Proceedings of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS)

DOI: http://dx.doi.org/10.15439/2025F8576

Citation: Proceedings of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS), M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 43, pages 351–356 (2025)

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Abstract. As urban centres increasingly adopt smart mobility solutions to address congestion, emissions, and transport efficiency, the demand for seamless integration among diverse services, such as ride-sharing, public transport tracking, electric vehicle infrastructure, and autonomous systems, continues to grow. However, current integration approaches are often rigid and monolithic, limiting scalability, adaptability, and real-time responsiveness. Digital twins offer a promising framework to dynamically model and manage urban mobility systems, but existing implementations frequently fall short due to tight coupling and limited modularity. This paper introduces a microservices-based digital twin architecture designed to enable flexible, scalable, and real-time integration of heterogeneous smart mobility services. By decoupling functionalities into independently deployable services that contribute to a unified city-wide model, the proposed architecture supports dynamic updates, fast iteration, and robust interoperability. The paper outlines related research, design principles, and system architecture, and presents a case study to validate the approach. Preliminary results demonstrate that a microservices-enabled digital twin can effectively overcome the limitations of current monolithic systems, paving the way for more agile and resilient smart mobility ecosystems. A key originality of the proposed architecture lies in its implementation approach: simulations are embedded within scenarios and sub-scenarios, enabling modular, workflow-driven orchestration of complex mobility analyses. This design allows for a structured and extensible integration of simulation services, tailored to evolving urban dynamics and decision-making needs.

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