# Congestion-Free Ant Traffic: Jam Absorption Mechanism in Multiple Platoons
## 1 Introduction  
Recent advancement in computation has made it possible to record, simulate, and analyze multi-agent complex systems by using agent-based modeling [1; 2]. Agent-based modeling is widely used for the modeling and synthesis of complex distributed systems such as distributed financial markets, artificial intelligence, and town planning [2; 3; 4]. Agent-based modeling is also used to study spatiotemporal organization in systems of interacting agents, including vehicular traffic, molecular motors moving on polymeric tracks, and ant colonies moving on trails [5; 6; 7; 8]. One of the major uses of agent-based modeling is the analysis of emergent behaviors in interacting multi-agent systems, which cannot be understood by merely studying individual elements of a complex system. In recent years, the study of ants' emergent behavior on trails has attracted particular attention for several reasons. The vast trail systems that ants form for transportation share many of the features of vehicular transportation systems [9; 10; 11; 12; 13; 14; 15; 16; 17]. Individual trails created by an ant colony can be functional for hours and can be considered analogous to highways. Thus, the collective movement of ants on trails (\"ant traffic\" (AT)) is analogous to vehicular traffic on a highway network [5; 18]. The social behavior of ants also indicates that biological evolution may have optimized AT; examples include (i) the formation of three lanes in bidirectional AT and (ii) natural selection of the shortest path to a food source [10; 16; 17; 19; 20; 21; 22; 23]. A recent empirical study of unidirectional AT in _Leptogenys processionalis_ revealed several exciting properties [14]. The average velocity of ants on a trail remained almost independent of density on that trail. Consequently, no jamming phase (referred to simply as \"jamming\") was observed in the fundamental diagrams. It was also found that ants on a trail formed clusters. The fundamental diagrams for AT are in contrast to those of vehicular traffic. In the latter, the average velocity decreases at high density, and thus, jamming occurs, indicating stop-and-go behavior and congestion [14]. Inspired by these fascinating findings about AT, a few previous theoretical studies attempted to explain the mechanism for jam-free AT on a unidirectional trail [9; 13; 15]. In [13], it was assumed that ants on the trail detect their headway distance visually and control their propelling force according to the headways. The model in [13] was able to capture all the features observed in [14], and it also indicated that ants might have nearest-neighbor repulsion, which was previously unknown. However, previous physiological studies about ants indicated that ant species with trail pheromones are practically blind and cannot detect objects farther than a few millimeters [10; 21]. On the other hand, in the case of [15], it was assumed that ants use chemotaxis for traffic management on AT. Specifically, the work in [15] argued that ants reduce their velocity for a corresponding increase in pheromone concentration. The model in [15] also captured all the major observations from [14], and it also supported the findings of [13], which suggested that ants might have nearest-neighbor repulsion. However, although the above-mentioned assumption of [15] partially agreed with previous studies (ants use chemotaxis for traffic management), previous studies showed that ants are attracted towards a higher concentration of pheromones (in contrast with the assumption in [15], ants might be increasing their velocity when they discover a higher concentration of pheromones) [10; 21; 24; 25]. Meanwhile, the model in [9] can be considered a pioneer model in the traffic flow analysis of AT, which has been well analyzed [5; 6; 11; 12; 26; 27]. The model in [9] is simple, yet it is in accordance with previous studies. However, it is a general model of ant traffic, which was proposed and analyzed prior to [14]. Therefore, it should be further improved and analyzed in light of the findings from [14].