Professors at the University of Trento studied the behavior of ants to understand how these insects move efficiently without getting stuck, even when they are in large groups.
Marco Guerrieri, a professor specializing in road and rail infrastructure, and Nicola Pugno, a professor of solid mechanics and structures, are co-authors of the study.
Ant behavior has inspired various scientific fields due to their ability to solve complex problems. During movement, ants create crisscrossing networks that resemble vehicle traffic on highways, the media writes.
By analyzing a 30-centimeter ant trail, which is 100 times longer than their body, and using deep learning algorithms to track their movements on video, the researchers mapped the trajectories, speed and flow of the ants’ movements. The results show that ants use strategies such as forming platoons, maintaining a steady speed, and moving without overtaking to avoid traffic jams, even when the groups are large.
According to Guerrieri, ants are one of the few species that can manage two-way traffic flows, similar to our roads but without congestion. He added that the ants follow pheromone trails marked by leading ants, moving in columns with small gaps and without overtaking.
From ants walking on pheromone trails to vehicles moving in highway lanes, the main challenge for all collective systems is avoiding congestion and delays, the researchers point out.
The research showed that ants solve complex traffic problems using simple, self-organizing rules that are not imposed from the outside, as is the case in traditional traffic. These rules stem from direct contact or chemical signals between ants, making their behavior more cooperative than vehicles on conventional roads.
The study offers several key contributions. First, it identifies microscopic traffic variables found in ant streams and analyzes the collective strategies they use to avoid congestion. Based on these findings, the study proposes traffic regulation strategies inspired by ants’ behavior.
Guerrieri suggests that future traffic systems for autonomous vehicles could be inspired by ants’ behavior. While ants “communicate” through pheromones, autonomous vehicles could use advanced communication technologies to interact with each other and with road infrastructure, forming coordinated platoons. This would allow them to travel in parallel lanes at high speeds and short distances, improving traffic efficiency, service levels, and reducing greenhouse gas emissions.
However, the study also highlights several limitations, including the fact that the traffic data focused on only one species of ant, which limits the generalizability of the results to all species. Also, the analysis was conducted on a straight section of the path without curves, intersections, or areas of conflict between streams. Furthermore, autonomous vehicle technology is still developing, and there is no empirical data from real-world traffic to support these findings.
