variation of the birth-death process (which can also be regarded as a proportional imitation rule from social point of view) for the strategy updating under both weak- and strong-selection (meaning the payoffs harvested from games contribute either slightly or heavily to the individuals performance). By implementing comparative studies, where the players are selected either randomly or in terms of their actual activities to playing games with their immediate neighbors, we figure out that heterogeneous activity benefits the emergence of collective cooperation in harsh environment (the action for cooperation is costly) under strong selection, while it impairs the formation of altruism under weak selection. Moreover, we find that the abundance of communities in the social network can evidently foster the fixation of cooperation under strong-selection, in contrast to the games evolving on the randomized counterparts. Our results are therefore helpful for us to better understand the evolution of cooperation in real social systems.