Simulation of Motion of an Ensemble of Unmanned Ground Vehicles Using FLAME GPU

Abstract

A new approach to modeling the spatial dynamics of unmanned ground vehicles (UV) and conventional vehicles (CV) using the FLAME GPU supercomputer agent-based simulation platform is presented. A new simulation model of an artificial road network (ARN) of the "Manhattan Grid" type is proposed, within the framework of which the spatial dynamics of the UV and CV ensemble is studied under various scenario conditions. The effects of "turbulence" and "crush" (traffic congestion) resulting from intensive and dense traffic of vehicles are investigated.

Simulation of rates of traffic accidents involving unmanned ground vehicles within a transportation system for the ‘smart city’

“…Previously, in [2][3][4], the existence of scenarios for accident-free movement of the UGVs ensemble interacting with manned ground vehicles (MGVs) has been shown for various configurations of the digital road networks and other environment characteristics. In particular, in the work [2] general conditions leading to occurrence of such accidents (mainly vehicle manoeuvres in dense traffic conditions) have been determined with the use of the developed agent-based model [5,6]. Thus, the 'turbulence' and 'crowding' effects arise with an increase in the density of UGVs and MGVs, when some drivers seek to increase their personal space through frequent lane changes, overtaking and braking.…”

“…Note that previously the phenomenological approach was proposed for modeling crowd behavior [17], considering the influence of the 'crowd effect' and other environmental characteristics (in particular, its configuration). A multi-agent system for control of UGVs has been developed based on this approach [5,6]. For this purpose, the large-scale agent-based simulation framework FLAME GPU was used 2 [5,18,19]; it makes it possible to efficiently parallelize the logic of agents' behavior and consider their individual decision-making systems when modeling the spacial dynamics of an ensemble of interacting vehicles.…”

“…A multi-agent system for control of UGVs has been developed based on this approach [5,6]. For this purpose, the large-scale agent-based simulation framework FLAME GPU was used 2 [5,18,19]; it makes it possible to efficiently parallelize the logic of agents' behavior and consider their individual decision-making systems when modeling the spacial dynamics of an ensemble of interacting vehicles. On the other hand, the phenomenological approach is based on Dirk Helbing's studies [20,21], which deal with models of humans and pedestrians' behavior under the influence of social forces.…”

“…Within the concept of the 'smart city' development, control systems for unmanned railway vehicles [22,23] are also of great interest: they can be used to form optimal routs for freight wagons (controlled by unmanned locomotives) for a 2 https://flamegpu.com/ given set of freight wagons and a list of requests for a cargo transportation. Also, a promising area of research is the use of fuzzy [4,5] and hierarchical clustering [24] methods to identify problem areas of the urban road network [25] (e.g., traffic jams, accident locations, etc.). This paper proposes an approach to modeling the rates of accidents and improving road safety within the scale of the 'smart city' by combining computational and expert decision-making methods.…”

Simulation of migration and demographic processes using FLAME GPU

“…The model of 'nomads and farmers' [2,3], in which some agents ('conditional farmers') create resources, while others destroy them in order to expand personal space ('conditional nomads') should be noted. Also, the models of population segregation of the Schelling class [4,5], models of movement of an ensemble of unmanned vehicles [6,7], models of migration and demographic processes [8][9][10], etc. are well known.…”