Multilevel and holonic model for dynamic holarchy management: Application to large-scale road traffic

Abstract

Nowadays, with the emergence of connected objects and cars, road traffic systems become more and more complex and exhibit hierarchical behaviors at several levels of detail. The multilevel modeling approach is generally appropriate to represent traffic from several perspectives. However, few works have been interested in multilevel traffic modeling. Moreover, most of the available multilevel models of traffic proposed in the literature are static because they use a set of predefined levels of detail and these representations cannot change during simulation. To tackle these drawbacks, this paper introduces a holonic multilevel and dynamic traffic model for large-scale traffic systems. To this end, the paper proposes a density-based upward holonification model to group similar entities to structure the holarchy of traffic. Additionally, it proposes a downward holonification model based on the Gaussian distribution to break down non-atomic entities. Moreover, the paper presents a methodology for the management of the holarchy’s dynamics over time allowing the transitions between heterogeneous representations of a traffic system. Furthermore, multilevel indicators based on standard deviation are proposed to assess the consistency of the simulation results. The experiments are conducted with several simple scenarios on a highway to investigate the trade-off between the simulation accuracy and the availability of computational resources.