ANTS seem to have cracked a problem we humans haven't. While our cars get clogged in jams, ants help each other to move around their colony much more efficiently. Understanding how they do this could inspire more effective routing of road traffic.
Collective intelligence expert Dirk Helbing from the Dresden University of Technology in Germany and his team investigated how ants move around their colony. They set up an ant highway with two routes of different widths from the nest to some sugar syrup. Unsurprisingly, the narrower route soon became congested. But when an ant returning along the congested route to the nest collided with another ant just starting out, the returning ant pushed the newcomer onto the other path. However, if the returning ant had enjoyed a trouble-free journey, it did not redirect the newcomer
The researchers created a computer model of more complex ant networks with routes of different lengths. The team found that even though ants being rerouted sometimes took a longer route, they still got to the food quickly and efficiently.
If human drivers travelling in opposite directions could pass congestion information to each other in this way, we would all be better off.
Analytical and Numerical Investigation of Ant Behavior Under Crowded Conditions....... 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.