Better tired than lost: Turtle ant trail networks favor coherence over short edges

Creating a routing backbone is a fundamental problem in both biology and engineering. The routing backbone of the trail networks of arboreal turtle ants (Cephalotes goniodontus) connects many nests and food sources using trail pheromone deposited by ants as they walk. Unlike species that forage on the ground, the trail networks of arboreal ants are constrained by the vegetation. We examined what objectives the trail networks meet by comparing the observed ant trail networks with networks of random, hypothetical trail networks in the same surrounding vegetation and with trails optimized for four objectives: minimizing path length, minimizing average edge length, minimizing number of nodes, and minimizing opportunities to get lost. The ants’ trails minimized path length by minimizing the number of nodes traversed rather than choosing short edges. In addition, the ants’ trails reduced the opportunity for ants to get lost at each node, favoring nodes with 3D configurations most likely to be reinforced by pheromone. Thus, rather than finding the shortest edges, turtle ant trail networks take advantage of natural variation in the environment to favor coherence, keeping the ants together on the trails.

Analysis of Cooperative Perception in Ant Traffic and Its Effects on Transportation System by Using a Congestion-Free Ant-Trail Model

We investigated agent-based model simulations that mimic an ant transportation system to analyze the cooperative perception and communication in the system. On a trail, ants use cooperative perception through chemotaxis to maintain a constant average velocity irrespective of their density, thereby avoiding traffic jams. Using model simulations and approximate mathematical representations, we analyzed various aspects of the communication system and their effects on cooperative perception in ant traffic. Based on the analysis, insights about the cooperative perception of ants which facilitate decentralized self-organization is presented. We also present values of communication-parameters in ant traffic, where the system conveys traffic conditions to individual ants, which ants use to self-organize and avoid traffic-jams. The mathematical analysis also verifies our findings and provides a better understanding of various model parameters leading to model improvements.

Comparative Quantification of Trail-Following Behavior in Pest Ants

A comparison of trail-following movement parameters of six major urban pest ants, Nylanderia fulva (Forel) (Hymenoptera: Formicidae), Pheidole megacephala, Linepithema humile (Mayr), Solenopsis invicta Buren, Paratrechina longicornis (Forel), and Technomyrmex albipes (Smith) demonstrated several differences in velocity of movement, amplitude of the deviations from a marked trail, percent fidelity to the trail, number of curves per unit of trail, and trail-following accuracy. Paratrechina longicornis and N. fulva had the largest deviations from the marked trails and moved three times faster (25–30 mm/s) along the trail than the slowest ant, S. invicta (< 10 mm/s), with other ants following between these extremes. Species differences in relation to going toward or returning from food were observed in a few cases, especially with Pa. longicornis for which velocity, amplitude, and trail fidelity differed between the foraging and return trails. Quantification of ant trail-following movement parameters can be useful in understanding the mechanics of ant movement and may be important in testing specific strategies and products that disrupt trail-following behavior.

Better tired than lost: turtle ant trail networks favor coherence over shortest paths

Creating a routing backbone is a fundamental problem in both biology and engineering. The routing backbone of arboreal turtle ants (Cephalotes goniodontus) connects many nests and food sources using trail pheromone deposited by ants as they walk. Unlike species that forage on the ground, the trail networks of arboreal ants are constrained by the vegetation. We examined what objectives turtle ant networks meet by comparing the observed ant trail networks with networks of random, hypothetical trails in the same surrounding vegetation and with trails optimized for each objective. The ants’ trails minimized the number of nodes traversed, reducing the opportunity for ants to get lost at each node, and favored nodes with 3D configurations most likely to be reinforced by pheromone, thus keeping the ants together on the same trail. Rather than finding the shortest path, turtle ant trail networks take advantage of natural variation in the environment to favor coherence, keeping the ants together on the trails.

Congestion-Free Ant Traffic: Jam Absorption Mechanism in Multiple Platoons

In this paper, an agent-based model of ant traffic on a unidirectional single-lane ant trail is presented to provide better understanding of the jam-free traffic of an ant colony. On a trail, the average velocity of ants remains approximately constant irrespective of density, thereby avoiding jamming. Assuming chemotaxis, we analyze platoon-related scenarios to assess the marching-platoon hypothesis, which claims that ants on a trail form a single platoon in which they march synchronously, thereby reducing hindrances due to increasing density. Contrary to that hypothesis, our findings show that ants on a trail do not march synchronously and do experience stop-and-go motion. However, more interestingly, our study also indicates that the ants’ chemotaxis behavior leads to a peculiar jam absorption mechanism, which helps to maintain free flow on a trail and avoids jamming. Again, contrary to the marching-platoon hypothesis, our findings also indicate that, rather than assisting traffic flow, forming a single cluster actually triggers jamming.