How do fire ants keep the traffic flowing as they excavate their tunnels? | Georgia Tech
By observing how fire ants excavate their deep and elaborate subterranean lairs, researchers have gleaned new insights into understanding optimal traffic flow in confined or crowded environments. The research findings published in the August 17 issue of Science could one day inform the movement of self-driving cars to navigate rush-hour traffic safely, or prevent nanorobots surging through our bloodstream from clogging critical arteries.
The study reveals specific behaviors of individual fire ants — like taking a rest — that reduce crowdedness and prevent 'ant-jams' from forming within their nests as they move about and dig new tunnels. The strategies could be applied to non-living systems that require the steady flow of large groups in confined or difficult to navigate spaces, such as robot swarms tasked with navigating and removing rubble after a disaster.
"Looking in detail at living systems — organisms just doing what they're doing — can lead you to discover beautiful natural phenomenon, which could potentially influence technological advances," said Daniel Goldman, a physicist at Georgia Tech and coauthor of the study.
Any time dense groups of objects flow through a restricted system, there is a potential for clusters or clogs to form. When those objects each have a goal, like humans in cars confined to the four lanes of a freeway and trying to make it home, these clusters and clogs can be detrimental. Clogs are a challenge in engineered systems like robot swarms that require each to remain autonomous, yet work together to achieve a collective goal in unpredictable environments without the help of external controls guiding the collective.
Social insects like ants routinely perform many tasks that demand a steady flow, such as excavating their tunnels. Other tasks like brood care or foraging also require rapid movement throughout the networks of narrow tunnels. Despite the tens-of-thousands of ants working together within a single colony, however, clusters of ants rarely form the flow-stopping clogs that could quickly bring the work to a halt, according to Goldman and his colleagues.
Goldman is interested in understanding how living systems perform certain tasks by using computational models and robots as scientific tools to discover the underlying principles of natural phenomena.
"Our study is one where we deeply integrate careful biological experimentation with theoretical computation and robotic models to pick apart different aspects of the living system's behavior," said Goldman.
In monitoring how individual fire ants, each marked with a colored dot on their back, worked together to excavate a new tunnel, the researchers identified peculiar behaviors. Many of the ants remained idle, not actively working but rather lounging about the tunnel walls, while others did the majority of the work. Only 30% of the ants performed nearly 70% of the work at any given time. Others marched from the excavated tunnel to the nest's exit without carrying any excavated material. According to the scientists, these seemingly counterproductive social behaviors are the adaptive strategies that ants have developed to allow them to quickly and efficiently excavate within their crowded nests.
"This is a traffic problem, and what the ants seem to be trying to do is keep the traffic flowing well. These strategies of giving up and reversing, or just not working at all tend to prevent large clusters or dissolve them pretty quickly," said Goldman.
The advantages of these adaptive behaviors were confirmed in computational and robot models where they could be manipulated as variables to see their effects on excavation performance. In simulations where each ant aggressively excavated, the tunnels quickly clogged. When each ant was allowed a small chance to decide to give up or remain idle, traffic flow improved.
According to Goldman, the ants have it all figured out. "We found that the optimal distribution, which the simulation converged on pretty quickly, was the one that looked a lot like the ants," he said.
The adaptive social behaviors of ants identified in the study offer some principal rules or guidelines which may one day help future teams of robots work effectively together to accomplish similar tasks. By learning from one another, large groups of robots could communicate with one another to collectively decide the conditions for optimal traffic flow considering the task at hand. Figuring out how to do this remains an active question, said Goldman, one that could be solved by a deeper understanding of how each ant makes decisions about whether to work, give up or remain idle in the context of the group's goals.
"It seems insane to want to study how ants collectively move around in tunnels," said Goldman. "They tell you interesting things about nature, such as the evolution of social behaviors, and in that I think there are potential solutions for our engineering friends to make devices that have real benefits."