Active walker model for the formation of human and animal trail systems

Helbing, Dirk; Schweitzer, Frank; Keltsch, Joachim; Molnár, Péter

doi:10.1103/physreve.56.2527

Cited by 239 publications

(178 citation statements)

References 39 publications

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“…• Trail formation: Although human and animal trails are formed for rather different purposes their structures have some similarities [20,21]. Often human trails are formed as a short-cut which makes it attractive to leave a paved path.…”

Section: Collective Phenomenamentioning

confidence: 99%

Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics

Kirchner

Schadschneider

2002

Physica A: Statistical Mechanics and its Applications

868

461

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We present simulations of evacuation processes using a recently introduced cellular automaton model for pedestrian dynamics. This model applies a bionics approach to describe the interaction between the pedestrians using ideas from chemotaxis. Here we study a rather simple situation, namely the evacuation from a large room with one or two doors. It is shown that the variation of the model parameters allows to describe different types of behaviour, from regular to panic. We find a nonmonotonic dependence of the evacuation times on the coupling constants. These times depend on the strength of the herding behaviour, with minimal evacuation times for some intermediate values of the couplings, i.e. a proper combination of herding and use of knowledge about the shortest way to the exit.

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Section: Collective Phenomenamentioning

confidence: 99%

Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics

Kirchner

Schadschneider

2002

Physica A: Statistical Mechanics and its Applications

868

461

View full text Add to dashboard Cite

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“…Formation of these trails have been described theoretically in terms of active-walker models. The mechanism is ubiquitous in nature and similar to river basin formation [17], formation of pedestrian trails [18,19], and formation of axon bundles in mammalian sensory neurons [20,21].…”

Section: Introductionmentioning

confidence: 99%

Absence of jamming in ant trails: Feedback control of self-propulsion and noise

Chaudhuri¹,

Nagar²

2015

Phys. Rev. E

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We present a model of ant traffic considering individual ants as self-propelled particles undergoing single file motion on a one-dimensional trail. Recent experiments on unidirectional ant traffic in wellformed natural trails showed that the collective velocity of ants remains approximately unchanged, leading to absence of jamming even at very high densities [John et. al., Phys. Rev. Lett. 102, 108001 (2009)]. Assuming a feedback control mechanism of self-propulsion force generated by each ant using information about the distance from the ant in front, our model captures all the main features observed in the experiment. The distance headway distribution shows a maximum corresponding to separations within clusters. The position of this maximum remains independent of average number density. We find a non-equilibrium first order transition, with the formation of an infinite cluster at a threshold density where all the ants in the system suddenly become part of a single cluster.

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“…The eld of active w alker models 22,117,118] is concerned with modeling \walkers" (be they human walkers or instead simple physical objects) crossing elds along trajectories, where those trajectories are a function of several factors, including in particular the trails already worn into the eld. Often the kind of trajectories considered are those that can be cast as solutions to actional extremization problems so that the walkers can be explicitly viewed as agents optimizing a private utility.…”

Section: Active Walker Modelsmentioning

confidence: 99%

Theory of Collective Intelligence

Wolpert

2004

Collectives and the Design of Complex Systems

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This paper surveys the emerging science of how to design a \COllective INtelligence" (COIN). A COIN is a large multi-agent system where: i) There is little to no centralized, personalized communication and/or control. ii) There is a provided world utility function that rates the possible histories of the full system.In particular, we a r e i n terested in COINs in which e a c h a g e n t runs a reinforcement learning (RL) algorithm. The conventional approach to designing large distributed systems to optimize a world utility does not use agents running RL algorithms. Rather, that approach begins with explicit modeling of the dynamics of the overall system, followed by detailed hand-tuning of the interactions between the components to ensure that they \cooperate" as far as the world utility i s concerned. This approach is labor-intensive, often results in highly nonrobust systems, and usually results in design techniques that have limited applicability. In contrast, we w i s h t o s o l v e the COIN design problem implicitly, via the \adaptive" character of the RL algorithms of each of the agents. This approach i n troduces an entirely new, profound design problem: Assuming the RL algorithms are able to achieve high rewards, what reward functions for the individual agents will, when pursued by those agents, result in high world utility? In other words, what reward functions will best ensure that we d o n o t have phenomena like t h e tragedy of the commons, Braess's paradox, or the liquidity trap? Although still very young, research speci cally concentrating on the COIN design problem has already resulted in successes in arti cial domains, in particular in packet-routing, the leader-follower problem, and in variants of Arthur's El Farol bar problem. It is expected that as it matures and draws upon other disciplines related to COINs, this research will greatly expand the range of tasks addressable by human engineers. Moreover, in addition to drawing on them, such a fully developed science of COIN design may provide much insight into other already established scienti c elds, such as economics, game theory, and population biology.

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Active walker model for the formation of human and animal trail systems

Cited by 239 publications

References 39 publications

Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics

Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics

Absence of jamming in ant trails: Feedback control of self-propulsion and noise

Theory of Collective Intelligence

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