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Optimal traffic organization in ants under crowded conditions

Nature volume 428, pages 70–73 (2004)Cite this article

Abstract

Efficient transportation, a hot topic in nonlinear science1, is essential for modern societies and the survival of biological species. Biological evolution has generated a rich variety of successful solutions2, which have inspired engineers to design optimized artificial systems3,4. Foraging ants, for example, form attractive trails that support the exploitation of initially unknown food sources in almost the minimum possible time5,6. However, can this strategy cope with bottleneck situations, when interactions cause delays that reduce the overall flow? Here, we present an experimental study of ants confronted with two alternative routes. We find that pheromone-based attraction generates one trail at low densities, whereas at a high level of crowding, another trail is established before traffic volume is affected, which guarantees that an optimal rate of food return is maintained. This bifurcation phenomenon is explained by a nonlinear modelling approach. Surprisingly, the underlying mechanism is based on inhibitory interactions. It points to capacity reserves, a limitation of the density-induced speed reduction, and a sufficient pheromone concentration for reliable trail perception. The balancing mechanism between cohesive and dispersive forces appears to be generic in natural, urban and transportation systems.

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Figure 1: Experimental set-up.
Figure 2: Average number of ants per minute crossing the two branches of the bridge within intervals of five minutes.
Figure 3: Experimental results.
Figure 4: Analytical and Monte Carlo simulation results.

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Acknowledgements

We thank G. Theraulaz and all the members of his team ‘Ethology and modelization of collective behaviours’ for discussions and comments on the manuscript. We also thank A. Schadschneider for discussions.

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Authors and Affiliations

  1. Centre de Recherches sur la Cognition Animale, UMR CNRS 5169, Université Paul Sabatier, 118 Route de Narbonne, F-31062, Toulouse Cedex, 4, France

    Audrey Dussutour & Vincent Fourcassié

  2. Centre d'Études des Phénomènes Non-linéaires et des Systèmes Complexe, Université Libre de Bruxelles, CP231, Boulevard du Triomphe, 1050, Bruxelles, Belgium

    Audrey Dussutour & Jean-Louis Deneubourg

  3. Institute for Economics and Traffic, Dresden University of Technology, D-01062, Dresden, Germany

    Dirk Helbing

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  1. Audrey Dussutour
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  2. Vincent Fourcassié
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  4. Jean-Louis Deneubourg
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Correspondence to Audrey Dussutour.

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Dussutour, A., Fourcassié, V., Helbing, D. et al. Optimal traffic organization in ants under crowded conditions. Nature 428, 70–73 (2004). https://doi.org/10.1038/nature02345

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