Optimal traffic organization in ants under crowded conditions

By A. Dussutour, V. Fourcassié, Dirk Helbing, Jean-Louis Deneubourg. Nature, 2004

303 citations recorded by the source corpus.

Efficient transportation, a hot topic in nonlinear science, is essential for modern societies and the survival of biological species. Biological evolution has generated a rich variety of successful solutions, which have inspired engineers to design optimized artificial systems. Foraging ants, for example, form attractive trails that support the exploitation of initially unknown food sources in almost the minimum possible time. 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.

Subfields: Ecology, Evolution, Behavior and Systematics, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1a39a363356d4579148fbffc6bd0bfc748ab6e32

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Citations in the corpus

Self-organized structures in a superorganism: do ants "behave" like molecules? (2006, background): “Likewise, an environmental factor that alters ants’ movement or perception range can deeply influence the patterns that will emerge at the collective level [27,47,48].”
From Crowd Dynamics to Crowd Safety: a Video-Based Analysis (2008, background): “While “panic” has recently been studied in animal experiments with mice [34] and ants [3] there is still an evident lack of data on critical conditions in human crowds.”
The biological principles of swarm intelligence (2007, background): “From the traffic management on a foraging network (Burd 2006; Couzin and Franks 2003; Dussutour et al. 2004; Vittori et al. 2006), to the building of efficient structures (Buhl et al.”
Self-organised complex aerial displays of thousands of starlings: a model (2009, background): “For instance, the foraging and grouping behavior of social insects (Gautrais et al. 2003; Dussutour et al. 2004; Ame et al. 2006) and of primates (te Boekhorst and Hogeweg 1994a, 1994b; Hemelrijk et al.”