Сценарное моделирование движения беспилотных транспортных средств в искусственной дорожной сети с использованием FLAME GPU
This article presents a model of the ground autonomous vehicles (AVs) motion in the Artificial Road Network (ARN) belonging to the "Manhattan Lattice" type with the implementation of the large-scale agent-based modeling framework FLAME GPU. The most important scenarios of the traffic situation development are investigated, in particular, which are associated with reducing visibility on the roads, especially in conditions of unusual behaviour of some agents of the traffic system, e.g. the unexpected appearance of obstacles such as agent-pedestrians and chaotic maneuvering of usual (i.e. manned) vehicles (MVs) having abnormal characteristics. A new approach to designing large-scale agent-based transportation simulations based on ARNs with a complex configuration and implementation using supercomputer technologies is proposed.