Using an agent-based traffic models, we analyze the manner in which the number of platoons within a traffic system is correlated with the appearance of traffic jams. Two definitions of a platoon are proposed and verified using agent-based simulations to find the one that provides the most realistic representation of traffic behavior in a stochastic model. We observe that traffic jams are closely related to the convergence of multiple platoons into a single platoon containing all the agents in the model. We also observed that at high-density, traffic system maintains a metastable state when it has multiple platoons in it. A traffic jam occurs when these multiple platoons are merged into a single platoon, which is equivalent to the concept of an infinite cluster in percolation theory.

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.

In this paper, we present an analysis of the correlation between the driving efficiency of drivers and traffic congestions on a highway. An agent-based model of highway traffic is used, where individual drivers are represented by agents undergoing single-lane unidirectional motion on a highway. In the proposed model, changes in the agent-modelling rules are able to simulate behavioural changes in driving efficiency of drivers. In addition, results from multiple simulations are compared with real life data. These comparisons show that during traffic congestions, driving efficiency of amateur drivers on a highway declines with an increase in the vehicular density on the same highway. Furthermore, this decrease in the driving efficiency of amateur drivers leads to a reduction of average velocity of all drivers on the same highway.

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.