Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation

Hoffmann, Benjamin; Urquhart, Neil; Chalmers, Kevin; Guckert, Michael

Abstract

Multi-agent systems may be considered appropriate tools for simulating complex systems such as those based around traffic and transportation networks. Modelling traffic participants as agents can reveal relevant patterns of traffic flow. Upsurging traffic in urban areas increases the relevance of such simulations and the insight they provide into reducing congestion and pollution. Developing multi-agent traffic simulations is a challenging task even for professional software developers. In contrast, domain experts need tools that can be quickly adapted to new questions emerging in their research without potentially error-prone communication with software developers. There is a need for simulation tools that are intuitive to domain experts yet flexible and adaptable by software developers as required. A model driven approach with an extensible domain specific language delivers an answer for both of these opposing requirements. The modeller is relieved from implementing time consuming programming details and can focus on the application itself. We present the domain specific language Athos that allows to create simulations of traffic and transport related problems declaratively. The models are platform independent and executable code can be generated for appropriate multi-agent platforms. The language is flexible and can be easily extended by exploiting the structure of the problem domain itself. In this paper, we present Athos and focus on how it can be extended by arbitrary traffic and routing algorithms through an annotation-based extension mechanism.

Citation

Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2020, February). Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation. Presented at Modelling 2020, Vienna

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Modelling 2020
• Start Date: Feb 19, 2020
• End Date: Feb 21, 2020
• Acceptance Date: Nov 28, 2019
• Publication Date: 2020
• Deposit Date: Jan 16, 2020
• Publicly Available Date: Jun 12, 2020
• Pages: 141-156
• Series Title: Lecture Notes in Informatics (LNI)
• Series ISSN: 1617-5468
• ISBN: 978-3-88579-696-1
• Public URL: http://researchrepository.napier.ac.uk/Output/2383940