Developing an integrative Modelling Language for enhancing road traffic simulations

Road traffic is a pervasive aspect in modern societies that affects millions people. The study of its multiple aspects is a very demanding task. Due to its complexity, traffic simulations become a key tool. Their development demands multidisciplinary teams, where communication problems are frequent. Model-driven engineering alleviates this situation providing graphical instruments for designing Modelling Languages (MLs) and semi-automatic transformations. This work presents a model-driven infrastructure composed by an integrative ML, a model editor, and a code generator. The ML is based on related literature and facilitates modelling different theories and simulations based on them. It considers the roles of individuals involved in road traffic, and partially adopts agent-based methodologies to model their decision-making. A case study shows how to produce a simulation specification adapting an existing traffic theory to the ML, and adjust this specification to a simulation platform for testing. It provides the basis for comparison with related work.