The SYNCHROMODE Project has been part of the publication of a research paper in this early spring 2025. The paper, titled “A Data-Driven Decision Support System for Multimodal Network and Traffic Management – SYNCHROMODE’, has been published in the conference proceedings “Climate Crisis and resilient transportation System, Lecture Notes in Intelligent Transportation and Infrastructure”, Springer editions, of the 7th Conference on Sustainable Mobility, CSuM2024.
The paper highlights the role of innovative and disruptive technologies as well as new mobility solutions to tackle the challenges defining the transport network and traffic management. Indeed, the European transportation network is facing significant challenges including traffic congestion, safety concerns, greenhouse gas emissions and associated costs.
To address these issues, SYNCHROMODE develops a data-driven decision support system aimed at enhancing multimodal network and traffic management.
The paper presents the development process for this system, which incorporates the data quality assessment, the modelling and simulation of multimodal transport, traffic prediction, network optimization techniques, and definition of novel multimodal Key Performance Indicators (KPIs).
The proposed system facilitates the prediction and optimization of multi-modal transport supply and demand data, the instantaneous and effective reaction to and management of various types of events, both planned and un-planned, as well as the communication and coordination of the various in-volved actors. The practicality and effectiveness of elements of this toolbox will lead to the creation of three distinct services, and specifically those of:
The services of the SYNCHROMODE Toolbox will be assessed in three case studies in Greece (Thessaloniki), the Netherlands, and Spain (Madrid), emphasising their potential to transform the transport network and traffic management across Europe.
In the paper, you will find the project’s objectives and scope, the methodology, the case studies applications as well as the challenges faced, and lessons learnt during the first year of the project.
The authors Evangelos Mitsakis, Dimitris Tzanis, Viktoria Petkani, Alexandros Dolianitis, Evangelos Mintsis, Areti Kotsi & Vasileios Psonis are affiliated to the Centre for Research and Technology Hellas – Hellenic Institute of Transport in Thessaloniki, Greece.
Access the publication and the full paper here: A Data-Driven Decision Support System for Multimodal Network and Traffic Management – SYNCHROMODE | SpringerLink
