A framework for a multi-agent traffic simulation using combined behavioural models

摘要

The task of simulation of urban processes often concerns city traffic and road dynamics. Many assumptions in an urban science may be made by analysing traffic flows and vehicle behaviour on city streets. Since road traffic is a dynamic and possibly spatially large system that depends on many external conditions, approaches like visual analysis and computational steering may be used. There are many traffic modelling frameworks presented in the field, but there are also several drawbacks most of them have: they are limited to a specific model or case; have abstracted logic which disregards some factors affecting vehicle movement; they ignore possible physical interactions which are not described in a model or use too many simplifications in vehicle interaction simulations. In this paper, a novel agent-based traffic modelling framework is presented, combining different classes of traffic models into a single vehicle agent and allowing the user to set a specific model for each supported class. The framework was made using a game engine, Unreal Engine 4, which allows users to model realistic interaction between vehicles and make realistic visualisations for purposes of visual analysis and computational steering.