A Case Study of the Development of an Agent-based Simulation in the Tra ffi c Signal Control Domain using an MDD Approach

Model-driven development (MDD) is an approach for supporting the development of software systems, in which high-level modeling artifacts drive the production of low-level, time and effort-consuming artifacts, such as source code. Previous work on its use showed that it significantly increases development productivity, given that the effort is focused on the business domain instead of technical issues. However, MDD was exploited in the context of agent-based development in a limited way, and previous work has not shown real evidences of the benefits that MDD promotes in this context. In this paper, we explore the use of MDD in agent-based modeling and simulation. We conducted a case study in the traffic signal control domain, in which autonomous agents are in charge of managing traffic light indicators to optimize traffic flow. We propose an MDD approach, composed of a modeling language, and model-to-code transformations for producing runnable simulations. An empirical study provides evidence that our MDD approach reduces the effort to develop agent-based simulations.

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