The European transportation sector confronts significant challenges, in-cluding traffic congestion, safety concerns, greenhouse gas emissions, and associated costs. The development of disruptive technologies and the emer-gence of new mobility solutions generate a revolution in the transport net-work and traffic management. To address these issues, SYNCHROMODE introduces an innovative data-driven decision support system, aimed at en-hancing multimodal network and traffic management. This paper presents the development process for this system, which incorporates the data quali-ty assessment, the modelling and simulation of multimodal transport, traf-fic 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, the instantaneous and effective reac-tion 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 a) Network-wide data exchange and integration, b) Cooperative dashboard for real-time monitoring and prediction of network-wide multimodal transport and traffic, and c) Resilient multimodal transport network and traffic management support tool. The services of the SYNCHROMODE Toolbox will be assessed in three case studies in Greece (Thessaloniki), the Netherlands, and Spain (Madrid), highlighting their potential to revolution-ize transport network and traffic management across Europe.


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    Title :

    A Data-Driven Decision Support System for Multimodal Network and Traffic Management – SYNCHROMODE


    Additional title:

    Lecture Notes in Intelligent Transportation and Infrastructure



    Conference:

    Conference on Sustainable Urban Mobility ; 2024 ; Kalivia Filaktis, Greece September 04, 2024 - September 06, 2024



    Publication date :

    2025-03-10


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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